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Speaker 1: Alz Media.

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Speaker 2: Hell and welcome to this week's Better Offline. I'm, of

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Speaker 2: course your host ed Zittron and for this week's episode,

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Speaker 2: I flew out to North Carolina to do a longer

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Speaker 2: form interview, the first of it's kind on the show,

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Speaker 2: a little slower, a little more fun, and I did

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Speaker 2: it with Steve Burke, founder and host of gamers Nexus,

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Speaker 2: an incredible hardware YouTube channel that's been going since two

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Speaker 2: thousand and eight and has over two and a half

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Speaker 2: million subscribers. We talked about the history of gamers Nexus,

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Speaker 2: the state of the hardware industry, tech journalism, gamers Nexus

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Speaker 2: is incredibly scientific approach to hardware testing, and of course

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Speaker 2: a little bit about AI. I think you're going to

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Speaker 2: really like it enjoy. So how long has the channel

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Speaker 2: been running? How long have you been doing this? Now?

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Speaker 1: About seventeen years and five months.

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Speaker 2: And we started off just doing gaming content. I did

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Speaker 2: go back in the files and found like a Modern

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Speaker 2: Warfare trailer I think, and then the Office Space parody,

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Speaker 2: which is awesome.

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Speaker 1: Yeah. Yeah.

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Speaker 3: So it started as game reviews and trailer analysis videos,

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Speaker 3: which was the Modern Warfare one and battlefield trailer analysis

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Speaker 3: that was like a whole subgenre. Back then you got

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Speaker 3: the trailer, you kind of picked apart what's going to

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Speaker 3: be in this game? And you know, then I did

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Speaker 3: game interviews. We spotlighted a bunch of indie games through

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Speaker 3: Steam's green Light program, and it kind of slowly got

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Speaker 3: into hardware.

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Speaker 2: What was Greenlight? Is that? Like? Is that kind of

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Speaker 2: the early early access.

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Speaker 3: Yeah, that was Steam's thing where they gave indie developers

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Speaker 3: who are unestablished kind of a way to try and

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Speaker 3: get onto Steam.

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Speaker 1: And so we did a lot of early coverage of games.

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Speaker 2: Yeah, I saw you doing a lot of convention interviews.

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Speaker 2: How did you grow from there to where you are today?

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Speaker 2: Which is said huge studio and massive testing facilities and such.

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Speaker 3: The interviews and the stuff at the conventions was kind

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Speaker 3: of the turning point for me because I was up

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Speaker 3: until maybe twenty twelve or something like that plus and

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Speaker 3: minus year, I was still technically in college. And then

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Speaker 3: I went to I went to pas Penny Arcade XPO.

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Speaker 3: I think I went to the twenty ten to one,

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Speaker 3: and after I got home from that, I decided, this

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Speaker 3: is kind of the only thing I want to do

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Speaker 3: go to stuff like this, And so it took me

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Speaker 3: two years but you know, eventually just dropped out and

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Speaker 3: then yeah, then just started doing more of those, and

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Speaker 3: it was it was the best way. First of all,

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Speaker 3: they're just fun, but then secondly it was sort of

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Speaker 3: how I started actually meeting the people we would end

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Speaker 3: up working with in the hardware industry.

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Speaker 2: Right, and did Well, how'd you get into testing? Because

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Speaker 2: I found one of you, I think your first viral clips,

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Speaker 2: which was the testing a power supply with a paper clip,

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Speaker 2: I believe.

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Speaker 3: Oh that was the that was to jumpstart a power

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Speaker 3: supply to yeah, test it, yeah, to make sure it works.

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Speaker 2: So how did you move into that? Because it it

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Speaker 2: seemed like it took a minute to get there.

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Speaker 3: Yeah, so I think around So I started the site

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Speaker 3: in two thousand and eight, I think officially, and then

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Speaker 3: got into publishing PC build guides in around twenty ten

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Speaker 3: or so. So that's when the hardware really started. And

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Speaker 3: I'd already been building computers but hadn't actually really published

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Speaker 3: much about it, So start publishing build guides. I think

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Speaker 3: it was just as simple as those were the first

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Speaker 3: thing that had any kind of like readership because it

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Speaker 3: was all articles back then, right, and so they were

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Speaker 3: so you started out writing yeah, exclusively, and then the

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Speaker 3: channel got added in two thousand and nine, but it

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Speaker 3: wasn't treating you know, YouTuber was not that's not a

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Speaker 3: job in two thousand and nine like that. Yeah, it's

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Speaker 3: a little before you like you had maybe Casey Nystadt

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Speaker 3: was at the front edge of that.

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Speaker 2: Yeah, I think I think it was like maybe Vine

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Speaker 2: was it was, it was still around when did Vine

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Speaker 2: pop up? Christ it was still asl but no back then,

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Speaker 2: so you were just on the fringe of this new content.

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Speaker 1: Yeah, and it was.

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Speaker 3: I did not start a YouTube channel with the intent

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Speaker 3: of making it a job, because I don't. If you

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Speaker 3: go on Internet archive, I didn't actually even remember this

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Speaker 3: until recently. And you look at the gamers Excess website

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Speaker 3: and you go to the about page from like two

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Speaker 3: thousand and eight or nine or ten, you'll see that

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Speaker 3: somewhere in those really early years, I had said that

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Speaker 3: we were running it without any form of banner ads,

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Speaker 3: which is actually true today too. We got rid of

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Speaker 3: the ads when we reintroduced the website recently. Right, But

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Speaker 3: like point being, you don't do that having no revenue

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Speaker 3: unless you aren't really thinking about trying to make it

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Speaker 3: a sustainable thing.

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Speaker 1: Right, it was purely for fun.

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Speaker 2: And how did it become a sustainable How did it

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Speaker 2: become your main job?

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Speaker 1: Yeah?

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Speaker 3: I think as YouTube grew basically, so we were kind

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Speaker 3: of in the early We weren't the first sort of

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Speaker 3: i'll call it generation of YouTubers who were able to

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Speaker 3: successfully make it a job, but I would say we were

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Speaker 3: maybe in the next generation right after that. And so yeah,

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Speaker 3: I started publishing more videos alongside the articles. So it

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Speaker 3: really was with case reviews computer case reviews, where we

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Speaker 3: would originally just focus on only writing a case review.

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Speaker 3: At some point, I'm saying we a lot. For a

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Speaker 3: while it was just me and then every now and

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Speaker 3: then it'd be soone to.

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Speaker 1: Help, but we would do case reviews.

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Speaker 3: And then I realized this would do well with video

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Speaker 3: because there's depth to it and there's like just a

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Speaker 3: lot of mechanical stuff, and those videos started doing pretty okay.

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Speaker 2: And did you move away? When did you move away

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Speaker 2: from the website, because I know you've come back to it.

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Speaker 3: Yeah, we probably around twenty I think around twenty eighteen

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Speaker 3: maybe is when I kind of like mothballed it basically

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Speaker 3: for a couple of years. And that was just because

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Speaker 3: at that point, we had just moved out of the

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Speaker 3: house and into an office and then into the first office,

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Speaker 3: and there was just too much content flow on the

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Speaker 3: video side. And up until that point, I was the

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Speaker 3: only one who was capable of maintaining the site and

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Speaker 3: publishing to it, not because it was a special skill,

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Speaker 3: but because the website was so completely fucked up and

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Speaker 3: cobbled together because.

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Speaker 2: I didn't have a CMS or anything it did, but

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Speaker 2: I built it like, oh so right, okay, yes.

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Speaker 3: So I had a CMS, but I had stuff bolted

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Speaker 3: onto it over twelve.

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Speaker 2: Years classic CMS. Shit.

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Speaker 1: Yeah, and I'm not a professional web developer.

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Speaker 2: And don't worry, most CMS developers on either.

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Speaker 1: Yes, that was something I came to realize. And so anyway,

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Speaker 1: it's just more and more, you know.

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Speaker 3: All the pieces were falling off the car while I

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Speaker 3: was driving it, and eventually I was like, I can't,

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Speaker 3: I can't, Like I have to just do one thing

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Speaker 3: and YouTube is not a platform I need to maintain,

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Speaker 3: which is good and bad. Yes, but yeah, we kind

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Speaker 3: of put the website on ice for a while and

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Speaker 3: then it wasn't until Wendell for Level one Text eventually

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Speaker 3: approached me and he was like, hey, I'm a web

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Speaker 3: developer actually, and he really wanted us to get our article,

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Speaker 3: our content script preserved in article form again, right, because

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Speaker 3: he's worried about just the loss of information you know

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Speaker 3: through video, right, And so he set us up to

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Speaker 3: where now people on the team like Jimmy are able

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Speaker 3: to maintain the site.

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Speaker 2: That's really cool. Yeah, and you've brought it back though

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Speaker 2: you're somewhat more fun Like is it do you ever

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Speaker 2: see the website growing into more of a media outlet

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Speaker 2: or is it just and is it just you writing

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Speaker 2: it as well?

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Speaker 3: Yeah, it's just us, you know, it's the same team.

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Speaker 3: It's the it's basically the video scripts that the team

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Speaker 3: rights converted into an article and so sometimes like it's not.

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Speaker 1: Going to read as naturally as a pure article.

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Speaker 3: Might, but we try to adapt it and if there's

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Speaker 3: any right now to me, it's like sort of a

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Speaker 3: community resource where I know for us, at least internally,

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Speaker 3: it's way more useful to have words, right, you.

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Speaker 1: Know, just skin through and control app than a video.

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Speaker 3: But also just like preservation wise, it's easier to preserve

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Speaker 3: articles and videos.

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Speaker 2: Are you how is YouTube as a platform though, is it?

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Speaker 2: Are you a slave to the algorithm so much do

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Speaker 2: you try and appeal to it? Do you just make content?

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Speaker 3: I think their YouTube has a platform. There's a lot

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Speaker 3: of ways to feel about it. For me, it's it's

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Speaker 3: almost like asking me how I feel about water at

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Speaker 3: this point, right, you know, it's like, how do you

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Speaker 3: feel about water?

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Speaker 1: It's like, well, I mean, if I don't drink it,

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Speaker 1: I die.

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Speaker 3: But like YouTube, it's it's not something I try to

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Speaker 3: game or play to.

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Speaker 1: It's basically just a fact of life, right, you know.

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Speaker 3: It's like it's it's there, and I have to think

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Speaker 3: about it, and every now and then I'll probably complain

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Speaker 3: about it. But realistically, I personally, I think it's kind

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Speaker 3: of a fool's errand to chase quote unquote the algorithm

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Speaker 3: too much because it kind of stifles and takes focus

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Speaker 3: away from the thing that actually matters, which is the content,

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Speaker 3: you know, and so like, yeah, there's things you can do,

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Speaker 3: like you can play with the thumbnail or the title,

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Speaker 3: but what I really wouldn't want to do is change

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Speaker 3: the actual type of content that's been produced just for

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Speaker 3: algorithmic purposes, because I think that that also creates kind

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Speaker 3: of like a almost like a black hole of creativity

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Speaker 3: where you stop producing the content for the purpose it

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Speaker 3: was intended and you start producing the content to be

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Speaker 3: a farm. To use your phrase, at that point, become

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Speaker 3: basically a slave to the algorithm where you can't escape it.

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Speaker 1: Once you start doing that, I think.

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Speaker 2: Yeah, at that point, you'll coverage is just dancing for

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Speaker 2: somebody else who changes their mind constantly.

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Speaker 3: Right exactly, because it's you no longer know who the

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Speaker 3: viewer is. And it's impossible to know what YouTube wants

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Speaker 3: because YouTube doesn't know what it wants. You could probably

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Speaker 3: ask a YouTube bene near a pointed specific question right

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Speaker 3: about the algorithm and they would probably tell you they

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Speaker 3: don't know.

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Speaker 2: So and has that has your experience with them being

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Speaker 2: chaotic or is it?

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Speaker 4: Uh?

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Speaker 1: No, because believe it or not, they don't talk to us.

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Speaker 2: So, I mean, I've heard content creators who do argue

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Speaker 2: with them. I've heard ones that don't talk to them

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Speaker 2: at all. It's interesting to hear, especially your your two

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Speaker 2: point six million this I think so yeah, that they

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Speaker 2: don't interact.

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Speaker 3: Yeah, So there was a period where they would assign

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Speaker 3: basically a channel rep to you, and so I would

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Speaker 3: get on a call, I don't know, somewhere around maybe

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Speaker 3: it wasn't the high hundreds of thousands of subs, And

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Speaker 3: that was kind of cool because like, Okay, if something

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Speaker 3: catastrophic happens, like let's just say, I don't know whatever,

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Speaker 3: I get locked out of my account because I fudge

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Speaker 3: the password too many times, something stupid like that, Right,

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Speaker 3: like I at least have someone I can talk to.

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Speaker 1: Those people were rotated through.

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Speaker 3: Revolving door basically every three or four months, so right

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Speaker 3: when you start to know the person and they can

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Speaker 3: help you, they're gone. And that was by design, I think,

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Speaker 3: as far as I understood it, that program got killed.

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Speaker 3: We don't have a REP now, which is normal, and

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Speaker 3: and the best I have is a a liaison. He's

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Speaker 3: called and he's a great guy. He's very nice. It's

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Speaker 3: not really his job, you know, to help us, but

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Speaker 3: he does it because he's a nice guy, and so

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Speaker 3: he's like the guy for like dozens of creators.

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Speaker 2: Yeah, it's just so bizoved to me that there isn't

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Speaker 2: a specific rep with with other people. But like a

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Speaker 2: rep whose job it is to kate, you would think

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Speaker 2: that your entertainment talent on some level, you'd.

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Speaker 3: Think they'd want to be available to help, and I'm

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Speaker 3: sure if you asked Google they would say that they

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Speaker 3: do want to be available to help, and they are

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Speaker 3: and you can tweet at them, you know.

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Speaker 2: Yeah, great. Yeah, but that's the weird thing about these platforms.

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Speaker 2: It does feel like they're like they benefit as much

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Speaker 2: as possible while providing.

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Speaker 3: So the revenue share is public, you know, for ad

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Speaker 3: Sense YouTube ad Sense, so tho's the ads before after,

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Speaker 3: in the middle of videos whatever. I think it's forty

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Speaker 3: five fifty five, with them getting forty five percent.

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Speaker 1: For perspective something like Steam.

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Speaker 3: I'm not an expert on this, but the last nieber

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Speaker 3: I saw was something like thirty percent for Steam, and

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Speaker 3: I think it's very able dependent on them for them, yeah,

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Speaker 3: for them, So you know, YouTube certainly benefits.

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Speaker 1: They to argue in their favor, Hosting videos is unbelievably expensive,

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Speaker 1: so I get it.

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Speaker 2: I didn't know that.

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Speaker 1: Yeah, yeah, well the split's pretty high.

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Speaker 3: I'm okay with it, Like I actually, I'm fine with

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Speaker 3: it with them getting forty five percent or whatever. It

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Speaker 3: is a bad sense because they don't impose restrictions on

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Speaker 3: things like us selling our own ads, right, So it's

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Speaker 3: like I don't really care, you know, and I don't

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Speaker 3: care if people block ads on our channel or whatever.

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Speaker 1: I don't give a shit.

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Speaker 3: But like the I think it's it's only if if

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Speaker 3: they ever overstep and they start restricting what you're allowed

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Speaker 3: to put in your content in a way that beyond

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Speaker 3: like I don't know, whatever they have their own rules

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Speaker 3: about like hate.

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Speaker 1: Speech and stuff like that.

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Speaker 3: Right, it is fam Yeah, but like in terms of

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Speaker 3: if they start restricting, let's just say they decide, yeah,

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Speaker 3: you're not allowed to sell merch without giving us a cut.

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Speaker 1: No, then I'd have a big.

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Speaker 2: Propool style is the YouTube way you make most of the.

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Speaker 3: Revenue in one way or another. Yeah, I mean YouTube

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Speaker 3: is the reason it's possible to do any of this

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Speaker 3: because I was doing it as articles only, and YouTube

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Speaker 3: didn't really become a focus until I said, like twenty

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Speaker 3: eighteen or so as a primary source.

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Speaker 1: And so yeah, through.

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Speaker 3: Mostly merchandise sales on our store, through Patreon support, which is,

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Speaker 3: you know, the monthly donations from viewers, and then sort

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Speaker 3: of after that it's like ads we sell.

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Speaker 2: And then ad sense right and wait, so you spent

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Speaker 2: like a decade mostly just writing pretty much.

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Speaker 3: Yeah, probably probably till I would say, like till twenty fifteen,

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Speaker 3: very seriously focused, not only writing.

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Speaker 2: Yeah, so was that your full time thing? Did you

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Speaker 2: have other jobs as well?

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Speaker 3: I did several side quests? Yes, I would collect side

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Speaker 3: quests from local business owners, you know, like Greeting's adventure.

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Speaker 1: I need a local website. Can you build that for me?

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Speaker 2: It's a living, as they say in the Flintstones, it's

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Speaker 2: and let's actually get really not necessarily super specific. But

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Speaker 2: what's your history, like, without getting to biographical, like how

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Speaker 2: did you come in to do? Are you? Were you

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Speaker 2: just naturally interested in this? Was this just a childhood thing?

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Speaker 1: I guess depends how far back we go.

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Speaker 3: But gaming was always an interest and continues to be

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Speaker 3: an interest, of course, I don't know. I mean the

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Speaker 3: first game I played was probably Lemmons.

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Speaker 2: Hell yes, yeah, hell yes Humans for me? Yeah yeah,

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Speaker 2: like first Lemmings game, yeah yeah, hell yes. Now I'm

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Speaker 2: so you were primarily a PC gamer though, yeah.

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Speaker 1: For sure?

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Speaker 3: Yeah so Lemmons, and then there are some other ones

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Speaker 3: back then, and uh I played a lot of nes

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Speaker 3: S nes N sixty four game, keep all that stuff,

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Speaker 3: a lot of Nintendo eventually.

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Speaker 1: Got a PS two as well.

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Speaker 3: But but after the N sixty four era, so like

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Speaker 3: early two.

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Speaker 1: Thousands was when I built my first computer.

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Speaker 3: Right before that, I was playing games like Command and Conquer,

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Speaker 3: Red Alert, yeah, and things things of that nature on

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Speaker 3: what you know. This was back when every family had

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Speaker 3: a quote unquote computer room, right, yeah, like there was

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Speaker 3: a room for the computer.

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Speaker 2: Or a nook in Mike England's so small.

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Speaker 3: Right yeah, but like point being where it's just like

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Speaker 3: this is the this is the dedicated computer area for

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Speaker 3: the computer, this household chair.

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Speaker 2: Yes.

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Speaker 3: So I played games on that built computer, you know,

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Speaker 3: early twenty penny and four and remained interested, and I

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Speaker 3: guess I started really getting more interested in the coverage

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Speaker 3: when we don't feel free to ask a file up

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Speaker 3: if you're interested in this.

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Speaker 1: But basically I was running like a gaming guild like

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Speaker 1: group of friends, you.

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Speaker 2: Know, nice So well, what were you gaming together? Is that? Yeah?

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Speaker 3: Counter Strike, Source Age, Evampires three ever, request, things like

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Speaker 3: that you played?

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Speaker 2: Request?

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Speaker 1: Yeah?

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Speaker 2: Whatsoever?

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Speaker 3: I think I was on Kurana, I was on the Raith,

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Speaker 3: I was moving. I think Karana merged into the race.

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Speaker 2: I went on storm Hammer as well. I paid the

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Speaker 2: extra It was not worth it, man, oh, good to know. Yeah,

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Speaker 2: same scars.

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Speaker 1: Then I interviewed Brad McQuaid.

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Speaker 2: I have a long and storied history of being a

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Speaker 2: problem for Sony online. Statement asking like the one British

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Speaker 2: journalist who asked any questions about this game, I got

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Speaker 2: in lots of trouble.

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Speaker 1: Ever, ever quest I remember buying it.

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Speaker 3: When I bought it was when it was sort of

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Speaker 3: demonized in some media as yeah, and also though specifically

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Speaker 3: as like the don't there was like some kind of

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Speaker 3: devil worshiping, like whatever, kind of like D and D. Right, Yeah,

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Speaker 3: D and D got the same treatment.

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Speaker 2: They didn't, but they didn't seem to have a problem

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Speaker 2: with the fact that getting to level fifty was a job.

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Speaker 2: Right you had to work eight hours a day. Yeah,

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Speaker 2: Oh god, so you had this guilt?

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Speaker 1: Sorry?

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Speaker 3: Yeah, And long story short. The website I had built

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Speaker 3: for that group of friends with a forum that had

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Speaker 3: all these gaming guides on it, we worked.

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Speaker 1: Very hard on. As you know, we were pretty at

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Speaker 1: that point.

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Speaker 3: We were mostly high school early college age at the

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Speaker 3: at the highest end, and everyone put a lot of

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Speaker 3: effort into making these guides. And then at one point

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Speaker 3: the website was hacked by just some common CMS breach, right,

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Speaker 3: and I didn't know how to to restore from backup

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Speaker 3: and didn't really know what I was doing, so I

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Speaker 3: lost all the data. And so you could imagine for

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Speaker 3: a group of like teenagers, losing gaming guides is like devastating.

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Speaker 1: Yeah, it's like here, like my life's work. A guy

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Speaker 1: for how to rush and Asian Vampires.

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Speaker 2: Yeah, oh my, well, I mean that was game e

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Speaker 2: fa ques there, I guess, but yeah, if you were

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Speaker 2: making your own, they can't have been that good on

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Speaker 2: game efic hues.

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Speaker 1: Yeah.

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Speaker 2: So the Library of Alexandria that yeah, sorry.

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Speaker 3: Yeah, yeah, so we lost that and that's when I

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Speaker 3: made a new website and that was the Gamer's next

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Speaker 3: to site.

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Speaker 2: So so you're all self taught then pretty much?

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Speaker 1: Yeah.

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Speaker 3: I mean self taught in the sense that there's not

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Speaker 3: a lot of formal education, not self taught in the

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Speaker 3: sense that the people I've worked with over the years,

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Speaker 3: especially engineers in the industry, are the ones who actually

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Speaker 3: taught me a lot. Yeah, right, but nothing formal, I guess.

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Speaker 1: Yeah.

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Speaker 2: And it seems that something I've noticed with your coverage

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Speaker 2: and actually the surrounding channels is it seems like people

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Speaker 2: in hodware are relatively generous with that time, like there

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Speaker 2: are some people who want but like a lot of

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Speaker 2: the scientific people seem very key to it and want

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Speaker 2: to help and make sure there's understanding.

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Speaker 1: Yeah, I think so.

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Speaker 3: I think people like the person who comes to mind

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Speaker 3: immediately is Tom Peterson, who currently works at Intel, used

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Speaker 3: to working on video.

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Speaker 1: But he's the type of guy where.

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Speaker 3: When you talk to him you can tell he's not

402
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Speaker 3: in it because he's trying to sell Intel's or previously

403
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Speaker 3: on videos product. He's in it because he likes the technology, right,

404
00:19:31,280 --> 00:19:33,399
Speaker 3: And so people like that, I think they tend to

405
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Speaker 3: be happy to just share yeah.

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Speaker 2: Which is really cool. And other YouTube channels as well

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Speaker 2: seem like Lewis Rossman around Box, they seem like very

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Speaker 2: they want to collaborate, which is really cool.

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Speaker 1: Yeah. Yeah Rossman and Steve from hard run Box. I've

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Speaker 1: done a lot of videos with Yeah.

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Speaker 2: You're having fun, yes, because there's a lot of cynicism

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Speaker 2: and kind of depression in media because of the job environment,

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Speaker 2: but there's also even above that seems like just a

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Speaker 2: depression around the work, but it doesn't. It seems more

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Speaker 2: fun what you're doing, and they indeed throughout the hogware people.

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Speaker 3: I think it's one of the things I kind of

417
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Speaker 3: really actively spend a lot of time managing, is trying

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Speaker 3: to make sure there's a cadence to the content where

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Speaker 3: we actually just did this recently. I kind of look

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Speaker 3: at it and it's like, all right, this is We've

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00:20:19,320 --> 00:20:21,600
Speaker 3: had a lot of heavy stuff recently. We had tariffs

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Speaker 3: into black Market, into Bloomberg, you know whatever, and so

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Speaker 3: then we switched to publishing more folks on reviews methodology.

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Speaker 1: I ran a review of a toy story.

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Speaker 2: Computer which I've seen and it's insanely cool. Yeah, I

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Speaker 2: actually kind of I don't know how good it is inside,

427
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Speaker 2: but I love the look of it.

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Speaker 1: Fine, I had problems with shipping.

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Speaker 3: But but the point being, you know, we we do

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Speaker 3: try to, like I try to manage what the tone

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Speaker 3: of the content is and for how long, because you

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Speaker 3: just you don't want to lose the fun of it,

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Speaker 3: you know, And so yeah, I would say I would

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Speaker 3: say also, even when it is a story that might

435
00:21:00,760 --> 00:21:04,360
Speaker 3: be more maybe categorized as depressing, so like if you're

436
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Speaker 3: covering some kind of corruption or something in the industry,

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Speaker 3: there is still.

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Speaker 1: Fun to the job.

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00:21:13,480 --> 00:21:16,639
Speaker 3: Of covering that thing where like the fun part is

440
00:21:16,680 --> 00:21:20,520
Speaker 3: not necessarily the topic. It's the trying to piece together

441
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Speaker 3: something that's like really complex and figure out how to

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Speaker 3: explain it to anybody.

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Speaker 2: I mean, the GPU tariffs, the tarrist one and the

444
00:21:27,800 --> 00:21:32,119
Speaker 2: GPU black market stuff was very seemed like it probably

445
00:21:32,160 --> 00:21:33,720
Speaker 2: sucked a little of your soul out, but that looked

446
00:21:33,720 --> 00:21:35,480
Speaker 2: like fun. It looked like a fun ben.

447
00:21:35,760 --> 00:21:37,760
Speaker 3: Is I mean, the tarist one, you know, it was

448
00:21:37,920 --> 00:21:40,240
Speaker 3: It's a story that there were people we spoke to

449
00:21:40,320 --> 00:21:43,679
Speaker 3: who are very negatively affected, and you feel for those people.

450
00:21:43,720 --> 00:21:46,520
Speaker 3: And that part is sad if you, you know, put

451
00:21:46,560 --> 00:21:51,080
Speaker 3: yourself in that position. But then on the the kind

452
00:21:51,119 --> 00:21:55,120
Speaker 3: of keeping it fun for yourself covering it side, if

453
00:21:55,119 --> 00:21:56,760
Speaker 3: you really just kind of step back and look at

454
00:21:56,800 --> 00:21:59,920
Speaker 3: it's like how fortunate can you be to for your

455
00:22:00,080 --> 00:22:02,640
Speaker 3: job be like I'm going to get on a plane

456
00:22:03,000 --> 00:22:06,040
Speaker 3: in twelve hours, you know, and fly and then I'm

457
00:22:06,040 --> 00:22:08,119
Speaker 3: not going to know where I'm going next until I

458
00:22:08,160 --> 00:22:11,560
Speaker 3: get there. Like that on its own is pretty fun. Yeah,

459
00:22:11,600 --> 00:22:13,959
Speaker 3: And that's it's very privileged to be able to do

460
00:22:14,040 --> 00:22:16,280
Speaker 3: that and know that at the end of it it's

461
00:22:16,280 --> 00:22:17,360
Speaker 3: going to be fine, you know.

462
00:22:17,520 --> 00:22:20,359
Speaker 2: Right, And so those and those trips were kind of

463
00:22:20,520 --> 00:22:21,440
Speaker 2: semi chaotic.

464
00:22:21,520 --> 00:22:24,360
Speaker 1: Then they're very chaotic. But that's like, that's why it's

465
00:22:24,400 --> 00:22:25,840
Speaker 1: fun because you.

466
00:22:25,960 --> 00:22:28,439
Speaker 2: Got to was it Hong Kong and you immediately like

467
00:22:28,520 --> 00:22:30,520
Speaker 2: got a price sheet for GPU.

468
00:22:30,760 --> 00:22:30,920
Speaker 1: Yeah.

469
00:22:31,000 --> 00:22:33,439
Speaker 3: Yeah, we were speaking with some suppliers and so we

470
00:22:33,480 --> 00:22:37,400
Speaker 3: had a price sheet. Yeah, we went to we went

471
00:22:37,440 --> 00:22:41,119
Speaker 3: to China for that trip. We met a guy we

472
00:22:41,119 --> 00:22:43,960
Speaker 3: weren't planning to meet. He was mister five in the

473
00:22:44,000 --> 00:22:45,640
Speaker 3: video and he was awesome.

474
00:22:45,920 --> 00:22:48,480
Speaker 2: And where do you find these? Is it people come

475
00:22:48,520 --> 00:22:51,040
Speaker 2: to you? Are they connections? I realized YOUNI laterally you

476
00:22:51,080 --> 00:22:52,200
Speaker 2: probably can't onnset.

477
00:22:51,920 --> 00:22:56,440
Speaker 3: But normally I normally I have a source for kind

478
00:22:56,440 --> 00:22:58,480
Speaker 3: of the first link in the chain, right, and then

479
00:22:58,520 --> 00:23:02,679
Speaker 3: it just kind of develops. You meet a person, you

480
00:23:02,760 --> 00:23:05,400
Speaker 3: hopefully leave a good impression with them, and then they

481
00:23:06,000 --> 00:23:07,600
Speaker 3: might say, you know, hey, I know someone who might

482
00:23:07,600 --> 00:23:09,320
Speaker 3: be interested in talking to you, and you kind of

483
00:23:09,320 --> 00:23:11,280
Speaker 3: go from there. And I think the biggest thing is like,

484
00:23:13,119 --> 00:23:17,560
Speaker 3: and this is kind of challenging sometimes, but learning to

485
00:23:17,560 --> 00:23:21,119
Speaker 3: to kind of roll with it where I operate at

486
00:23:21,160 --> 00:23:25,119
Speaker 3: a relatively high level of anxiety in terms of preparedness, yeah,

487
00:23:25,240 --> 00:23:28,080
Speaker 3: you know, and so to have a wrench thrown in

488
00:23:28,080 --> 00:23:29,879
Speaker 3: where it's like, hey, you might be interested in meeting

489
00:23:29,880 --> 00:23:32,840
Speaker 3: this guy. I'm like, well, like my schedule is really

490
00:23:32,840 --> 00:23:35,520
Speaker 3: I have figured it out. You have to be willing

491
00:23:35,560 --> 00:23:36,320
Speaker 3: to deviate from it.

492
00:23:36,520 --> 00:23:39,000
Speaker 2: Yes, that's the only way to there's kind of any

493
00:23:39,040 --> 00:23:40,000
Speaker 2: good broadcast work.

494
00:23:40,080 --> 00:23:41,000
Speaker 1: Yeah, and you pulled it off.

495
00:23:41,160 --> 00:23:44,679
Speaker 2: It's good. So you've got quite an operation here as

496
00:23:44,720 --> 00:23:46,720
Speaker 2: well around how many people work.

497
00:23:46,680 --> 00:23:48,520
Speaker 1: With you day to day.

498
00:23:49,280 --> 00:23:54,440
Speaker 3: It's five to five to ten total day to day,

499
00:23:54,600 --> 00:23:57,120
Speaker 3: so it just depends you know who's doing what each.

500
00:23:57,080 --> 00:24:00,200
Speaker 2: Day, right, And then mostly around editing the videos and stuff.

501
00:24:00,240 --> 00:24:02,480
Speaker 1: A couple editors slash camera operators.

502
00:24:03,640 --> 00:24:08,480
Speaker 3: We have a couple of writers slash testers, so kind

503
00:24:08,480 --> 00:24:11,679
Speaker 3: of like if you're testing the product, you're probably the

504
00:24:11,680 --> 00:24:14,560
Speaker 3: one who's going to write the review that often makes

505
00:24:14,560 --> 00:24:18,160
Speaker 3: the most sense, not always, but and then editors often

506
00:24:18,200 --> 00:24:20,040
Speaker 3: will shoot the b roll they need because they kind

507
00:24:20,040 --> 00:24:22,399
Speaker 3: of they hit a clip, they realize they need something.

508
00:24:23,000 --> 00:24:24,200
Speaker 1: Yeah. And then we've got.

509
00:24:25,960 --> 00:24:29,480
Speaker 3: A remote researcher as well who's been contributing to some

510
00:24:29,520 --> 00:24:30,600
Speaker 3: of the new stories coming up.

511
00:24:30,800 --> 00:24:33,840
Speaker 2: Very cool. Yeah, and how long does the video take?

512
00:24:34,080 --> 00:24:36,560
Speaker 2: Putting aside the obvious ones like the tarist one, which

513
00:24:36,600 --> 00:24:38,639
Speaker 2: I think a little bit different. How long does it

514
00:24:38,680 --> 00:24:42,000
Speaker 2: take to get a review together, or like any particular video.

515
00:24:41,840 --> 00:24:45,280
Speaker 3: A review of I can give you actual numbers. A

516
00:24:45,280 --> 00:24:50,359
Speaker 3: CPU cooler requires forty hours of testing work where there's

517
00:24:50,400 --> 00:24:54,480
Speaker 3: some kind of manual involvement from the technician, so that

518
00:24:54,680 --> 00:24:57,040
Speaker 3: if we have one cooler, that's going to be someone's

519
00:24:57,119 --> 00:25:00,000
Speaker 3: job for one week basically, right and so right now,

520
00:25:00,080 --> 00:25:04,119
Speaker 3: that'll be Mike typically running those tests, and then the

521
00:25:04,280 --> 00:25:07,760
Speaker 3: actual So if I write that review, it probably takes

522
00:25:07,800 --> 00:25:09,760
Speaker 3: me two hours to write it, you know, it takes

523
00:25:09,760 --> 00:25:13,560
Speaker 3: me the runtime plus ten or twenty minutes to film it,

524
00:25:14,160 --> 00:25:18,320
Speaker 3: and then because you obviously have whatever mistakes that you know,

525
00:25:18,359 --> 00:25:21,800
Speaker 3: you do retakes right, so runtime plus hundred twenty minutes,

526
00:25:21,920 --> 00:25:24,400
Speaker 3: and then the editors I would say they typically take

527
00:25:24,400 --> 00:25:28,400
Speaker 3: about eight hours to complete a relatively simple review edit

528
00:25:29,359 --> 00:25:30,320
Speaker 3: plus some camera work.

529
00:25:30,400 --> 00:25:32,480
Speaker 1: So a cooler review you might be.

530
00:25:32,440 --> 00:25:36,200
Speaker 3: Somewhere in the range of fifty to max maybe sixty hours.

531
00:25:36,800 --> 00:25:38,320
Speaker 1: And then something.

532
00:25:38,040 --> 00:25:42,760
Speaker 3: Like like the black Market video. If you don't count

533
00:25:42,800 --> 00:25:46,680
Speaker 3: my time, so if my time is zero, I don't

534
00:25:46,680 --> 00:25:48,520
Speaker 3: remember exactly how many hours we had in it.

535
00:25:48,520 --> 00:25:48,879
Speaker 1: It was.

536
00:25:50,200 --> 00:25:51,680
Speaker 3: I know if you count my time it was over

537
00:25:51,720 --> 00:25:55,040
Speaker 3: three hundred hours. Jesus, it might have been more like

538
00:25:55,080 --> 00:25:58,960
Speaker 3: four hundred. But and then the ASRock motherboard video we

539
00:25:59,040 --> 00:26:03,120
Speaker 3: just did yeah on CPU failures and Azrok boards. That

540
00:26:03,160 --> 00:26:06,959
Speaker 3: one was like with editing and filming time, I think

541
00:26:06,960 --> 00:26:09,080
Speaker 3: that was two hundred and forty hours. So like, that's

542
00:26:09,080 --> 00:26:12,160
Speaker 3: an example of a content piece that we will lose

543
00:26:12,200 --> 00:26:15,800
Speaker 3: money on, but it's like it's subsidized. First of all,

544
00:26:15,840 --> 00:26:18,400
Speaker 3: I don't care because I want to do it. Secondly,

545
00:26:18,600 --> 00:26:21,240
Speaker 3: you do have to pay for it somehow, and so

546
00:26:21,440 --> 00:26:23,880
Speaker 3: for us, we basically we raised so much money from

547
00:26:23,880 --> 00:26:27,600
Speaker 3: the black market video, I'm able to go, Okay, that's paid.

548
00:26:27,320 --> 00:26:29,240
Speaker 2: For, you know, moove me through that situation.

549
00:26:29,640 --> 00:26:32,000
Speaker 1: Yeah, which the Azrok thing.

550
00:26:32,080 --> 00:26:35,520
Speaker 3: So the Azrok thing is they have some kind of

551
00:26:35,720 --> 00:26:38,679
Speaker 3: yet unknown issue that is resulting in the death of

552
00:26:38,840 --> 00:26:42,800
Speaker 3: CPUs expensive ones, and people don't know exactly what it is.

553
00:26:42,880 --> 00:26:45,320
Speaker 3: They haven't been entirely forthcoming about it. It seems like they

554
00:26:45,320 --> 00:26:49,000
Speaker 3: don't know what the fuck's going on. And so we

555
00:26:49,440 --> 00:26:53,199
Speaker 3: got a viewer's motherboard that had killed the CPU and

556
00:26:53,359 --> 00:26:55,800
Speaker 3: did a bunch of diagnostics. This was one of the

557
00:26:56,480 --> 00:26:58,879
Speaker 3: instances where we couldn't come to a conclusion, and we

558
00:26:58,960 --> 00:27:01,439
Speaker 3: decided let's just like, let's just publish everything and maybe

559
00:27:01,480 --> 00:27:02,560
Speaker 3: someone can use it.

560
00:27:02,440 --> 00:27:05,040
Speaker 2: As the company being communicative of they been trying to

561
00:27:05,040 --> 00:27:05,679
Speaker 2: fix things.

562
00:27:05,800 --> 00:27:09,520
Speaker 3: They appear to be trying to fix things, just not

563
00:27:09,640 --> 00:27:12,879
Speaker 3: very successfully. I would not say they've been communicative like

564
00:27:12,920 --> 00:27:14,960
Speaker 3: they haven't. I don't think they've done a good job

565
00:27:15,000 --> 00:27:17,439
Speaker 3: at telling their customers what's going on.

566
00:27:17,880 --> 00:27:20,399
Speaker 2: Right. So, how is your relationship in general with the

567
00:27:20,400 --> 00:27:23,639
Speaker 2: hardware manufacturers you mentioned the Intel. It sounds like you

568
00:27:23,680 --> 00:27:26,560
Speaker 2: have some people who are friendly and yeah, others.

569
00:27:26,280 --> 00:27:27,280
Speaker 1: Yeah, it depends, you know.

570
00:27:27,480 --> 00:27:31,400
Speaker 3: I'm sure you've worked with enough people where the people

571
00:27:31,600 --> 00:27:35,560
Speaker 3: are often different from the company in terms of the stance,

572
00:27:36,320 --> 00:27:41,119
Speaker 3: and it really depends person to person. But generally speaking,

573
00:27:42,359 --> 00:27:46,000
Speaker 3: the companies are able to maintain a fairly open line

574
00:27:46,000 --> 00:27:49,720
Speaker 3: of communication and be relatively mature about even criticisms because

575
00:27:49,760 --> 00:27:54,800
Speaker 3: normally the people actually in between us and their bosses

576
00:27:55,480 --> 00:27:58,080
Speaker 3: are pretty good at their job, right, you know, And

577
00:27:58,080 --> 00:28:02,679
Speaker 3: so like there's a guy at who he's incredible at

578
00:28:02,680 --> 00:28:06,080
Speaker 3: what he does because and I really don't think consumers,

579
00:28:07,240 --> 00:28:08,680
Speaker 3: I think a lot of people don't know this job

580
00:28:08,760 --> 00:28:11,560
Speaker 3: role exists, but it's really important and the role is

581
00:28:11,600 --> 00:28:16,199
Speaker 3: effectively to be like the translator between outside criticism and

582
00:28:16,320 --> 00:28:17,320
Speaker 3: internal action.

583
00:28:17,680 --> 00:28:19,879
Speaker 2: Right right, So not quite a PR role, but like

584
00:28:19,920 --> 00:28:22,040
Speaker 2: a developer. Not quite developer really.

585
00:28:22,200 --> 00:28:26,760
Speaker 3: It's almost like like tech marketing maybe yeah, but like

586
00:28:26,760 --> 00:28:30,879
Speaker 3: they're not really marketing in the traditional sense. But so

587
00:28:30,920 --> 00:28:32,320
Speaker 3: the guy at AMD, he does a really good job

588
00:28:32,320 --> 00:28:34,880
Speaker 3: because he's told me how if we have a criticism.

589
00:28:34,960 --> 00:28:38,360
Speaker 3: I asked me to what happens internally, and he said, well, normally,

590
00:28:38,840 --> 00:28:40,960
Speaker 3: like marketing might go to him and kind of be like,

591
00:28:41,080 --> 00:28:43,240
Speaker 3: what the fuck, Like why did Steve say this? Or

592
00:28:43,360 --> 00:28:46,640
Speaker 3: hardburn boxed or whoever, which is covered by Steve, I guess,

593
00:28:46,840 --> 00:28:48,840
Speaker 3: but they might ask why did the Steve say this?

594
00:28:49,760 --> 00:28:53,760
Speaker 3: And it's his job to figure that out. And he

595
00:28:53,840 --> 00:28:55,560
Speaker 3: was telling me he normally just asked them, well is

596
00:28:55,600 --> 00:28:58,760
Speaker 3: it true? Right, And if they say it's true, then

597
00:28:58,760 --> 00:29:01,360
Speaker 3: he says, well, then make it not true by fixing it.

598
00:29:01,520 --> 00:29:03,240
Speaker 2: See, this is the thing I've run a p off of.

599
00:29:03,360 --> 00:29:05,480
Speaker 2: And it's like when clients come to White they say that,

600
00:29:05,520 --> 00:29:08,320
Speaker 2: I'm like, and many times said why did you do that?

601
00:29:08,640 --> 00:29:08,800
Speaker 1: Right?

602
00:29:09,080 --> 00:29:10,880
Speaker 2: And they say, well, it's not a fair I'm like,

603
00:29:10,960 --> 00:29:12,960
Speaker 2: how is it unfair? Because if you can explain to me,

604
00:29:13,040 --> 00:29:14,800
Speaker 2: I can go and get this fixed, right, you have

605
00:29:14,840 --> 00:29:17,440
Speaker 2: to explain to me for and it is interesting that

606
00:29:17,440 --> 00:29:18,560
Speaker 2: that role has to exist.

607
00:29:18,640 --> 00:29:21,120
Speaker 3: But yeah, I mean, if it's just a communication problem, right,

608
00:29:21,160 --> 00:29:24,480
Speaker 3: if they're like, well, it's it's true, but we didn't

609
00:29:24,720 --> 00:29:27,920
Speaker 3: we don't like it. Yeah, right, so it's got to

610
00:29:27,920 --> 00:29:30,400
Speaker 3: be a real reason. But yeah, most of the companies,

611
00:29:30,440 --> 00:29:32,920
Speaker 3: the relationship is fine.

612
00:29:32,920 --> 00:29:34,360
Speaker 2: When they generally take criticism.

613
00:29:34,400 --> 00:29:38,840
Speaker 3: Well, the people who interface with us take the criticism well,

614
00:29:39,080 --> 00:29:42,400
Speaker 3: because it's just a job. The companies don't always.

615
00:29:42,560 --> 00:29:44,800
Speaker 2: Do you have any executive exposure? Do you know if

616
00:29:44,800 --> 00:29:45,920
Speaker 2: any executives watch?

617
00:29:46,480 --> 00:29:50,560
Speaker 3: I know that Johnson Juan once watched at least part

618
00:29:50,600 --> 00:29:54,400
Speaker 3: of one of our videos, at least because it was

619
00:29:54,440 --> 00:29:57,040
Speaker 3: communicated to me by someone it works.

620
00:29:56,800 --> 00:29:58,400
Speaker 2: With him, all bold, all caps.

621
00:29:59,120 --> 00:30:02,200
Speaker 1: Ye, I was told that he was not thrilled.

622
00:30:02,360 --> 00:30:05,200
Speaker 2: Oh that doesn't that doesn't sound like Jensen. He's usually

623
00:30:05,200 --> 00:30:07,520
Speaker 2: such a cool head. But do you do you know

624
00:30:07,600 --> 00:30:09,480
Speaker 2: if I don't even need names, but do you know

625
00:30:09,520 --> 00:30:11,280
Speaker 2: if there's like a good amount.

626
00:30:10,920 --> 00:30:12,600
Speaker 1: Of them, Uh?

627
00:30:13,160 --> 00:30:17,560
Speaker 3: Sometimes, yeah, I mean we AMD we had a video

628
00:30:18,160 --> 00:30:21,440
Speaker 3: where we were basically like begging them to not fuck

629
00:30:21,520 --> 00:30:24,520
Speaker 3: up the launch of their nine thousand series GPS because

630
00:30:24,600 --> 00:30:28,040
Speaker 3: their competition like no one had showed up for the

631
00:30:28,040 --> 00:30:31,160
Speaker 3: consumer Intel. They were kind of there, but they're like

632
00:30:31,240 --> 00:30:34,800
Speaker 3: not super viable yet. And anyway, I know after that

633
00:30:34,880 --> 00:30:37,440
Speaker 3: video they had emailed us and this wasn't a thread

634
00:30:37,480 --> 00:30:39,920
Speaker 3: I told them was on record, but they'd emailed us

635
00:30:39,960 --> 00:30:44,760
Speaker 3: and said, uh, you know, basically their sort of executive

636
00:30:44,760 --> 00:30:47,840
Speaker 3: marketing team had watched it and they did talk about

637
00:30:47,880 --> 00:30:50,360
Speaker 3: the problems we raised, and that's cool. It seemed like

638
00:30:50,360 --> 00:30:51,480
Speaker 3: they addressed some of them.

639
00:30:51,560 --> 00:30:53,560
Speaker 2: Yeah, do you ever try and get interviews with them?

640
00:30:54,080 --> 00:30:58,360
Speaker 3: Yeah, occasionally, I mean, especially if there's like the Asus

641
00:30:58,400 --> 00:31:03,720
Speaker 3: situation with their warranty as context for people has had

642
00:31:03,760 --> 00:31:08,000
Speaker 3: an ongoing problem with customer support, where people who need

643
00:31:08,040 --> 00:31:11,920
Speaker 3: a warranty field often end up posting online saying they

644
00:31:11,960 --> 00:31:12,440
Speaker 3: got screwed.

645
00:31:12,600 --> 00:31:14,760
Speaker 2: Is this across the board or with specific things?

646
00:31:14,760 --> 00:31:18,520
Speaker 1: Definitely Motherboard. I'm not sure about other categories because I

647
00:31:18,520 --> 00:31:19,000
Speaker 1: really liked the.

648
00:31:19,000 --> 00:31:21,680
Speaker 2: Rock Gangs ally, but have had a few listeners say yeah,

649
00:31:21,720 --> 00:31:24,000
Speaker 2: we've got some warranty issues and it's actually I kind

650
00:31:24,000 --> 00:31:25,520
Speaker 2: of wanted to address that with you in the know.

651
00:31:26,320 --> 00:31:26,840
Speaker 1: Well that one.

652
00:31:26,880 --> 00:31:29,560
Speaker 3: I know a lot about the ally specifically yeah, So

653
00:31:30,400 --> 00:31:33,080
Speaker 3: to like close the loop on the executive question, the

654
00:31:33,600 --> 00:31:38,680
Speaker 3: Asus thing, I we published a series about the warranty problems.

655
00:31:39,400 --> 00:31:44,120
Speaker 3: We proposed a number of fixes, and eventually I really

656
00:31:44,120 --> 00:31:46,560
Speaker 3: pushed them to let us speak to an executive and

657
00:31:46,560 --> 00:31:50,080
Speaker 3: customer support. They put a director of marketing in front

658
00:31:50,120 --> 00:31:53,200
Speaker 3: of us, very very nice guy, yeah, but by his

659
00:31:53,360 --> 00:31:56,440
Speaker 3: job right, And so I kept pushing back in him

660
00:31:56,440 --> 00:31:58,920
Speaker 3: where I was like, look, man, nothing against you. You know,

661
00:31:59,280 --> 00:32:02,360
Speaker 3: you're not the guy. And so they eventually got us

662
00:32:02,400 --> 00:32:05,440
Speaker 3: to the to the right guy, which is something I

663
00:32:05,480 --> 00:32:07,240
Speaker 3: try to remember too.

664
00:32:09,120 --> 00:32:10,360
Speaker 1: We really try.

665
00:32:10,120 --> 00:32:13,600
Speaker 3: To go to executive levels if possible, because if it's

666
00:32:13,680 --> 00:32:15,640
Speaker 3: just some dude who was told to do with in,

667
00:32:16,280 --> 00:32:18,080
Speaker 3: I can't really press him on the decision.

668
00:32:18,160 --> 00:32:20,680
Speaker 2: You can't punish him. It's not really his decision making.

669
00:32:20,480 --> 00:32:23,840
Speaker 3: It's company, yeah, and he's not paid enough to like

670
00:32:24,200 --> 00:32:26,880
Speaker 3: deal with it, you know. So so we try to

671
00:32:26,880 --> 00:32:30,440
Speaker 3: go above that person. And we did the same with

672
00:32:30,520 --> 00:32:32,480
Speaker 3: New Egg. They sat a room.

673
00:32:32,320 --> 00:32:35,080
Speaker 1: Full of like four, I think through four executives with

674
00:32:35,160 --> 00:32:36,800
Speaker 1: us a couple of years ago.

675
00:32:36,880 --> 00:32:40,040
Speaker 3: Yeah, so they a lot of times they'll play ball,

676
00:32:40,080 --> 00:32:43,360
Speaker 3: which like credit to them, you know. But the asues

677
00:32:43,400 --> 00:32:47,240
Speaker 3: ally thing, the long story short on that is, we

678
00:32:48,080 --> 00:32:52,200
Speaker 3: had a defect. I want to say it was like

679
00:32:52,200 --> 00:32:54,880
Speaker 3: the joystick or something. We had some kind of defect.

680
00:32:54,920 --> 00:32:57,560
Speaker 3: We sent it in for actual repair on our unit

681
00:32:57,720 --> 00:33:03,160
Speaker 3: anonymously or you know, as a pseudonym, and they sent

682
00:33:03,240 --> 00:33:06,120
Speaker 3: us a photo of the xtue of the chassis where

683
00:33:06,160 --> 00:33:09,080
Speaker 3: there was a tiny nick, like a tiny tiny crater

684
00:33:09,640 --> 00:33:13,880
Speaker 3: that's basically the size of a pinpoint in the end

685
00:33:14,120 --> 00:33:18,400
Speaker 3: the edge of the chassis that is purely cosmetic. And

686
00:33:18,440 --> 00:33:20,840
Speaker 3: this is something that like we literally put it under

687
00:33:20,840 --> 00:33:23,000
Speaker 3: a microscope to see what they were talking about.

688
00:33:23,160 --> 00:33:24,760
Speaker 2: And they said it wasn't covered.

689
00:33:24,640 --> 00:33:27,240
Speaker 3: And they said that they would have to charge us.

690
00:33:27,320 --> 00:33:29,000
Speaker 3: I forget how much it was. It was like ninety

691
00:33:29,040 --> 00:33:31,560
Speaker 3: or one hundred and eighty or something dollars goodness to

692
00:33:31,680 --> 00:33:34,800
Speaker 3: repair a problem that was unrelated to this cosmetic thing

693
00:33:35,160 --> 00:33:37,400
Speaker 3: and was their fault, and they were trying to use

694
00:33:37,440 --> 00:33:41,160
Speaker 3: it to charge us for the repair. Yeah, so we

695
00:33:41,280 --> 00:33:45,280
Speaker 3: ran that as a story, and you know, I mean

696
00:33:46,040 --> 00:33:51,760
Speaker 3: eventually it was handled, but I don't count it as

697
00:33:51,920 --> 00:33:54,240
Speaker 3: being done correctly if they find out who we are

698
00:33:54,280 --> 00:33:55,040
Speaker 3: and then they fixed it.

699
00:33:55,120 --> 00:33:56,719
Speaker 2: That was the thing. Because you said it was anonymous,

700
00:33:57,160 --> 00:34:00,360
Speaker 2: like a dummy thing, right, and I assume you it

701
00:34:00,480 --> 00:34:02,000
Speaker 2: with a different card with it, Like.

702
00:34:02,000 --> 00:34:04,760
Speaker 3: I think I bought it from like a retail physical story, right,

703
00:34:04,840 --> 00:34:05,400
Speaker 3: so there's no.

704
00:34:05,600 --> 00:34:08,800
Speaker 2: Trace because I like that thing. But now I'm like regretting.

705
00:34:09,000 --> 00:34:09,800
Speaker 1: That's a good device.

706
00:34:09,920 --> 00:34:11,680
Speaker 2: But it's like, hopefully it doesn't break.

707
00:34:11,920 --> 00:34:13,759
Speaker 4: Yeah, it's a great device as long as it never

708
00:34:13,800 --> 00:34:25,600
Speaker 4: has a problem.

709
00:34:25,719 --> 00:34:28,920
Speaker 2: So okay, let's change. Let's change tag to the industry

710
00:34:28,960 --> 00:34:30,399
Speaker 2: at large. And I want to talk to you about

711
00:34:30,440 --> 00:34:33,719
Speaker 2: electronic arts because I know you just did a video.

712
00:34:34,560 --> 00:34:37,800
Speaker 2: My whole thing was, how does he get worse? Because

713
00:34:37,800 --> 00:34:40,239
Speaker 2: there's a company they've been dog shit for a while.

714
00:34:40,239 --> 00:34:41,560
Speaker 2: And that's a personal opinion.

715
00:34:42,400 --> 00:34:43,360
Speaker 1: I think that's an objective.

716
00:34:43,520 --> 00:34:45,600
Speaker 2: Yeah, I mean, look at the Maden franchise.

717
00:34:46,120 --> 00:34:51,120
Speaker 1: I think I don't know. EA is like bizarre to me.

718
00:34:51,560 --> 00:34:52,680
Speaker 1: I don't get it.

719
00:34:53,200 --> 00:34:56,320
Speaker 3: I know you can look at their financial reports and whatever,

720
00:34:56,400 --> 00:35:02,359
Speaker 3: but the powers at play and the EA acquisition, it's

721
00:35:02,920 --> 00:35:08,000
Speaker 3: multiple governments through one connection or another. And I think

722
00:35:08,040 --> 00:35:10,160
Speaker 3: for a lot of people, regardless of what they think

723
00:35:10,360 --> 00:35:14,319
Speaker 3: about social issues, it is just, if you really think

724
00:35:14,360 --> 00:35:19,560
Speaker 3: about it, weird for government or government connected entities to

725
00:35:19,719 --> 00:35:24,960
Speaker 3: start acquiring video game companies and I personally, like, I'm

726
00:35:25,080 --> 00:35:28,040
Speaker 3: very skeptical of it because the US government in particular

727
00:35:28,680 --> 00:35:33,280
Speaker 3: has dragged video games at every opportunity they get for decades.

728
00:35:33,800 --> 00:35:36,960
Speaker 3: It's always like the video games cause violence, you know,

729
00:35:37,080 --> 00:35:39,720
Speaker 3: and it's from people who've probably never played an actual

730
00:35:39,800 --> 00:35:41,640
Speaker 3: game in their lives.

731
00:35:41,400 --> 00:35:43,319
Speaker 2: And from one instead of this deal, it's mostly it's

732
00:35:43,360 --> 00:35:45,040
Speaker 2: like Saudi money and PE money.

733
00:35:45,360 --> 00:35:48,640
Speaker 3: Yes, So it's yes, So there's private equity. As he said,

734
00:35:48,680 --> 00:35:51,080
Speaker 3: there's Saudi money through the PAF and then on the

735
00:35:51,200 --> 00:35:56,520
Speaker 3: US side Affinity Partners, which is helmed by Jared Kushner

736
00:35:57,160 --> 00:35:59,440
Speaker 3: right to former senior advisor to the President, and I

737
00:35:59,440 --> 00:36:03,480
Speaker 3: think who he just sent over to some kind of

738
00:36:03,480 --> 00:36:06,840
Speaker 3: peace discussion or something, so he's still involved somehow. But anyway,

739
00:36:06,880 --> 00:36:10,560
Speaker 3: so that's the US side where you've got PE money.

740
00:36:10,640 --> 00:36:13,799
Speaker 3: You have somehow indirectly the US government but through a

741
00:36:13,840 --> 00:36:18,000
Speaker 3: former US government official and then his firm, the Affinity Partners,

742
00:36:19,000 --> 00:36:23,680
Speaker 3: has received somewhere around two billion dollars of initial investment

743
00:36:23,760 --> 00:36:27,200
Speaker 3: from the Saudi pif that was a New York Times

744
00:36:27,239 --> 00:36:28,040
Speaker 3: report previous.

745
00:36:27,840 --> 00:36:31,720
Speaker 2: So is funded by the other people invested.

746
00:36:32,080 --> 00:36:35,360
Speaker 3: Yeah, And I think if I remember the numbers correct,

747
00:36:35,440 --> 00:36:37,719
Speaker 3: it was close to ninety million dollars out of there,

748
00:36:37,719 --> 00:36:40,080
Speaker 3: one hundred and sixty or so million in management fees

749
00:36:40,400 --> 00:36:45,359
Speaker 3: for the last filing was from managing Saudi money. And

750
00:36:45,400 --> 00:36:49,080
Speaker 3: then you've got the PIF from Saudi Arabia working with

751
00:36:49,160 --> 00:36:52,520
Speaker 3: this firm to buy EA Games. One of the things

752
00:36:52,520 --> 00:36:55,000
Speaker 3: we didn't talk about in the video that I just

753
00:36:55,480 --> 00:36:57,080
Speaker 3: I hadn't really thought too much about it, and I

754
00:36:57,120 --> 00:37:00,960
Speaker 3: saw some excellent comments that made me think more about it,

755
00:37:00,960 --> 00:37:07,439
Speaker 3: But is that companies like EA Games control a huge

756
00:37:07,480 --> 00:37:10,320
Speaker 3: amount of data that seems inconsequential on the surface.

757
00:37:10,800 --> 00:37:13,760
Speaker 1: It's video game data, Like, right, what is okay?

758
00:37:13,800 --> 00:37:16,640
Speaker 3: So what Let's just pretend there's a clean path for

759
00:37:16,920 --> 00:37:19,480
Speaker 3: the data to exit EA Games and go to the

760
00:37:19,600 --> 00:37:21,960
Speaker 3: US government or go to the Chinese or the Saudi

761
00:37:22,040 --> 00:37:24,919
Speaker 3: rating whatever. Right, Let's just pretend there's a path there.

762
00:37:26,040 --> 00:37:28,280
Speaker 3: They can't really do anything useful with your save game file.

763
00:37:29,360 --> 00:37:33,120
Speaker 3: But one of the things that does interest me, and

764
00:37:33,600 --> 00:37:37,080
Speaker 3: I just want to maybe caution here that this isn't.

765
00:37:38,520 --> 00:37:40,799
Speaker 1: I don't think there's anything going on here right now, but.

766
00:37:41,280 --> 00:37:47,920
Speaker 3: I think there is the opportunity to abuse anti cheat systems,

767
00:37:48,440 --> 00:37:52,440
Speaker 3: which are like kernel level software in most cases that

768
00:37:52,520 --> 00:37:57,000
Speaker 3: run on the computer. So if you wanted to deploy

769
00:37:57,080 --> 00:37:59,919
Speaker 3: like some kind of root kit with very low level

770
00:38:00,080 --> 00:38:03,960
Speaker 3: access to computers, you could do it through anti cheat solutions.

771
00:38:04,320 --> 00:38:05,399
Speaker 1: Now, I don't think this is.

772
00:38:05,360 --> 00:38:07,960
Speaker 3: Happening right, right, and so I want to make sure

773
00:38:08,000 --> 00:38:09,520
Speaker 3: people know that because you don't want it sound like

774
00:38:09,520 --> 00:38:11,520
Speaker 3: it's some crazy, wild conspiracy theory.

775
00:38:11,760 --> 00:38:13,800
Speaker 1: I'm just saying it's possible for it to happen.

776
00:38:13,880 --> 00:38:15,640
Speaker 2: But I mean there's probably a trophy of dated with

777
00:38:15,680 --> 00:38:18,600
Speaker 2: the EA play or whatever horrible cloud service.

778
00:38:18,320 --> 00:38:18,680
Speaker 3: For sure.

779
00:38:19,640 --> 00:38:22,879
Speaker 1: Maybe they have chat logs that could be useful to elements. Right.

780
00:38:23,440 --> 00:38:26,959
Speaker 3: The US government has talked about wanting to bring Gabe

781
00:38:27,000 --> 00:38:31,600
Speaker 3: Newell in for a testimony of some kind to talk

782
00:38:31,600 --> 00:38:35,680
Speaker 3: about radicalization of teens who play video games.

783
00:38:35,560 --> 00:38:37,560
Speaker 2: Right, and they're doing that with the Discord CEO. I

784
00:38:37,600 --> 00:38:39,080
Speaker 2: think or they are already did that.

785
00:38:39,280 --> 00:38:41,080
Speaker 3: Yeah, And I mean, if you want to go way back, right,

786
00:38:41,480 --> 00:38:44,560
Speaker 3: this has been the circus has been had before.

787
00:38:44,719 --> 00:38:46,719
Speaker 1: It was just last time was with rock music.

788
00:38:47,160 --> 00:38:51,279
Speaker 2: Right, So god, I just as just said, it's like,

789
00:38:51,360 --> 00:38:54,520
Speaker 2: I don't know how EA gets worse though, because you

790
00:38:54,560 --> 00:38:56,040
Speaker 2: were sports I don't know if you're a sports fan

791
00:38:56,160 --> 00:38:56,560
Speaker 2: or anything.

792
00:38:56,600 --> 00:38:57,560
Speaker 1: I'm aware of sports.

793
00:38:57,760 --> 00:39:00,480
Speaker 2: Yeah, I said, this is the one of the pigs

794
00:39:00,520 --> 00:39:03,759
Speaker 2: that buys Madden every year. It has got worse while

795
00:39:03,760 --> 00:39:06,200
Speaker 2: also staying the same. And I don't know, I mean,

796
00:39:06,280 --> 00:39:07,799
Speaker 2: the only way for them to make it worse is

797
00:39:07,800 --> 00:39:10,839
Speaker 2: to just have it steal your money at this point,

798
00:39:10,960 --> 00:39:13,560
Speaker 2: just actually go through your Walter. I just don't have

799
00:39:13,719 --> 00:39:16,920
Speaker 2: they spoken of their plans for the company other than using.

800
00:39:16,760 --> 00:39:22,920
Speaker 3: AI Yeah, great, this is why you should film to expression.

801
00:39:23,280 --> 00:39:26,759
Speaker 1: Yeah, just the the revulsions like you melt it. Yeah.

802
00:39:28,040 --> 00:39:30,319
Speaker 2: And that most of the debt, it looks like he's

803
00:39:30,360 --> 00:39:32,120
Speaker 2: going to it's sort of most of the revenue is

804
00:39:32,160 --> 00:39:33,160
Speaker 2: going into the debt as well.

805
00:39:33,239 --> 00:39:34,960
Speaker 3: Yeah, I think it's I think it was like a

806
00:39:35,000 --> 00:39:38,560
Speaker 3: twenty billion dollar debt or something that they have to

807
00:39:38,560 --> 00:39:40,520
Speaker 3: pay down relatively fast. I don't remember how much pre

808
00:39:40,600 --> 00:39:42,640
Speaker 3: you're off the top of my head, but it's it's

809
00:39:42,760 --> 00:39:47,520
Speaker 3: enough where not sure exactly what the game plan is.

810
00:39:47,520 --> 00:39:50,600
Speaker 3: But the current CEO, who's remaining in the CEO at

811
00:39:50,680 --> 00:39:52,760
Speaker 3: least right now, I think his name is Andrew Wilson,

812
00:39:52,800 --> 00:39:56,920
Speaker 3: I want to say, has stated that they have plans

813
00:39:56,920 --> 00:40:01,640
Speaker 3: for use of AI EEA, and I think the as

814
00:40:01,680 --> 00:40:07,279
Speaker 3: a whole have stated use plans for agents AI agents.

815
00:40:06,200 --> 00:40:10,399
Speaker 2: The very real thing that exists, great stuff fucking EA.

816
00:40:11,360 --> 00:40:12,959
Speaker 2: So that's how they do it. They become a AI

817
00:40:13,200 --> 00:40:17,319
Speaker 2: and it sucks even harder. But let's change topics to

818
00:40:17,360 --> 00:40:22,200
Speaker 2: another weird acquisition investment. Intel, how do you feel about

819
00:40:22,200 --> 00:40:23,960
Speaker 2: this in Nvidia Intel situation?

820
00:40:24,800 --> 00:40:28,520
Speaker 3: I think the Nvidia Intel US government situation, Yes, it's

821
00:40:28,600 --> 00:40:32,680
Speaker 3: really weird. I am not I mean I don't like it.

822
00:40:34,000 --> 00:40:38,040
Speaker 3: I think I understand the US government's interest. I'm sure

823
00:40:38,480 --> 00:40:42,560
Speaker 3: they look at it as absolutely a national security asset.

824
00:40:43,080 --> 00:40:46,280
Speaker 3: It's our only way we can even dream of making

825
00:40:47,200 --> 00:40:51,640
Speaker 3: relevant competitive chips in America. And so if for some

826
00:40:51,760 --> 00:40:55,600
Speaker 3: reason you needed a local resource to do that, Intel

827
00:40:55,719 --> 00:41:00,200
Speaker 3: is it. So I get it, But at the same time,

828
00:41:01,600 --> 00:41:03,799
Speaker 3: the way it came about is kind of bizarre to me.

829
00:41:03,880 --> 00:41:12,520
Speaker 3: Where the timeline of events was. Trump says Intel CEO

830
00:41:12,640 --> 00:41:18,040
Speaker 3: lip Putin is quote highly conflicted, and that the only

831
00:41:18,120 --> 00:41:20,719
Speaker 3: resolution to this problem of being highly conflicted would be

832
00:41:20,719 --> 00:41:24,560
Speaker 3: for him to resign. The reasoning it seemed for that

833
00:41:25,600 --> 00:41:29,719
Speaker 3: belief of being highly conflicted is pasted or current investments

834
00:41:29,800 --> 00:41:34,120
Speaker 3: by Intel's current CEO in Chinese companies, including some which

835
00:41:34,120 --> 00:41:36,960
Speaker 3: I have Chinese military ties. So that's my understanding of

836
00:41:37,000 --> 00:41:41,520
Speaker 3: that event. Immediately following that, within days, well within one day,

837
00:41:41,520 --> 00:41:45,080
Speaker 3: Intel respond publicly. Intel CEO within days gets on a plane,

838
00:41:45,160 --> 00:41:48,799
Speaker 3: meets Trump. Now they're friends. Trump says it, calls him

839
00:41:48,800 --> 00:41:54,799
Speaker 3: a success. And then shortly after this, you know, you're

840
00:41:55,160 --> 00:41:57,560
Speaker 3: on this this roller coaster, Intel stock the whole time

841
00:41:57,600 --> 00:42:00,160
Speaker 3: plunges when he says he needs to resign.

842
00:42:00,280 --> 00:42:01,480
Speaker 1: It's skyrockets, you know.

843
00:42:02,120 --> 00:42:04,880
Speaker 3: And then shortly after all that, the US government is

844
00:42:05,880 --> 00:42:10,239
Speaker 3: effectively acquiring ten percent of Intel, right and yeah, I mean,

845
00:42:10,320 --> 00:42:13,879
Speaker 3: and on then video side, after a couple of weeks

846
00:42:13,880 --> 00:42:18,160
Speaker 3: after this, Stop and Video is acquiring five billion dollars

847
00:42:18,200 --> 00:42:20,040
Speaker 3: worth of Intel, which I think is around four percent

848
00:42:20,120 --> 00:42:21,400
Speaker 3: or something according to Reuters.

849
00:42:22,680 --> 00:42:25,520
Speaker 1: So I just I don't really know.

850
00:42:26,000 --> 00:42:29,680
Speaker 3: I guess my answer is, ed, I don't know what's

851
00:42:29,719 --> 00:42:30,719
Speaker 3: happening anymore.

852
00:42:31,160 --> 00:42:33,160
Speaker 2: And that's kind of where I've come down in this whoop,

853
00:42:33,160 --> 00:42:35,560
Speaker 2: because it's not clear what happens next. They're going to

854
00:42:35,600 --> 00:42:37,839
Speaker 2: do something together. Do you think they're going to keep

855
00:42:37,880 --> 00:42:40,080
Speaker 2: making the elk GPUs or is that because they haven't

856
00:42:40,080 --> 00:42:41,359
Speaker 2: said they're going to stop making them.

857
00:42:41,400 --> 00:42:45,680
Speaker 1: I think they're at risk. I that was a that

858
00:42:45,760 --> 00:42:47,239
Speaker 1: was an unintentional pun.

859
00:42:47,400 --> 00:42:50,880
Speaker 3: Very few people will get no, I loved it nice. Yeah,

860
00:42:51,000 --> 00:42:54,560
Speaker 3: I think there is some risk there. So, like the

861
00:42:54,600 --> 00:42:56,560
Speaker 3: stated plan is that they're going to work together on

862
00:42:56,680 --> 00:42:59,759
Speaker 3: X eighty six, which is an ISA and instruction you know,

863
00:43:00,120 --> 00:43:05,120
Speaker 3: architecture that is used in CPUs, and they want to

864
00:43:05,120 --> 00:43:07,200
Speaker 3: work together on x eighty six solutions, which there's not

865
00:43:07,239 --> 00:43:09,920
Speaker 3: a ton OF's. There's a lot of ARM there's Intel,

866
00:43:09,920 --> 00:43:11,879
Speaker 3: and there's AMD for x eighty six for the most part,

867
00:43:11,960 --> 00:43:16,040
Speaker 3: some via but and they also are planning to work

868
00:43:16,080 --> 00:43:22,120
Speaker 3: together on envy Link integration, which was Nvidia's actually effective

869
00:43:22,160 --> 00:43:23,319
Speaker 3: solution was that.

870
00:43:23,239 --> 00:43:25,200
Speaker 2: They go through Mellano's acquisition.

871
00:43:25,440 --> 00:43:29,239
Speaker 3: Mellanox is their networking infrastructure, right and envy Link is

872
00:43:29,320 --> 00:43:32,640
Speaker 3: there sort of on board, although now it's expanded, but

873
00:43:33,560 --> 00:43:37,959
Speaker 3: basically PCIe alternatives. Oh okay, so so PCI Express wasn't

874
00:43:37,960 --> 00:43:40,799
Speaker 3: doing it, friend VideA. This is actually one of the

875
00:43:40,840 --> 00:43:43,879
Speaker 3: areas where it's not just all marketing bullshit, Like envy

876
00:43:43,880 --> 00:43:46,399
Speaker 3: Link serves a real purpose. It does a real thing

877
00:43:46,560 --> 00:43:49,360
Speaker 3: and and they need it. And so they're going to

878
00:43:49,400 --> 00:43:55,680
Speaker 3: work with Intel to integrate this protocol into other products

879
00:43:56,000 --> 00:44:02,600
Speaker 3: which will make end videos. GPUs more lolliable on CPUs

880
00:44:02,840 --> 00:44:04,160
Speaker 3: like x eighty six CPUs.

881
00:44:04,400 --> 00:44:06,239
Speaker 2: Right, do you think there could be a good thing

882
00:44:06,280 --> 00:44:08,560
Speaker 2: about this? Could that actually be a positive?

883
00:44:08,680 --> 00:44:12,319
Speaker 3: It'll definitely be better for Nvidia's solutions. I mean, if

884
00:44:12,320 --> 00:44:14,040
Speaker 3: you want to look at it purely in a vacuum

885
00:44:14,040 --> 00:44:18,560
Speaker 3: of ignore literally all business and all competition aspects and

886
00:44:18,560 --> 00:44:21,960
Speaker 3: look at only the product level, their product should be

887
00:44:21,960 --> 00:44:27,040
Speaker 3: better as a result of it. In theory, I think

888
00:44:27,040 --> 00:44:31,560
Speaker 3: there's risk to both and the end to Intel here.

889
00:44:32,160 --> 00:44:34,000
Speaker 3: So in particular, something that's interesting that a lot of

890
00:44:34,040 --> 00:44:37,800
Speaker 3: people don't know is the mobile the laptop side of

891
00:44:37,840 --> 00:44:42,319
Speaker 3: the business where this is another stated goal of NVIDI

892
00:44:42,400 --> 00:44:44,920
Speaker 3: and Intel is they want to make laptop hardware, so

893
00:44:44,960 --> 00:44:47,480
Speaker 3: they want to make silicon with RTX chiplets, which is

894
00:44:47,640 --> 00:44:51,080
Speaker 3: a tiny piece of silicon for the the sc or

895
00:44:51,080 --> 00:44:54,440
Speaker 3: the CPU. And on the laptop side of the business,

896
00:44:54,560 --> 00:44:58,480
Speaker 3: the entire industry aligns to end Video's schedule. So if

897
00:44:58,600 --> 00:45:01,880
Speaker 3: Nvidia and Intel previous we're both launching a CPU and

898
00:45:01,880 --> 00:45:03,920
Speaker 3: this just happened at about the same time they launched

899
00:45:03,920 --> 00:45:05,440
Speaker 3: a cp in a GPU between the two of them,

900
00:45:06,160 --> 00:45:10,000
Speaker 3: the vendors will align to Nvidia's GPU, meaning all of

901
00:45:10,080 --> 00:45:14,520
Speaker 3: the marketing effort, the money, the sampling, the review guidance

902
00:45:14,600 --> 00:45:16,240
Speaker 3: where you know they will get in touch.

903
00:45:16,040 --> 00:45:19,319
Speaker 1: With reviewers and educate them on the new architecture.

904
00:45:20,040 --> 00:45:25,400
Speaker 3: All of that basically happens around Nvidia's timing because Nvidia

905
00:45:25,560 --> 00:45:31,960
Speaker 3: sells units, right and so because of that, if Nvidia

906
00:45:32,120 --> 00:45:35,040
Speaker 3: is suddenly, you know, if they launch a new GPU

907
00:45:35,120 --> 00:45:38,479
Speaker 3: for mobile right now, Intel and A, it doesn't matter

908
00:45:38,480 --> 00:45:41,320
Speaker 3: which CPU is in it, MSI or Asus or hpuor

909
00:45:41,320 --> 00:45:43,919
Speaker 3: the Nobo or Dell. They' launch their notebook with whatever

910
00:45:43,960 --> 00:45:46,840
Speaker 3: CPU doesn't matter. The Nvidio GPUs the part that matters

911
00:45:46,840 --> 00:45:52,200
Speaker 3: to them. If Nvidia is working with Intel, then suddenly

912
00:45:52,880 --> 00:45:57,120
Speaker 3: it would seem that there's motive for them to leverage

913
00:45:57,200 --> 00:46:04,839
Speaker 3: allocation of GPU Silicon with the intent being to get

914
00:46:04,880 --> 00:46:07,879
Speaker 3: more Intel Nvidia co branded.

915
00:46:07,560 --> 00:46:10,839
Speaker 1: CPUs deployed in notebooks. You see where I'm going with this.

916
00:46:10,840 --> 00:46:13,520
Speaker 2: Yeah, because this is kind of a long tail thing.

917
00:46:13,560 --> 00:46:16,680
Speaker 2: But it's like the old ms DOS situation, Yeah, where

918
00:46:16,719 --> 00:46:20,040
Speaker 2: OEMs just ultimately went with dot because could Nvidia push

919
00:46:20,080 --> 00:46:20,680
Speaker 2: down prices?

920
00:46:20,719 --> 00:46:24,080
Speaker 1: I su moor, Well, I mean they they historically have

921
00:46:24,160 --> 00:46:26,920
Speaker 1: been I don't know.

922
00:46:26,960 --> 00:46:31,440
Speaker 3: I guess you'd say maybe revolted against an EVJ situation.

923
00:46:31,600 --> 00:46:33,359
Speaker 3: But we've covered plenty of vendors in the past. I'll

924
00:46:33,360 --> 00:46:34,680
Speaker 3: just name them now because it's been long enough. But

925
00:46:34,719 --> 00:46:38,399
Speaker 3: like a sus, MSI, Gigabyte, and EVJ have all told

926
00:46:38,440 --> 00:46:43,040
Speaker 3: us about times where allocation, which is the it's the

927
00:46:43,080 --> 00:46:46,040
Speaker 3: pot of gold, right, it's it's how many chips they get,

928
00:46:47,000 --> 00:46:51,640
Speaker 3: is withheld or is modulated based on their willingness to

929
00:46:51,719 --> 00:46:56,040
Speaker 3: comply with whatever the current sort of requirements are.

930
00:46:56,000 --> 00:46:57,400
Speaker 2: And what would those requirements be.

931
00:46:58,080 --> 00:47:02,239
Speaker 3: In the past, it's been stuff like well, I mean,

932
00:47:02,239 --> 00:47:08,080
Speaker 3: on an EVGA side of things, they had always told

933
00:47:08,160 --> 00:47:12,760
Speaker 3: us about being restricted in their ability to design certain

934
00:47:12,840 --> 00:47:17,440
Speaker 3: high end boards that might have like overclocking solutions, engineering solutions,

935
00:47:18,600 --> 00:47:20,160
Speaker 3: and so there was there was kind of like a

936
00:47:20,200 --> 00:47:21,000
Speaker 3: trade behind.

937
00:47:20,760 --> 00:47:23,360
Speaker 2: The those restrictions happened. They do they need something of

938
00:47:23,400 --> 00:47:24,520
Speaker 2: an nvidious.

939
00:47:24,120 --> 00:47:27,120
Speaker 3: Side or well sometimes yeah, but it can be like

940
00:47:28,400 --> 00:47:31,120
Speaker 3: we need you to not do that, or we need

941
00:47:31,160 --> 00:47:34,120
Speaker 3: you to sell a certain amount of this priced class

942
00:47:34,160 --> 00:47:36,239
Speaker 3: of card. So as an example, there was a time

943
00:47:36,280 --> 00:47:42,200
Speaker 3: where we'd reported when multiple sources at EVGA informed us

944
00:47:42,280 --> 00:47:48,640
Speaker 3: that the MSRP cards were not actually real, like they

945
00:47:48,800 --> 00:47:51,160
Speaker 3: were going to exist for a short period for launch

946
00:47:51,680 --> 00:47:55,000
Speaker 3: to comply with Nvideo's requirement, and as soon as it

947
00:47:55,040 --> 00:47:57,240
Speaker 3: was no longer a hard requirement to get the allocation,

948
00:47:57,320 --> 00:47:59,879
Speaker 3: they were going to kill the product because they didn't

949
00:47:59,880 --> 00:48:01,000
Speaker 3: have margin.

950
00:48:01,360 --> 00:48:03,520
Speaker 2: And so they effectively had to release something that made

951
00:48:03,520 --> 00:48:04,120
Speaker 2: the money.

952
00:48:04,360 --> 00:48:05,040
Speaker 1: Yeah, basically.

953
00:48:05,160 --> 00:48:06,680
Speaker 3: Yeah, there was one I think we reported on where

954
00:48:06,680 --> 00:48:09,520
Speaker 3: they were making like four box or something, and that's

955
00:48:09,520 --> 00:48:12,200
Speaker 3: on a that was I think that was like a

956
00:48:12,360 --> 00:48:14,560
Speaker 3: three hundred dollars something Boar Christ Yeah.

957
00:48:14,719 --> 00:48:17,800
Speaker 2: Yeah, so this is fairly typical for nvidio.

958
00:48:17,880 --> 00:48:22,399
Speaker 3: This kind of allocation is is their leverage. Yeah, it's

959
00:48:22,440 --> 00:48:25,640
Speaker 3: also how they create internal competition between the board partners.

960
00:48:25,960 --> 00:48:28,960
Speaker 3: Now AMD does this too, and so does Intel. I

961
00:48:29,000 --> 00:48:32,600
Speaker 3: think with Intel the differences they don't really have anything that.

962
00:48:32,960 --> 00:48:34,839
Speaker 2: A ton of leverage at the moment, not really.

963
00:48:34,920 --> 00:48:38,680
Speaker 3: Yeah, and AMD, you know, they they also play games

964
00:48:38,680 --> 00:48:40,960
Speaker 3: with allocation. I think the difference is nvideo is just

965
00:48:42,320 --> 00:48:45,200
Speaker 3: the difference is if you make nvideo products and you

966
00:48:45,239 --> 00:48:49,360
Speaker 3: make am D products like GPUs, you can lose the

967
00:48:49,440 --> 00:48:52,160
Speaker 3: AMD ones or ten percent of the supply or whatever

968
00:48:52,520 --> 00:48:54,799
Speaker 3: and still be in business. But if you lose the

969
00:48:54,840 --> 00:48:57,719
Speaker 3: nvideo ones, you're fucked, right Like business is over.

970
00:48:58,160 --> 00:49:01,080
Speaker 2: So they could use this with CPUs. There could be

971
00:49:01,120 --> 00:49:02,160
Speaker 2: a scenario.

972
00:49:01,800 --> 00:49:02,800
Speaker 1: That is my concern.

973
00:49:03,040 --> 00:49:08,880
Speaker 3: Yeah, my concern is if they're in mobile with CPU

974
00:49:08,960 --> 00:49:13,040
Speaker 3: and GPU. Now it's not just they're aligning to Nvidya's GPUs.

975
00:49:13,760 --> 00:49:17,640
Speaker 3: There's again a there's no evidence they're planning to do this,

976
00:49:18,440 --> 00:49:21,400
Speaker 3: but I think I've seen enough historical context to be

977
00:49:21,440 --> 00:49:24,960
Speaker 3: concerned about a possibility where they say, Hey, we'd really

978
00:49:25,040 --> 00:49:27,200
Speaker 3: love it if you would put more of the Intel

979
00:49:27,360 --> 00:49:30,919
Speaker 3: RTX CPUs in your notebooks so that you can get

980
00:49:31,040 --> 00:49:32,360
Speaker 3: enough fifty ninety GPUs.

981
00:49:32,640 --> 00:49:35,200
Speaker 2: Oh so they will, They'll use one, So okay, now

982
00:49:35,239 --> 00:49:37,400
Speaker 2: I understand. So it's the leverage with other cards that

983
00:49:37,400 --> 00:49:40,719
Speaker 2: they'll use the force of this. Yes, potentially potentially. I

984
00:49:40,760 --> 00:49:44,239
Speaker 2: know that this is and this they've done this for years, like.

985
00:49:44,360 --> 00:49:46,719
Speaker 1: Yeah, yeah, allocation is a is a big lever.

986
00:49:47,040 --> 00:49:49,320
Speaker 2: Do you think they do similar things with the AI GPUs.

987
00:49:50,239 --> 00:49:51,879
Speaker 1: Uh, I don't know.

988
00:49:52,040 --> 00:49:56,320
Speaker 3: I don't really talk to because that would be probably

989
00:49:56,360 --> 00:50:00,719
Speaker 3: more like Dell HP like those big enterprise deployers. I

990
00:50:00,719 --> 00:50:03,880
Speaker 3: don't really talk to people there. I mean to me,

991
00:50:04,000 --> 00:50:05,960
Speaker 3: it just seems like this is kind of a company

992
00:50:05,960 --> 00:50:07,920
Speaker 3: culture thing, and this is all this is all me

993
00:50:08,000 --> 00:50:11,480
Speaker 3: speaking from what we've reported on. You know, we have

994
00:50:11,560 --> 00:50:13,759
Speaker 3: some facts for some of the stuff where we've we've

995
00:50:13,800 --> 00:50:17,800
Speaker 3: covered it, like with the EVJ situation, but yeah, enterprise,

996
00:50:17,840 --> 00:50:20,160
Speaker 3: I'm not sure how exactly that side works.

997
00:50:21,280 --> 00:50:25,040
Speaker 2: So when it comes to AIGPUS, is there is it

998
00:50:25,120 --> 00:50:28,160
Speaker 2: a limitation of your testing as the way you don't

999
00:50:28,400 --> 00:50:30,319
Speaker 2: look into them because it felt like it's the one

1000
00:50:30,360 --> 00:50:32,319
Speaker 2: thing I'm like surprised that you haven't dug into more

1001
00:50:32,320 --> 00:50:34,560
Speaker 2: with like a one hundreds h one hundreds, Like.

1002
00:50:34,680 --> 00:50:37,239
Speaker 3: Yeah, So there's sort of there's like two sides to it.

1003
00:50:37,280 --> 00:50:40,920
Speaker 3: There's testing and then there's just reporting on whatever the

1004
00:50:40,960 --> 00:50:45,239
Speaker 3: news is. And so the reporting part we did that

1005
00:50:45,640 --> 00:50:51,360
Speaker 3: with the black market video. The testing side, I guess

1006
00:50:52,360 --> 00:50:54,080
Speaker 3: there's there's like a couple of things that are nested

1007
00:50:54,120 --> 00:50:56,120
Speaker 3: with in testing. So we've done a little bit of

1008
00:50:56,200 --> 00:50:59,880
Speaker 3: quote unquote AI testing and that was on the RTX

1009
00:51:00,080 --> 00:51:04,160
Speaker 3: or six thousand Blackwell GPU. This is something that is

1010
00:51:04,200 --> 00:51:06,520
Speaker 3: still new. It's not one hundred percent clear to me

1011
00:51:06,600 --> 00:51:10,799
Speaker 3: what is a reproducible reliable test, right It's part of

1012
00:51:10,800 --> 00:51:14,760
Speaker 3: the problem is if you're testing LLLMS or generative AI

1013
00:51:14,960 --> 00:51:19,680
Speaker 3: or whatever, something that makes images by nature of the application,

1014
00:51:20,160 --> 00:51:23,919
Speaker 3: it's almost semi it's different every time.

1015
00:51:24,040 --> 00:51:27,280
Speaker 2: We would also need a massive cluster to really emulate

1016
00:51:27,320 --> 00:51:29,080
Speaker 2: what it is because one A one hundred or eight

1017
00:51:29,080 --> 00:51:30,440
Speaker 2: one hundred isn't really gonna happen.

1018
00:51:30,520 --> 00:51:33,480
Speaker 3: Yeah, and that's kind of like you can run those tests.

1019
00:51:34,520 --> 00:51:39,240
Speaker 3: But and this would be a valid request from the audience.

1020
00:51:39,280 --> 00:51:41,919
Speaker 3: I think an audience that really cares about it would

1021
00:51:41,960 --> 00:51:43,840
Speaker 3: be like okay, cool, So like what about if you

1022
00:51:43,920 --> 00:51:46,560
Speaker 3: have you know, ten of them or whatever.

1023
00:51:46,280 --> 00:51:48,200
Speaker 2: And even then, how do you even practically?

1024
00:51:48,560 --> 00:51:48,759
Speaker 4: Yeah?

1025
00:51:48,800 --> 00:51:51,239
Speaker 3: And I just I think we can do it, and

1026
00:51:51,239 --> 00:51:55,520
Speaker 3: I do think we'll probably integrate some kind of long

1027
00:51:55,600 --> 00:52:00,840
Speaker 3: term testing for single GPU boards or dual GP single boards.

1028
00:52:02,760 --> 00:52:05,959
Speaker 3: But it's right now, it's so new that to test

1029
00:52:06,000 --> 00:52:13,160
Speaker 3: it properly requires a lot of research and a lot

1030
00:52:13,200 --> 00:52:14,480
Speaker 3: of sort of trial and error.

1031
00:52:14,600 --> 00:52:17,799
Speaker 2: Well, so how would you even because with something like

1032
00:52:17,920 --> 00:52:20,440
Speaker 2: GB two hundreds or GB three hundred, they've got their

1033
00:52:20,440 --> 00:52:23,200
Speaker 2: own distinct cooling. You're not going to get a giant

1034
00:52:23,280 --> 00:52:24,759
Speaker 2: racking wherever you want.

1035
00:52:24,960 --> 00:52:27,160
Speaker 1: Yeah, there's there's definitely a limit.

1036
00:52:27,239 --> 00:52:29,480
Speaker 2: And what are you testing for? It's just I've I

1037
00:52:29,560 --> 00:52:31,640
Speaker 2: have spoke spoke to a few listeners and like, oh

1038
00:52:31,680 --> 00:52:33,520
Speaker 2: what about AIJ why's you know, and it's kind of

1039
00:52:33,800 --> 00:52:35,920
Speaker 2: on some level, what would you even be testing?

1040
00:52:36,160 --> 00:52:38,360
Speaker 3: Yeah, I think that's a big question for us, And

1041
00:52:38,560 --> 00:52:41,759
Speaker 3: I think that's where like the most immediate thing that

1042
00:52:41,800 --> 00:52:43,839
Speaker 3: would maybe make sense for us would be some kind

1043
00:52:43,880 --> 00:52:47,600
Speaker 3: of consumer level I really hate to call things AI,

1044
00:52:47,760 --> 00:52:51,960
Speaker 3: but like AI application. So maybe that's someone wants to

1045
00:52:52,040 --> 00:52:56,040
Speaker 3: just buy a fifty ninety or whatever, use it for gaming,

1046
00:52:56,160 --> 00:52:59,360
Speaker 3: and then at night they're training something on it, or

1047
00:52:59,400 --> 00:53:03,480
Speaker 3: they're running some kind of system. That's the I think

1048
00:53:03,520 --> 00:53:07,040
Speaker 3: that's the most sensible thing we could test anything where

1049
00:53:07,040 --> 00:53:11,560
Speaker 3: you're getting into like actual data center workloads. I it

1050
00:53:11,640 --> 00:53:13,719
Speaker 3: seems like the only real source for that stuff is

1051
00:53:13,840 --> 00:53:15,560
Speaker 3: basically first party at this point.

1052
00:53:15,320 --> 00:53:16,960
Speaker 2: And semi analysis to an extent.

1053
00:53:17,239 --> 00:53:19,920
Speaker 1: Yeah, you spoke with them at all. They've reached out,

1054
00:53:20,160 --> 00:53:22,320
Speaker 1: not some analysis, but I know the work.

1055
00:53:22,520 --> 00:53:25,960
Speaker 2: Yeah. I mean it's a good news Letterum just cure surprise.

1056
00:53:26,040 --> 00:53:28,879
Speaker 2: They haven't the depth they go into. But let's talk

1057
00:53:28,920 --> 00:53:31,799
Speaker 2: about AI. Actually, how do you feel about AI? Like

1058
00:53:32,040 --> 00:53:34,600
Speaker 2: you you don't do a ton about it? Yeah, which

1059
00:53:34,640 --> 00:53:36,400
Speaker 2: is fine, it's just how do you feel about it?

1060
00:53:36,440 --> 00:53:38,520
Speaker 2: And what? Why haven't you done more?

1061
00:53:39,160 --> 00:53:39,279
Speaker 5: That?

1062
00:53:39,560 --> 00:53:40,480
Speaker 2: Not as a negative.

1063
00:53:40,680 --> 00:53:45,640
Speaker 3: Yeah, most of the coverage we've done has been news based,

1064
00:53:45,760 --> 00:53:47,880
Speaker 3: so it might be reports, you know, it might be

1065
00:53:47,920 --> 00:53:50,919
Speaker 3: like an investigation or whatever, but but not a lot

1066
00:53:50,960 --> 00:53:54,720
Speaker 3: of I don't know, like testing, like we're talking about

1067
00:53:54,880 --> 00:54:00,359
Speaker 3: the biggest problems I have with it right now are

1068
00:54:01,760 --> 00:54:03,439
Speaker 3: First of all, I think if we go like really

1069
00:54:03,480 --> 00:54:06,799
Speaker 3: big picture, I don't know to qualify everything. I think

1070
00:54:06,840 --> 00:54:11,400
Speaker 3: there are use cases for things like LMS. The best

1071
00:54:11,480 --> 00:54:15,640
Speaker 3: use case I have that I've actually used is translation

1072
00:54:16,360 --> 00:54:19,880
Speaker 3: where I speak other languages, and I use Google Translate

1073
00:54:19,920 --> 00:54:22,880
Speaker 3: for most of that. Because Google Translate is a dumb translator.

1074
00:54:22,960 --> 00:54:26,480
Speaker 3: It translates the words you type into it. Sometimes that

1075
00:54:26,520 --> 00:54:30,799
Speaker 3: doesn't work for a colloquial phrase, right right, So if

1076
00:54:30,800 --> 00:54:33,319
Speaker 3: you take any idiom, it's not really going to do

1077
00:54:33,360 --> 00:54:38,080
Speaker 3: that well through Google Translate. Something like chat GPT makes

1078
00:54:38,120 --> 00:54:40,840
Speaker 3: it a little easier sometimes to search for like really

1079
00:54:40,880 --> 00:54:46,640
Speaker 3: specific colloquial or idiomatic ways to express something. So I

1080
00:54:46,640 --> 00:54:50,759
Speaker 3: would say that's like a real use case. You can

1081
00:54:50,800 --> 00:54:54,680
Speaker 3: also be deep down there, Yeah, but it is like

1082
00:54:54,760 --> 00:54:57,200
Speaker 3: the specific thing that they're kind of built around, so

1083
00:54:57,520 --> 00:54:58,279
Speaker 3: they do it well.

1084
00:55:00,160 --> 00:55:01,120
Speaker 1: I think the.

1085
00:55:02,560 --> 00:55:04,600
Speaker 3: With that qualifier out of the way, the big picture

1086
00:55:04,640 --> 00:55:11,239
Speaker 3: concerns I have with AI are weaponization of things like

1087
00:55:11,480 --> 00:55:16,680
Speaker 3: LMS to propagandas and so this could be for companies

1088
00:55:16,680 --> 00:55:19,640
Speaker 3: to market products, it could be for governments, it could

1089
00:55:19,680 --> 00:55:21,240
Speaker 3: be for unknown entities whatever.

1090
00:55:21,560 --> 00:55:23,759
Speaker 1: But having seen the bot comments on.

1091
00:55:23,800 --> 00:55:26,799
Speaker 3: Videos you know every day, is that the problem? It

1092
00:55:26,840 --> 00:55:29,040
Speaker 3: is a very consistent problem, and they're getting better.

1093
00:55:29,200 --> 00:55:30,240
Speaker 2: So what are they doing?

1094
00:55:30,520 --> 00:55:33,600
Speaker 3: So originally it started as the really obvious ones. There

1095
00:55:33,600 --> 00:55:36,319
Speaker 3: were kind of two kinds. There's the bots that do

1096
00:55:36,400 --> 00:55:39,320
Speaker 3: financial scam scams where they basically.

1097
00:55:40,640 --> 00:55:45,160
Speaker 1: Post something about like some cryptocurrency, right, some scam coin.

1098
00:55:46,560 --> 00:55:49,800
Speaker 3: The other one would be the bots that have a

1099
00:55:50,160 --> 00:55:54,319
Speaker 3: photo of someone's ass, you know, and then three emojis

1100
00:55:54,400 --> 00:55:58,520
Speaker 3: and some text about whatever. And that's the more like

1101
00:55:58,600 --> 00:56:01,239
Speaker 3: traditional trying to scam. Some went into interacting with a

1102
00:56:01,280 --> 00:56:04,800
Speaker 3: fake user that presents themselves as an attractive person.

1103
00:56:05,680 --> 00:56:07,200
Speaker 1: So those are the two common types of bots.

1104
00:56:08,040 --> 00:56:10,359
Speaker 3: Historically, those have been really easy for a savvy user

1105
00:56:10,400 --> 00:56:13,520
Speaker 3: to identify because yeah, it's like it's always the same language.

1106
00:56:13,600 --> 00:56:16,680
Speaker 3: It's like the old old you know, Nigerian prints email

1107
00:56:16,960 --> 00:56:19,000
Speaker 3: scam right right, you can read it and you're like,

1108
00:56:19,000 --> 00:56:22,040
Speaker 3: I know this is a scam. But where it's going

1109
00:56:22,120 --> 00:56:24,479
Speaker 3: now kind of concerns me because there have been times

1110
00:56:24,480 --> 00:56:27,000
Speaker 3: where I'm not sure if it's a bot or a

1111
00:56:27,040 --> 00:56:29,520
Speaker 3: real person, right, And there was one recently I just

1112
00:56:29,640 --> 00:56:33,680
Speaker 3: banned from the channel that originally I thought it was

1113
00:56:33,680 --> 00:56:37,319
Speaker 3: a user because I forget what the message was. But

1114
00:56:37,360 --> 00:56:40,480
Speaker 3: it was like, I wonder what Steve and Wendell think

1115
00:56:40,520 --> 00:56:44,520
Speaker 3: about blah blah blah, And it was clearly polling stuff

1116
00:56:44,520 --> 00:56:47,040
Speaker 3: from the title and or the transcript of the video

1117
00:56:47,719 --> 00:56:48,800
Speaker 3: and then create an account.

1118
00:56:49,080 --> 00:56:51,080
Speaker 1: And I left it alone for a minute to see

1119
00:56:51,080 --> 00:56:51,680
Speaker 1: where it would go.

1120
00:56:52,320 --> 00:56:55,040
Speaker 3: And there's like replies under the thread where it's a

1121
00:56:55,040 --> 00:56:58,200
Speaker 3: bot replying to itself through different accounts I guess, uh,

1122
00:56:58,600 --> 00:57:01,080
Speaker 3: and eventually just tries to you off site to go

1123
00:57:01,520 --> 00:57:04,360
Speaker 3: you know, get scammed. So I banned all those accounts.

1124
00:57:04,800 --> 00:57:08,879
Speaker 3: But the thing that was concerning was was that it's

1125
00:57:08,960 --> 00:57:13,640
Speaker 3: pulling context from the video transcript and forming a sentence

1126
00:57:13,680 --> 00:57:19,000
Speaker 3: that makes sense, right, and then creating the appearance of

1127
00:57:19,080 --> 00:57:22,880
Speaker 3: a real dialogue between the appearance of real users about

1128
00:57:22,880 --> 00:57:23,720
Speaker 3: this subject that.

1129
00:57:23,680 --> 00:57:26,120
Speaker 1: Made sense to then scam someone.

1130
00:57:26,960 --> 00:57:29,720
Speaker 2: I've seen these people in blue sky for sure. Yeah, sorry,

1131
00:57:29,840 --> 00:57:31,840
Speaker 2: seeing these boots in blue sky where it's just someone

1132
00:57:31,840 --> 00:57:33,800
Speaker 2: appearing to have a guy. It's like, wow, I read

1133
00:57:33,840 --> 00:57:36,080
Speaker 2: that from the thing. Well do you think about this?

1134
00:57:36,320 --> 00:57:36,520
Speaker 1: Right?

1135
00:57:36,880 --> 00:57:38,880
Speaker 2: I've never seen them get to sending me to a website,

1136
00:57:38,920 --> 00:57:41,360
Speaker 2: but I imagine that's that's a few down the change.

1137
00:57:41,400 --> 00:57:42,520
Speaker 1: The way it normally happens.

1138
00:57:42,520 --> 00:57:45,240
Speaker 3: If you go to like CNBC or any finance channel,

1139
00:57:45,280 --> 00:57:47,560
Speaker 3: and you'll see these on any new video they post.

1140
00:57:47,960 --> 00:57:50,520
Speaker 3: They all talk so like CNBC is my favorite one

1141
00:57:50,560 --> 00:57:53,640
Speaker 3: to look at for this because okay, you'll see and

1142
00:57:53,680 --> 00:57:55,520
Speaker 3: it's not their fault, they're just the target of it.

1143
00:57:55,760 --> 00:57:57,920
Speaker 3: But you'll see a bot comment that'll say something like

1144
00:57:59,240 --> 00:58:01,880
Speaker 3: I have hundreds of thousands of dollars and I don't

1145
00:58:01,880 --> 00:58:05,680
Speaker 3: know how to invest it right, right, And it's always

1146
00:58:05,680 --> 00:58:06,680
Speaker 3: some ridiculous number.

1147
00:58:07,080 --> 00:58:08,400
Speaker 1: Yeah, and then there's a reply to it.

1148
00:58:08,480 --> 00:58:12,480
Speaker 3: It's like I had excellent luck with John Smith, and

1149
00:58:12,560 --> 00:58:15,240
Speaker 3: John Smith is the comments like, yeah, they're comments.

1150
00:58:15,440 --> 00:58:18,120
Speaker 2: I've seen these in Korra. Okay, it's like, how do

1151
00:58:18,160 --> 00:58:20,440
Speaker 2: I invest one hundred and fifty thousand dollars? It's like, well,

1152
00:58:20,520 --> 00:58:23,120
Speaker 2: I did it on right oscoin or whatever.

1153
00:58:23,480 --> 00:58:24,160
Speaker 1: Yeah.

1154
00:58:24,200 --> 00:58:26,360
Speaker 3: But these they'll talk about like the name of a

1155
00:58:26,440 --> 00:58:32,360
Speaker 3: person and have this fake conversation about some financial advisor

1156
00:58:32,360 --> 00:58:35,439
Speaker 3: who doesn't exist, and then you google that name, which

1157
00:58:35,480 --> 00:58:38,080
Speaker 3: is fairly unique, right, so that's the only thing that

1158
00:58:38,080 --> 00:58:40,520
Speaker 3: comes up. And then it's a website that's a scam,

1159
00:58:41,400 --> 00:58:43,000
Speaker 3: and they you know, these.

1160
00:58:42,840 --> 00:58:45,520
Speaker 2: Point new ones compared to the original one.

1161
00:58:45,640 --> 00:58:47,840
Speaker 1: It's it's less obvious than.

1162
00:58:49,480 --> 00:58:54,320
Speaker 3: By questionable cryptocurrency or nft on website.

1163
00:58:54,640 --> 00:58:57,960
Speaker 2: Yeah. I don't know how you even deal with this.

1164
00:58:58,240 --> 00:59:00,920
Speaker 2: I don't know what the solution is other than just

1165
00:59:01,000 --> 00:59:01,880
Speaker 2: chutting them all down.

1166
00:59:02,000 --> 00:59:04,680
Speaker 1: Yeah, the channel owners have to ban them, but there's

1167
00:59:04,720 --> 00:59:05,120
Speaker 1: too many.

1168
00:59:05,200 --> 00:59:07,439
Speaker 2: You get a lot reddit to them, seeing I don't

1169
00:59:07,480 --> 00:59:10,080
Speaker 2: know if you're active on your subreddit much. I haven't checked.

1170
00:59:10,200 --> 00:59:10,720
Speaker 1: Not too much.

1171
00:59:10,880 --> 00:59:13,760
Speaker 2: Yeah, I'm in mind too much. But I do catch

1172
00:59:13,800 --> 00:59:19,560
Speaker 2: someone occasionally who is just an obvious bar sick host, disgusting. Yeah,

1173
00:59:19,600 --> 00:59:22,360
Speaker 2: but I just I ignorantly just assumed that they were

1174
00:59:22,400 --> 00:59:24,959
Speaker 2: being annoying and they were there to sow discord rather

1175
00:59:25,000 --> 00:59:26,600
Speaker 2: than send me to something to buy.

1176
00:59:26,840 --> 00:59:30,440
Speaker 1: Right. I think that's the thing too. I forget who

1177
00:59:30,440 --> 00:59:31,120
Speaker 1: the report was from.

1178
00:59:31,160 --> 00:59:34,040
Speaker 3: There was a recent report about something close actually, I

1179
00:59:34,040 --> 00:59:37,480
Speaker 3: think I saw it re reported and fact checked by

1180
00:59:37,800 --> 00:59:41,760
Speaker 3: Kurtzkazak to the channel where it was close to like

1181
00:59:41,800 --> 00:59:43,560
Speaker 3: fifty percent of Internet traffic is bought.

1182
00:59:44,120 --> 00:59:47,560
Speaker 2: Yes, yeah, and that's gonna fuck the ad industry.

1183
00:59:47,760 --> 00:59:50,520
Speaker 3: It's gonna be bad for everything because like, fuck the

1184
00:59:50,560 --> 00:59:53,200
Speaker 3: ad industry. It's gonna be bad for humanity.

1185
00:59:53,520 --> 00:59:53,760
Speaker 1: Well.

1186
00:59:53,880 --> 00:59:56,000
Speaker 2: Oh, to be clear, I don't care about the idea.

1187
00:59:56,200 --> 00:59:58,360
Speaker 2: I'm saying that that's how everything's paid for online.

1188
00:59:58,480 --> 01:00:01,480
Speaker 1: Yeah, it'll screw that all screw it's this is like

1189
01:00:02,120 --> 01:00:06,200
Speaker 1: Library of Alexandria is on fire. Yeah. Problem like this

1190
01:00:06,280 --> 01:00:07,720
Speaker 1: is this is like loss.

1191
01:00:07,600 --> 01:00:12,320
Speaker 3: Of of knowledge issues. And I think it's because, uh,

1192
01:00:12,760 --> 01:00:15,800
Speaker 3: you know, there's there's been a consolidation of sites into

1193
01:00:15,880 --> 01:00:21,360
Speaker 3: media forms of media or media for presentation like videos,

1194
01:00:21,400 --> 01:00:24,080
Speaker 3: discord things where it's not well preserved.

1195
01:00:24,720 --> 01:00:26,880
Speaker 1: And as those.

1196
01:00:26,680 --> 01:00:29,560
Speaker 3: Things collapse, because like you said, the ad industry collapses

1197
01:00:29,640 --> 01:00:32,360
Speaker 3: or whatever, there's gonna be a loss of information and knowledge.

1198
01:00:32,880 --> 01:00:38,040
Speaker 3: The death of the internet. Uh, you know, it's gonna

1199
01:00:38,080 --> 01:00:42,640
Speaker 3: happen from the the fact that you can no longer

1200
01:00:42,720 --> 01:00:45,560
Speaker 3: tell if you're the only real human in the threat

1201
01:00:45,640 --> 01:00:48,720
Speaker 3: or not for the conversation, right, and so you're gonna

1202
01:00:48,720 --> 01:00:51,680
Speaker 3: stop interacting at all because you don't know if they're.

1203
01:00:51,560 --> 01:00:52,120
Speaker 1: Bots or not.

1204
01:00:52,360 --> 01:00:53,560
Speaker 2: You think that this is gonna happen.

1205
01:00:53,880 --> 01:00:55,200
Speaker 1: I think it's happening.

1206
01:00:55,560 --> 01:01:00,000
Speaker 3: What I don't know is are the companies that can

1207
01:01:00,000 --> 01:01:03,760
Speaker 3: control the large platforms incentivized to stop it.

1208
01:01:04,760 --> 01:01:07,320
Speaker 2: I wonder because there is a level of, like any engagement,

1209
01:01:07,320 --> 01:01:09,520
Speaker 2: it's good engagement, but if people don't engage what they're

1210
01:01:09,520 --> 01:01:09,760
Speaker 2: going to.

1211
01:01:09,800 --> 01:01:12,720
Speaker 3: Do, there might be a tipping point. Maybe right now

1212
01:01:13,360 --> 01:01:15,560
Speaker 3: it's something they don't really touch. Like, you know, it

1213
01:01:15,600 --> 01:01:19,400
Speaker 3: took YouTube and awfully long time to start effectively addressing

1214
01:01:19,400 --> 01:01:21,720
Speaker 3: the bot problem, right and they still haven't really done it,

1215
01:01:22,480 --> 01:01:22,959
Speaker 3: and so.

1216
01:01:23,400 --> 01:01:25,320
Speaker 2: And that was just bot commenters or so views.

1217
01:01:25,640 --> 01:01:26,840
Speaker 1: Yeah, well there's that too.

1218
01:01:27,000 --> 01:01:29,400
Speaker 3: Yeah, there's I don't know too much about the view side,

1219
01:01:29,400 --> 01:01:34,600
Speaker 3: but the bot commentser's side. They it's hard to know.

1220
01:01:35,480 --> 01:01:38,920
Speaker 3: Are they dragging their feet on this as a counterintelligence operation?

1221
01:01:39,080 --> 01:01:43,080
Speaker 3: If the bots are intentionally really stupid, then they could

1222
01:01:43,160 --> 01:01:47,160
Speaker 3: be useful for trying to determine what are YouTube's countermeasures

1223
01:01:47,440 --> 01:01:48,440
Speaker 3: to get rid of those.

1224
01:01:48,280 --> 01:01:50,320
Speaker 2: Bots so that they can still convent them.

1225
01:01:50,480 --> 01:01:53,200
Speaker 3: Right, So you maybe if you're playing YouTube side of it,

1226
01:01:54,000 --> 01:01:57,120
Speaker 3: you know, the thought is we don't want to just

1227
01:01:57,160 --> 01:01:59,080
Speaker 3: ban these because they're going to figure out our mechanisms

1228
01:01:59,120 --> 01:02:00,400
Speaker 3: we use for more important one.

1229
01:02:00,360 --> 01:02:02,520
Speaker 2: It's exactly you know what, I actually buy that third

1230
01:02:02,520 --> 01:02:04,400
Speaker 2: because that's exactly what they did with s E. With

1231
01:02:04,560 --> 01:02:06,440
Speaker 2: sh They're just like, well, we couldn't possibly tell you

1232
01:02:06,440 --> 01:02:08,320
Speaker 2: how this works because someone would just do it.

1233
01:02:08,560 --> 01:02:10,360
Speaker 1: Yeah yeah with Google or Google.

1234
01:02:10,440 --> 01:02:14,360
Speaker 2: Yeah, they own YouTube, so it's like Jesus fucking cut.

1235
01:02:14,200 --> 01:02:15,400
Speaker 1: And the other thing too. You know.

1236
01:02:15,440 --> 01:02:17,320
Speaker 3: There's that, But there's also if you want to take

1237
01:02:17,320 --> 01:02:19,680
Speaker 3: the more cynical side, the less YouTube side, it could

1238
01:02:19,760 --> 01:02:22,600
Speaker 3: be that they want to report high engagement numbers to shareholders.

1239
01:02:22,720 --> 01:02:23,880
Speaker 1: Yes, and bots do that.

1240
01:02:23,960 --> 01:02:24,080
Speaker 4: Well.

1241
01:02:24,080 --> 01:02:26,360
Speaker 2: I mean they did that with by combining Gemini with

1242
01:02:26,400 --> 01:02:28,920
Speaker 2: Google Assistance and they had three hundred million I think

1243
01:02:29,080 --> 01:02:31,800
Speaker 2: weekly active views or something, right, Yeah.

1244
01:02:31,880 --> 01:02:34,720
Speaker 3: So but then the result is there may be a

1245
01:02:34,720 --> 01:02:40,760
Speaker 3: tipping point maybe at some point human engagement that's like

1246
01:02:40,800 --> 01:02:43,320
Speaker 3: somehow verified, which is scary for a different reason. But

1247
01:02:43,760 --> 01:02:48,760
Speaker 3: human engagement becomes almost artisanal. Like the reason you buy

1248
01:02:48,840 --> 01:02:51,640
Speaker 3: something from Etsy instead of Amazon. You know, some guy

1249
01:02:51,720 --> 01:02:54,720
Speaker 3: made it in his garage. Yeah, and so.

1250
01:02:55,080 --> 01:03:00,560
Speaker 2: Etsy full of bots. Now that's ultimate. Do you subscribe

1251
01:03:00,560 --> 01:03:02,440
Speaker 2: to the whole dead Internet theory? Do you think that?

1252
01:03:03,080 --> 01:03:07,080
Speaker 3: I think parts of it are starting to look.

1253
01:03:09,000 --> 01:03:11,400
Speaker 1: Practical, Like Facebook, I feel.

1254
01:03:11,480 --> 01:03:14,120
Speaker 2: That's my one where it's just like this is like

1255
01:03:14,240 --> 01:03:16,400
Speaker 2: old people screaming at their TV at this point.

1256
01:03:16,560 --> 01:03:20,680
Speaker 3: Yeah, and it's filled with bots that either trick them

1257
01:03:20,880 --> 01:03:23,560
Speaker 3: or that and raise them into a response.

1258
01:03:38,720 --> 01:03:40,560
Speaker 2: One of my favorite things to do is if you

1259
01:03:40,600 --> 01:03:43,320
Speaker 2: go on Facebook and you type in Facebook support into

1260
01:03:43,360 --> 01:03:46,040
Speaker 2: the chat bot ah, and you find the groups that

1261
01:03:46,160 --> 01:03:49,200
Speaker 2: are people thinking they're posting on Facebook grip and I

1262
01:03:49,280 --> 01:03:51,320
Speaker 2: know there's one of them that has like ten thousand

1263
01:03:51,360 --> 01:03:55,640
Speaker 2: people on it, and it's people like boomeras. I hate

1264
01:03:55,680 --> 01:03:58,120
Speaker 2: to sound out, but it's like people in the seventies

1265
01:03:58,120 --> 01:04:00,440
Speaker 2: being like, I don't know how to compute work, and

1266
01:04:00,560 --> 01:04:02,720
Speaker 2: three guys from Indonesia responded like, I would love to

1267
01:04:02,720 --> 01:04:06,840
Speaker 2: help you. His number from Indonesia, which is Facebook support is.

1268
01:04:06,920 --> 01:04:10,840
Speaker 3: I mean, it's kind of it is the the basically

1269
01:04:10,880 --> 01:04:13,760
Speaker 3: there's investment comments like on CNBC I was talking about

1270
01:04:13,760 --> 01:04:17,720
Speaker 3: where it looks like a real thing, you know, in

1271
01:04:17,760 --> 01:04:21,080
Speaker 3: this case, it maybe looks like actual Facebook support, right,

1272
01:04:21,440 --> 01:04:25,919
Speaker 3: And the end result is maybe maybe it's someone trying

1273
01:04:25,920 --> 01:04:28,040
Speaker 3: to help, Maybe they're enthusiasts, you really know face.

1274
01:04:27,880 --> 01:04:31,600
Speaker 2: Oh it's all Indonesian scammers. Okay, I've looked through. I

1275
01:04:31,640 --> 01:04:34,440
Speaker 2: may have spent a few hours of what like just

1276
01:04:34,600 --> 01:04:36,840
Speaker 2: I could be doing literally anything else just looking at them,

1277
01:04:36,920 --> 01:04:40,640
Speaker 2: and it's entirely guys in the Global South just defrauding people.

1278
01:04:41,480 --> 01:04:43,920
Speaker 3: Yes, and there's whole channels now that are built around

1279
01:04:44,160 --> 01:04:47,680
Speaker 3: scam busting, right, Like I forget the names of some

1280
01:04:47,760 --> 01:04:51,760
Speaker 3: of them, but there's like YouTube channels where they'll they'll

1281
01:04:51,800 --> 01:04:56,000
Speaker 3: walk through kind of the bot scam link. I think

1282
01:04:56,040 --> 01:05:00,960
Speaker 3: the AI stuff, the lms, you know, the core question

1283
01:05:01,000 --> 01:05:03,040
Speaker 3: of like what do I think of AI? All of

1284
01:05:03,080 --> 01:05:06,760
Speaker 3: those can be tools for good things. I think the

1285
01:05:06,840 --> 01:05:11,840
Speaker 3: bad things right now are very profitable. It's the dumbest

1286
01:05:11,880 --> 01:05:13,520
Speaker 3: bad thing that's profitable as a scam.

1287
01:05:13,920 --> 01:05:16,040
Speaker 2: But even then it's not profitable for the AI companies.

1288
01:05:16,040 --> 01:05:18,920
Speaker 2: It's profitable for the scammers. It's like the only people

1289
01:05:18,920 --> 01:05:21,520
Speaker 2: making money all Jensen Hwang and scammers.

1290
01:05:21,760 --> 01:05:21,960
Speaker 1: Right.

1291
01:05:22,080 --> 01:05:26,360
Speaker 3: Yeah, And maybe there's I don't know, there's probably some

1292
01:05:27,680 --> 01:05:31,040
Speaker 3: like Fortune five hundred company that thinks they're making money

1293
01:05:31,080 --> 01:05:31,360
Speaker 3: on it.

1294
01:05:31,400 --> 01:05:32,840
Speaker 1: I don't know that I've found.

1295
01:05:32,880 --> 01:05:35,200
Speaker 2: But no, OK, maybe there's one. No, this is like

1296
01:05:35,280 --> 01:05:38,680
Speaker 2: my one hyper focus of like anyone who mentions the

1297
01:05:38,760 --> 01:05:39,920
Speaker 2: revenue with AI, I know.

1298
01:05:40,200 --> 01:05:42,880
Speaker 3: Well there was one, wasn't there some report that said,

1299
01:05:43,360 --> 01:05:46,160
Speaker 3: what was it like over ninety.

1300
01:05:45,920 --> 01:05:50,120
Speaker 2: No ROI amazing report. Amazing report because you know it

1301
01:05:50,160 --> 01:05:53,040
Speaker 2: was good because immediately people said hit piece. The moment

1302
01:05:53,080 --> 01:05:55,000
Speaker 2: it says hit piece, you know that it's the true

1303
01:05:55,360 --> 01:05:57,840
Speaker 2: just people immediately think it's a hit piece.

1304
01:05:57,960 --> 01:05:59,480
Speaker 1: Do you remember who the report was by.

1305
01:05:59,680 --> 01:06:02,439
Speaker 2: It was by the Nanda lab mit.

1306
01:06:02,880 --> 01:06:03,240
Speaker 1: Oh wow.

1307
01:06:03,480 --> 01:06:06,080
Speaker 2: And people got really assy about it because they said, oh,

1308
01:06:06,120 --> 01:06:08,120
Speaker 2: it's just a bunch of interviews, that's how they did it.

1309
01:06:08,160 --> 01:06:09,600
Speaker 2: How the fuck do you think surveys work?

1310
01:06:09,720 --> 01:06:10,040
Speaker 1: Right?

1311
01:06:10,280 --> 01:06:12,480
Speaker 2: And so they spoke to no, they spoke to a

1312
01:06:12,520 --> 01:06:16,600
Speaker 2: bunch of Fortune one hundred I think CEOs and people

1313
01:06:16,800 --> 01:06:18,919
Speaker 2: really miss reddics. They said, oh, it's a learning gap

1314
01:06:18,920 --> 01:06:22,480
Speaker 2: between people using this and not understanding AI. No, the

1315
01:06:22,480 --> 01:06:25,000
Speaker 2: paper says it's a learning gap because the ais don't learn,

1316
01:06:25,240 --> 01:06:28,080
Speaker 2: but no one reads. Okay, but it's it's so strange

1317
01:06:28,080 --> 01:06:31,200
Speaker 2: as well, because it's everywhere. But it's also nothing. And

1318
01:06:31,240 --> 01:06:34,560
Speaker 2: I mean it feels like there is AI within the hardware.

1319
01:06:34,560 --> 01:06:38,320
Speaker 2: Well with like I forget, forget the term the upscaling ones, Yes,

1320
01:06:38,440 --> 01:06:39,439
Speaker 2: do those generally work?

1321
01:06:39,520 --> 01:06:42,560
Speaker 1: That's actually a really good point. Yeah, so, and.

1322
01:06:42,480 --> 01:06:45,840
Speaker 2: That's different to large language books different transform based that's

1323
01:06:45,880 --> 01:06:47,760
Speaker 2: that's really good DLSS and such.

1324
01:06:47,960 --> 01:06:50,800
Speaker 3: DLSS is like a real thing that works and does

1325
01:06:51,080 --> 01:06:54,680
Speaker 3: it's good. Broadly it's effective, I mean.

1326
01:06:54,560 --> 01:06:56,280
Speaker 2: And that's when it fills in the frames.

1327
01:06:56,040 --> 01:06:57,400
Speaker 1: Right DLS.

1328
01:06:57,400 --> 01:06:59,880
Speaker 3: So there's kind of like sub technologies they have, but

1329
01:07:01,040 --> 01:07:05,160
Speaker 3: broadly speaking, DLSS originally started as just it stands for

1330
01:07:05,280 --> 01:07:08,400
Speaker 3: deep learned super sampling, and it started where they would

1331
01:07:08,400 --> 01:07:12,800
Speaker 3: take ground truth images, meaning like basically we're saying this

1332
01:07:12,880 --> 01:07:16,320
Speaker 3: is reality, and I think there were sixteen K resolution.

1333
01:07:16,320 --> 01:07:19,880
Speaker 3: They're ridiculously high resolution. They would train on all these

1334
01:07:19,920 --> 01:07:26,040
Speaker 3: images and then use that data game by game to

1335
01:07:26,080 --> 01:07:31,200
Speaker 3: be able to upscale from a lower native render resolution

1336
01:07:32,040 --> 01:07:35,680
Speaker 3: to a higher i'll call it projected resolution to the viewer,

1337
01:07:35,800 --> 01:07:36,320
Speaker 3: to the user.

1338
01:07:36,800 --> 01:07:40,600
Speaker 1: And that was the original implementation and it is pretty

1339
01:07:40,600 --> 01:07:41,000
Speaker 1: good now.

1340
01:07:41,080 --> 01:07:44,080
Speaker 3: Like it's actually if you need to run at ten

1341
01:07:44,160 --> 01:07:46,920
Speaker 3: adp native so that your video card can handle the

1342
01:07:46,920 --> 01:07:50,160
Speaker 3: game at a good frame rate but make it look

1343
01:07:50,240 --> 01:07:53,040
Speaker 3: higher resolution, a lot of times it works and actually

1344
01:07:53,080 --> 01:07:56,560
Speaker 3: two N video's credit, DLSS in some situations can be

1345
01:07:56,560 --> 01:08:00,280
Speaker 3: better than native, which shouldn't be possible in theory, but

1346
01:08:00,400 --> 01:08:04,200
Speaker 3: because of the way they've actually integrated the deep learning

1347
01:08:04,240 --> 01:08:06,000
Speaker 3: on it now, which has been rebranded.

1348
01:08:05,560 --> 01:08:06,320
Speaker 1: These days to AI.

1349
01:08:06,600 --> 01:08:07,760
Speaker 2: Of course what it was called.

1350
01:08:07,600 --> 01:08:10,680
Speaker 3: Deep learning because the way they've integrated it, it can

1351
01:08:10,720 --> 01:08:14,120
Speaker 3: sometimes reconstruct details that should be there but are not,

1352
01:08:15,680 --> 01:08:17,200
Speaker 3: and we've done some videos on that.

1353
01:08:17,600 --> 01:08:19,599
Speaker 1: But yeah, that's a use case of deep learning.

1354
01:08:19,680 --> 01:08:22,000
Speaker 2: Then that's completely different to the world of laws of language.

1355
01:08:22,080 --> 01:08:23,040
Speaker 1: Yeah, it's not an LM.

1356
01:08:23,120 --> 01:08:26,200
Speaker 3: Yeah, it's like it has a singular purpose, right, make

1357
01:08:26,280 --> 01:08:28,600
Speaker 3: the thing look better, or generate frames to insert to

1358
01:08:28,640 --> 01:08:31,160
Speaker 3: smooth it over, and that's overall not bad.

1359
01:08:31,160 --> 01:08:33,080
Speaker 1: Also, there's places it's really useless.

1360
01:08:33,320 --> 01:08:36,479
Speaker 3: Yeah, But I think also though, the difference is when

1361
01:08:36,520 --> 01:08:40,840
Speaker 3: that technology is useless, it's not really harmful, whereas when

1362
01:08:40,840 --> 01:08:44,280
Speaker 3: an LM is useless, it is harmful because it's it's

1363
01:08:44,640 --> 01:08:46,160
Speaker 3: putting bad information.

1364
01:08:45,760 --> 01:08:49,000
Speaker 2: Out or just even if it's not being used particularly

1365
01:08:49,040 --> 01:08:52,120
Speaker 2: well and someone's just fucking around with it, it's incredibly environmentally damaging.

1366
01:08:52,320 --> 01:08:53,479
Speaker 1: That is a great point as well.

1367
01:08:53,600 --> 01:08:56,400
Speaker 2: Yes, they a fe your stuff being plagiarized for the models,

1368
01:08:56,520 --> 01:08:56,800
Speaker 2: you know.

1369
01:08:56,920 --> 01:09:00,360
Speaker 3: For models, Well, I know I did a there was

1370
01:09:00,400 --> 01:09:02,920
Speaker 3: a great one where I did a Google search and

1371
01:09:04,080 --> 01:09:07,160
Speaker 3: I searched for the release date of a product, and

1372
01:09:07,520 --> 01:09:09,720
Speaker 3: you know, Gemini spat out in a.

1373
01:09:09,720 --> 01:09:11,600
Speaker 1: Year and it was wrong by two years, and I

1374
01:09:11,640 --> 01:09:14,080
Speaker 1: was like, what the fuck? And I clicked to see

1375
01:09:14,120 --> 01:09:16,759
Speaker 1: what its sources were, and one of its top source

1376
01:09:16,880 --> 01:09:19,200
Speaker 1: was us, and I was like, what the fuck? Did

1377
01:09:19,240 --> 01:09:19,960
Speaker 1: we screw that up?

1378
01:09:20,040 --> 01:09:21,559
Speaker 2: Yeah? Like what ended up happening?

1379
01:09:21,680 --> 01:09:24,800
Speaker 3: So I went to our own article and it was

1380
01:09:24,800 --> 01:09:28,639
Speaker 3: a revisit we had published two years after the original

1381
01:09:28,720 --> 01:09:31,599
Speaker 3: product came out, and we made that clear in the article.

1382
01:09:32,560 --> 01:09:35,559
Speaker 3: But it's just looking at the published date and mapping

1383
01:09:35,600 --> 01:09:38,000
Speaker 3: it to the product name, and it decided this is

1384
01:09:38,040 --> 01:09:40,040
Speaker 3: the release date two years later, you know.

1385
01:09:40,160 --> 01:09:41,000
Speaker 1: And and so like.

1386
01:09:42,920 --> 01:09:48,200
Speaker 3: It learned or took from our content, misrepresented it, misrepresented it,

1387
01:09:48,479 --> 01:09:52,639
Speaker 3: and then credited the incorrect information to us.

1388
01:09:53,120 --> 01:09:55,160
Speaker 1: So now it also makes it look like I got it.

1389
01:09:55,080 --> 01:10:00,120
Speaker 2: Wrong, right, So everyone loses, including the customer. Yeah, it's

1390
01:10:00,120 --> 01:10:02,160
Speaker 2: a shame though, but I mean I feel like in

1391
01:10:02,200 --> 01:10:06,240
Speaker 2: the whole AI generitive world, your stuff is more valuable,

1392
01:10:06,280 --> 01:10:09,680
Speaker 2: the very hands on, very specific work and the very

1393
01:10:09,680 --> 01:10:10,880
Speaker 2: hardcore testing you though.

1394
01:10:11,040 --> 01:10:13,400
Speaker 3: It's also we're fortunate that it's kind of at the

1395
01:10:13,439 --> 01:10:18,320
Speaker 3: front end of like, if we're reviewing products, then.

1396
01:10:19,479 --> 01:10:21,080
Speaker 1: Someone who's an enthusiast trying.

1397
01:10:20,840 --> 01:10:24,200
Speaker 3: To decide on a purchase is still coming to us

1398
01:10:24,240 --> 01:10:26,040
Speaker 3: before it's useful in training.

1399
01:10:26,240 --> 01:10:30,160
Speaker 2: So I imagine the generative content is kind of antithetical

1400
01:10:30,200 --> 01:10:31,960
Speaker 2: to the kind of testing you do as well, because

1401
01:10:31,960 --> 01:10:34,240
Speaker 2: you can't really fake because.

1402
01:10:34,200 --> 01:10:37,040
Speaker 3: Not really, you can't really like generate a review, you know,

1403
01:10:37,040 --> 01:10:37,799
Speaker 3: it would be obvious.

1404
01:10:37,880 --> 01:10:41,040
Speaker 2: And also you have these massive machines for testing stuff here, yeah,

1405
01:10:41,040 --> 01:10:44,799
Speaker 2: which are insanely cool. And actually that's a good question.

1406
01:10:44,880 --> 01:10:46,439
Speaker 2: How do you source this kind of stuff? Do you

1407
01:10:46,439 --> 01:10:49,679
Speaker 2: buy from industrial because you have like pressure tested, Well, actually,

1408
01:10:49,720 --> 01:10:51,520
Speaker 2: maybe you could speak to some of the machines.

1409
01:10:51,280 --> 01:10:51,760
Speaker 1: Run through it.

1410
01:10:51,840 --> 01:10:55,360
Speaker 3: Yeah, So yeah, we have a Hemiana Quick chamber, which

1411
01:10:55,400 --> 01:10:59,040
Speaker 3: is a sound chamber and acoustic test chamber. We have

1412
01:10:59,680 --> 01:11:03,920
Speaker 3: a laser scanner that does three D scans of like

1413
01:11:04,600 --> 01:11:05,880
Speaker 3: of products.

1414
01:11:06,000 --> 01:11:07,679
Speaker 1: And converted some into three D models.

1415
01:11:07,960 --> 01:11:11,000
Speaker 3: We have pressure testers, we have fan testers, cooler testing,

1416
01:11:11,720 --> 01:11:14,760
Speaker 3: and then more traditional power supply tester stuff like that,

1417
01:11:15,680 --> 01:11:20,080
Speaker 3: and so yeah, generally, the way we go about it

1418
01:11:20,120 --> 01:11:26,280
Speaker 3: is we identify a problem. Typically, this is kind of

1419
01:11:26,280 --> 01:11:28,200
Speaker 3: the part of the business I work on the most personally,

1420
01:11:28,360 --> 01:11:31,879
Speaker 3: is like basically test engineering or design. So we identify

1421
01:11:31,880 --> 01:11:34,760
Speaker 3: a shortcoming, which is like this product is claiming this thing.

1422
01:11:35,360 --> 01:11:38,280
Speaker 3: We are not able to validate or invalidate their claims

1423
01:11:38,320 --> 01:11:40,559
Speaker 3: because we don't have the tool to do it. And

1424
01:11:40,600 --> 01:11:43,360
Speaker 3: then either I just do some research online and find

1425
01:11:43,360 --> 01:11:46,280
Speaker 3: the tool, or you know, sometimes the real challenge is

1426
01:11:46,280 --> 01:11:49,040
Speaker 3: knowing the name of a thing and that it exists.

1427
01:11:49,720 --> 01:11:52,599
Speaker 3: And so I went through this with current clamps, which

1428
01:11:52,640 --> 01:11:54,240
Speaker 3: is just a clamp you put on a wire to

1429
01:11:54,280 --> 01:11:57,400
Speaker 3: read the current going through it. A long time ago,

1430
01:11:57,479 --> 01:11:58,920
Speaker 3: when I started this, I didn't know that was a

1431
01:11:58,920 --> 01:12:02,759
Speaker 3: tool that existed. And it's like magic because you put

1432
01:12:02,800 --> 01:12:06,320
Speaker 3: a wire through a client a plastic looking clamp, and

1433
01:12:06,360 --> 01:12:09,559
Speaker 3: then through the magic of electromagnetics, it tells you what

1434
01:12:09,600 --> 01:12:12,800
Speaker 3: the amperage is. And when I found that, you know

1435
01:12:13,040 --> 01:12:17,120
Speaker 3: early and it's not a new it's been around forever.

1436
01:12:17,520 --> 01:12:19,640
Speaker 3: But when it was new to me, I was like,

1437
01:12:19,680 --> 01:12:21,840
Speaker 3: holy shit, this is If I only knew the name

1438
01:12:21,880 --> 01:12:24,120
Speaker 3: of this thing sooner, I could have bought it.

1439
01:12:24,160 --> 01:12:25,880
Speaker 2: And all of your testing is effectively new to you.

1440
01:12:25,880 --> 01:12:27,799
Speaker 2: You've had to kind of build it and learn yourself

1441
01:12:28,160 --> 01:12:29,840
Speaker 2: with help from right, with.

1442
01:12:29,760 --> 01:12:31,520
Speaker 1: A lot of expert help outside.

1443
01:12:31,960 --> 01:12:35,840
Speaker 3: And yeah, I would say sourcing it mostly comes from

1444
01:12:36,320 --> 01:12:39,320
Speaker 3: either just doing research or we tore a lot of

1445
01:12:40,000 --> 01:12:43,320
Speaker 3: factories and engineering facilities and make videos on it, and

1446
01:12:43,920 --> 01:12:47,040
Speaker 3: normally when I'm there, I do my best to talk

1447
01:12:47,080 --> 01:12:50,880
Speaker 3: to the actual people who use that equipment. And that's

1448
01:12:51,000 --> 01:12:52,760
Speaker 3: that's kind of how we learned that it exists, you know,

1449
01:12:52,800 --> 01:12:54,880
Speaker 3: Like I did a tour recently of a facility where

1450
01:12:55,520 --> 01:12:57,320
Speaker 3: they showed us something that they had built for a

1451
01:12:57,360 --> 01:13:00,000
Speaker 3: client for testing cooling products.

1452
01:13:00,320 --> 01:13:01,559
Speaker 1: And when they.

1453
01:13:01,439 --> 01:13:03,439
Speaker 3: Were done explaining it so I could talk about it

1454
01:13:03,439 --> 01:13:06,759
Speaker 3: in a video, I said to them, can I buy.

1455
01:13:06,600 --> 01:13:07,280
Speaker 1: One of those?

1456
01:13:07,720 --> 01:13:07,880
Speaker 2: You know?

1457
01:13:08,080 --> 01:13:12,679
Speaker 1: But the yeah, yeah, yeah, they sell it, so that's

1458
01:13:12,720 --> 01:13:13,840
Speaker 1: so cool. Yeah.

1459
01:13:13,880 --> 01:13:15,479
Speaker 2: And do they come and train you to use it?

1460
01:13:15,840 --> 01:13:16,840
Speaker 1: Sometimes you can.

1461
01:13:16,960 --> 01:13:18,680
Speaker 3: You can either pay for training or they'll do it

1462
01:13:18,680 --> 01:13:20,400
Speaker 3: for free for up to whatever four.

1463
01:13:20,240 --> 01:13:21,000
Speaker 1: Hours or something.

1464
01:13:21,040 --> 01:13:23,680
Speaker 2: You know. And do you generally operate these machines or

1465
01:13:24,000 --> 01:13:24,680
Speaker 2: do they train the.

1466
01:13:24,680 --> 01:13:27,960
Speaker 3: Crew generally, either I'm the first one to learn how

1467
01:13:28,000 --> 01:13:31,960
Speaker 3: to use it, or someone specific on the team might

1468
01:13:32,000 --> 01:13:33,519
Speaker 3: be one of the first ones to learn how to

1469
01:13:33,600 --> 01:13:33,840
Speaker 3: use it.

1470
01:13:34,280 --> 01:13:36,240
Speaker 1: So like we had.

1471
01:13:37,840 --> 01:13:41,719
Speaker 3: For the laser scanner, it was Patrick on the team

1472
01:13:42,040 --> 01:13:44,760
Speaker 3: who ultimately in that case I had tasked him with

1473
01:13:44,840 --> 01:13:47,160
Speaker 3: learning how to use it, and he went through he

1474
01:13:47,240 --> 01:13:50,400
Speaker 3: documented it you know, and now anyone can use the sop.

1475
01:13:50,360 --> 01:13:52,360
Speaker 2: And the laser's kind of you describing to me earlier.

1476
01:13:52,439 --> 01:13:56,160
Speaker 2: It's used that to see if there's devotes ye, like

1477
01:13:56,200 --> 01:13:59,400
Speaker 2: in the in the cooling you explain.

1478
01:13:59,120 --> 01:14:01,240
Speaker 1: I'm surface, I'm doing it terrible job. Now you're pretty

1479
01:14:01,320 --> 01:14:01,920
Speaker 1: much right on it.

1480
01:14:01,960 --> 01:14:04,519
Speaker 3: I mean it's yeah, cooling product has a flat surface

1481
01:14:04,560 --> 01:14:07,080
Speaker 3: that needs to contact a piece of silicon. And what

1482
01:14:07,120 --> 01:14:10,080
Speaker 3: we're looking for is, Okay, the performance is really good

1483
01:14:10,160 --> 01:14:13,519
Speaker 3: or really bad thermally, and we can't look at it

1484
01:14:13,560 --> 01:14:15,920
Speaker 3: and figure out why. Maybe if we scan this at

1485
01:14:15,920 --> 01:14:18,920
Speaker 3: a microscopic level, it'll reveal something.

1486
01:14:19,400 --> 01:14:20,640
Speaker 1: And so sometimes.

1487
01:14:20,200 --> 01:14:24,240
Speaker 3: It'll reveal that there's these like deep pits in the

1488
01:14:24,280 --> 01:14:27,360
Speaker 3: surface of the metal that you can't necessarily see by

1489
01:14:27,400 --> 01:14:31,160
Speaker 3: eye and can really affect the cooling performance. Other times

1490
01:14:31,200 --> 01:14:35,160
Speaker 3: you might see a curvature to it where maybe externally

1491
01:14:35,240 --> 01:14:37,040
Speaker 3: it's not obvious, but actually when you install it on

1492
01:14:37,080 --> 01:14:39,880
Speaker 3: the silicon product, say only two thirds of it or

1493
01:14:39,960 --> 01:14:43,519
Speaker 3: contact in the metal. And so this laser scanner scans

1494
01:14:43,520 --> 01:14:46,320
Speaker 3: the surface with the laser and then makes a three

1495
01:14:46,400 --> 01:14:49,880
Speaker 3: D model, and we can use that to inspect the problems.

1496
01:14:50,240 --> 01:14:52,800
Speaker 2: Do you ever get do companies ever reach out for

1497
01:14:52,840 --> 01:14:54,000
Speaker 2: any consultancy things.

1498
01:14:54,080 --> 01:14:57,240
Speaker 1: They do that all the time. We reject all of it.

1499
01:14:58,520 --> 01:15:02,400
Speaker 1: So because it's too much. There's a lot of reasons.

1500
01:15:02,439 --> 01:15:04,479
Speaker 3: The core of all of it is it's too much

1501
01:15:05,320 --> 01:15:09,920
Speaker 3: conflict of interest, right where let's just like, let's just

1502
01:15:10,000 --> 01:15:13,639
Speaker 3: say it's possible to take a testing job, a private

1503
01:15:13,680 --> 01:15:18,519
Speaker 3: testing job, and do it with absolutely zero bias towards

1504
01:15:18,600 --> 01:15:19,320
Speaker 3: future reviews.

1505
01:15:19,680 --> 01:15:22,120
Speaker 1: I just we'll just accept that premise for a second.

1506
01:15:22,680 --> 01:15:25,080
Speaker 3: Even under those conditions, I still don't like it because

1507
01:15:26,160 --> 01:15:29,559
Speaker 3: now I'm putting a weird spot where when that product launches,

1508
01:15:30,479 --> 01:15:32,160
Speaker 3: it's gonna be hard for me to review.

1509
01:15:31,920 --> 01:15:35,120
Speaker 2: It because you, oh, because you've already seen it.

1510
01:15:35,240 --> 01:15:37,840
Speaker 3: I've seen it, and I might have provided input on

1511
01:15:37,880 --> 01:15:39,320
Speaker 3: it that they paid for.

1512
01:15:39,280 --> 01:15:40,320
Speaker 1: If I'm involved.

1513
01:15:40,400 --> 01:15:43,320
Speaker 3: Right, So, now, like let's say I'm not happy with

1514
01:15:43,360 --> 01:15:45,800
Speaker 3: their execution, What am I gonna go say?

1515
01:15:45,800 --> 01:15:47,280
Speaker 1: I told them so, right, Like.

1516
01:15:47,280 --> 01:15:49,639
Speaker 2: That's not how much can you reveal? And even then

1517
01:15:49,800 --> 01:15:52,000
Speaker 2: I mentioned the trade secret so brilliant.

1518
01:15:51,720 --> 01:15:53,120
Speaker 1: You probably end up under an NDA.

1519
01:15:53,960 --> 01:15:55,920
Speaker 3: The best approach to that would be to recuse yourself

1520
01:15:55,920 --> 01:15:58,680
Speaker 3: from reviewing it at all. But then the problem is,

1521
01:15:59,120 --> 01:16:01,280
Speaker 3: like now I can't do my job for consumers.

1522
01:16:01,360 --> 01:16:02,439
Speaker 2: Yeah, how good is the money on?

1523
01:16:02,520 --> 01:16:02,920
Speaker 5: I like?

1524
01:16:03,280 --> 01:16:03,840
Speaker 1: Yeah?

1525
01:16:03,960 --> 01:16:07,000
Speaker 3: And I also think it just cannibalizes the process where

1526
01:16:07,439 --> 01:16:10,400
Speaker 3: you're taking things that would make excellent public videos and

1527
01:16:10,439 --> 01:16:13,479
Speaker 3: public data, and you're presenting it privately to never be

1528
01:16:13,520 --> 01:16:14,320
Speaker 3: seen by anyone.

1529
01:16:15,000 --> 01:16:18,559
Speaker 2: Right And by the nature of these agreements, I imagine they

1530
01:16:18,560 --> 01:16:20,280
Speaker 2: could obfiscate your coverage on some level.

1531
01:16:20,280 --> 01:16:20,880
Speaker 1: I would think so.

1532
01:16:21,160 --> 01:16:25,200
Speaker 3: And also it's just, yeah, you're taking the thing that

1533
01:16:25,280 --> 01:16:27,479
Speaker 3: made you desirable to do the testing to begin with.

1534
01:16:27,800 --> 01:16:30,400
Speaker 3: You're doing it privately, so it's not public, So the

1535
01:16:30,479 --> 01:16:33,479
Speaker 3: desire to have you do the private testing reduces, right, right,

1536
01:16:33,520 --> 01:16:36,280
Speaker 3: Like it seems like it's just a sort of self sabotage.

1537
01:16:36,320 --> 01:16:38,840
Speaker 2: But how do the hardware companies feel about you having

1538
01:16:38,880 --> 01:16:40,120
Speaker 2: such high level testing?

1539
01:16:40,600 --> 01:16:43,160
Speaker 3: Most of the people think it's cool, right, you know,

1540
01:16:43,600 --> 01:16:48,679
Speaker 3: I think the I'm sure a lot of them don't care.

1541
01:16:49,680 --> 01:16:53,880
Speaker 3: I know that some of the company representatives have told

1542
01:16:53,880 --> 01:16:58,040
Speaker 3: me how they'll be more careful with how they market

1543
01:16:58,080 --> 01:17:01,799
Speaker 3: certain things if they know we're gonna yeah rocks.

1544
01:17:01,880 --> 01:17:03,320
Speaker 2: I actually genuinely love that.

1545
01:17:03,560 --> 01:17:04,080
Speaker 1: Yeah.

1546
01:17:04,120 --> 01:17:06,080
Speaker 3: So, and that's not just us, you know, there's other

1547
01:17:06,120 --> 01:17:09,360
Speaker 3: reviewers who also do an excellent job. And because the

1548
01:17:09,400 --> 01:17:14,200
Speaker 3: review community. People kind of specialize in different areas. I

1549
01:17:14,240 --> 01:17:17,479
Speaker 3: think it just sort of collectively keeps companies somewhat on

1550
01:17:17,520 --> 01:17:21,320
Speaker 3: their toes. But obviously you know the company is going

1551
01:17:21,400 --> 01:17:21,799
Speaker 3: to company.

1552
01:17:22,000 --> 01:17:36,479
Speaker 2: Yeah, they will shit about regardless. What is a kind

1553
01:17:36,479 --> 01:17:38,120
Speaker 2: of testing you can't do right now that you want

1554
01:17:38,120 --> 01:17:38,879
Speaker 2: to in the future.

1555
01:17:39,200 --> 01:17:45,559
Speaker 3: I would say the probably the the Well, so there's

1556
01:17:45,560 --> 01:17:49,800
Speaker 3: one we can do, but it's not really practical, and

1557
01:17:49,880 --> 01:17:54,439
Speaker 3: that would be basically more frequent transience testing. So there's

1558
01:17:54,439 --> 01:17:58,599
Speaker 3: something with power delivery. I know you've been studying lately

1559
01:17:59,760 --> 01:18:03,400
Speaker 3: where where there's transient spikes and so on a GPU

1560
01:18:03,439 --> 01:18:03,960
Speaker 3: or a CPU.

1561
01:18:04,000 --> 01:18:04,599
Speaker 1: This would be.

1562
01:18:04,680 --> 01:18:10,719
Speaker 3: A basically microscopic spike in the current or the power

1563
01:18:10,720 --> 01:18:14,640
Speaker 3: consumption right for really like normally like one hundred microseconds

1564
01:18:14,720 --> 01:18:15,120
Speaker 3: or something.

1565
01:18:15,400 --> 01:18:17,200
Speaker 1: We can test it. We've done in the past.

1566
01:18:18,320 --> 01:18:21,920
Speaker 3: But because if you're capturing data for seconds out of time,

1567
01:18:22,120 --> 01:18:26,840
Speaker 3: down to scales of thirty microsecond gaps or whatever, the

1568
01:18:27,160 --> 01:18:29,519
Speaker 3: amount of data is enormous, it's really hard to process.

1569
01:18:29,520 --> 01:18:31,439
Speaker 2: It's like a storage and processing problem.

1570
01:18:31,520 --> 01:18:33,320
Speaker 1: Yeah, it's a major processing problem.

1571
01:18:33,360 --> 01:18:35,120
Speaker 2: And what would you want to be so is that

1572
01:18:35,479 --> 01:18:37,639
Speaker 2: if there is, what would those spikes mean?

1573
01:18:38,040 --> 01:18:42,080
Speaker 3: It would help us to stay on top of especially

1574
01:18:42,120 --> 01:18:48,080
Speaker 3: GPU manufacturers, but also CPU if if there's sudden spikes

1575
01:18:48,080 --> 01:18:50,000
Speaker 3: that might take a system offline. So as an example,

1576
01:18:50,000 --> 01:18:54,680
Speaker 3: this happened with a previous generation of both Nvidia and mdgpus,

1577
01:18:54,680 --> 01:18:57,880
Speaker 3: but where they would have large spikes and power draw

1578
01:18:57,920 --> 01:19:00,840
Speaker 3: that deviated from the non old draw. So if you're

1579
01:19:00,840 --> 01:19:03,599
Speaker 3: at four hundred and fifty watts and there's a spike

1580
01:19:03,680 --> 01:19:07,040
Speaker 3: to eleven hundred watts for one hundred micro seconds or something,

1581
01:19:07,640 --> 01:19:11,280
Speaker 3: this might be enough to trip over current protection on

1582
01:19:11,280 --> 01:19:14,160
Speaker 3: the power spot and just shut the computer off. And

1583
01:19:14,160 --> 01:19:16,680
Speaker 3: then the end user is like, what the fuck? My

1584
01:19:16,720 --> 01:19:18,879
Speaker 3: power supply is enough to handle four hundred and fifty.

1585
01:19:18,640 --> 01:19:20,479
Speaker 1: Watts right off?

1586
01:19:20,520 --> 01:19:22,240
Speaker 2: And this happened that Yeah.

1587
01:19:22,080 --> 01:19:24,240
Speaker 3: We saw this with I want to say it was

1588
01:19:24,240 --> 01:19:29,400
Speaker 3: the thirty series, the RTX thirty series, and like it

1589
01:19:29,400 --> 01:19:31,679
Speaker 3: was a problem that doesn't show up in normal power testing,

1590
01:19:32,120 --> 01:19:33,680
Speaker 3: but within a silloscope you can see it.

1591
01:19:34,400 --> 01:19:39,920
Speaker 1: And uh again credit to end video for the problems

1592
01:19:39,920 --> 01:19:40,519
Speaker 1: we point out.

1593
01:19:40,560 --> 01:19:42,840
Speaker 3: On the positive side, they did actually fix this problem

1594
01:19:42,840 --> 01:19:43,639
Speaker 3: in the forty series.

1595
01:19:43,760 --> 01:19:47,040
Speaker 2: Yeah, so here's here's a weird one, but I know

1596
01:19:47,080 --> 01:19:50,519
Speaker 2: it's near detO heart Linux Gaming. Yeah, are you actually,

1597
01:19:50,640 --> 01:19:53,440
Speaker 2: do you think this is a viable alternative to Windows

1598
01:19:53,479 --> 01:19:56,960
Speaker 2: with Windows ten kind of dying will being killed in

1599
01:19:57,000 --> 01:19:57,439
Speaker 2: the bag?

1600
01:19:57,680 --> 01:20:01,559
Speaker 1: Yeah, I think. I think Microsoft is the best marketing

1601
01:20:01,600 --> 01:20:02,679
Speaker 1: that Linux has ever had.

1602
01:20:02,840 --> 01:20:04,840
Speaker 2: I go on, Yeah, My.

1603
01:20:05,240 --> 01:20:10,120
Speaker 3: Biggest concern with Windows is not like the death of

1604
01:20:10,240 --> 01:20:17,240
Speaker 3: ten ongoing security support. It is the slow intrusion of spyware.

1605
01:20:18,640 --> 01:20:19,479
Speaker 1: Well like recall.

1606
01:20:20,080 --> 01:20:23,639
Speaker 3: Yes, you know where recall is marketed as this secure,

1607
01:20:24,040 --> 01:20:32,040
Speaker 3: locally saved, encrypted reel of your information. But to me,

1608
01:20:32,880 --> 01:20:35,960
Speaker 3: like capturing screenshots of your desktop while you use it

1609
01:20:36,000 --> 01:20:37,640
Speaker 3: at all is problematic.

1610
01:20:37,960 --> 01:20:39,519
Speaker 1: Yes, and we've done some testing.

1611
01:20:39,560 --> 01:20:42,920
Speaker 3: It's not published yet, but it'll do some dumb filtering

1612
01:20:42,960 --> 01:20:44,800
Speaker 3: so if it sees the word password on the screen,

1613
01:20:44,880 --> 01:20:47,519
Speaker 3: it won't take a screen shot, right, But like, you're

1614
01:20:47,560 --> 01:20:49,280
Speaker 3: not always going to have one of those words on

1615
01:20:49,320 --> 01:20:52,679
Speaker 3: the screen when it shouldn't take a screen shot.

1616
01:20:52,960 --> 01:20:53,160
Speaker 2: Right.

1617
01:20:53,160 --> 01:20:56,280
Speaker 3: Maybe you have some accounting documents open, you know, and

1618
01:20:56,720 --> 01:20:59,559
Speaker 3: it's information that's sensitive, but recall doesn't know it's sensitive.

1619
01:21:00,200 --> 01:21:02,840
Speaker 3: And uh, it's stuff like that that concerns me, where

1620
01:21:04,560 --> 01:21:08,719
Speaker 3: it's breachable and exploitable because it exists not necessarily because

1621
01:21:08,720 --> 01:21:13,680
Speaker 3: there is an exploit, right and uh, and then Windows

1622
01:21:13,840 --> 01:21:19,120
Speaker 3: eleven is continuing to add telemetry and user data and

1623
01:21:19,160 --> 01:21:20,679
Speaker 3: engagement monitoring tools.

1624
01:21:20,800 --> 01:21:22,880
Speaker 2: And that's kind of a big feature of home s,

1625
01:21:23,120 --> 01:21:26,160
Speaker 2: like all the horrible s operating systems, the cheap ones.

1626
01:21:26,360 --> 01:21:30,760
Speaker 3: Yeah, it's yeah, everything that. It's just there's so much

1627
01:21:31,240 --> 01:21:35,080
Speaker 3: data harvesting, you know, Microsoft's This is why I think

1628
01:21:35,120 --> 01:21:37,360
Speaker 3: Microsoft hasn't really cared too much in recent years.

1629
01:21:37,400 --> 01:21:40,200
Speaker 1: If you if you don't license Windows. They used to

1630
01:21:40,200 --> 01:21:40,719
Speaker 1: really care.

1631
01:21:40,600 --> 01:21:43,000
Speaker 3: About that, yes, because now it's like, yeah, go ahead

1632
01:21:43,000 --> 01:21:45,240
Speaker 3: and steal it from us, like we're going to just

1633
01:21:45,240 --> 01:21:46,640
Speaker 3: take all your data and that's how we make the

1634
01:21:46,680 --> 01:21:47,280
Speaker 3: money anyway.

1635
01:21:47,439 --> 01:21:50,880
Speaker 2: Horrifying. But do you think Linux is viable as a

1636
01:21:50,920 --> 01:21:51,400
Speaker 2: gaming plot?

1637
01:21:51,520 --> 01:21:54,240
Speaker 3: I think it as a gaming platform specifically, I think

1638
01:21:54,280 --> 01:21:57,639
Speaker 3: it's becoming a lot more viable. So thanks to Valve

1639
01:21:57,760 --> 01:22:03,160
Speaker 3: and the Steam deck ands and it's pushed for Proton

1640
01:22:03,240 --> 01:22:05,519
Speaker 3: as a translation layer between the application and.

1641
01:22:05,560 --> 01:22:06,880
Speaker 1: The operating system.

1642
01:22:06,920 --> 01:22:09,880
Speaker 3: And what is that just for the Yeah, so Proton

1643
01:22:10,439 --> 01:22:14,439
Speaker 3: is it's a translation layer, which means it's working to

1644
01:22:15,080 --> 01:22:19,200
Speaker 3: effectively interpret the code that is that the game is

1645
01:22:19,240 --> 01:22:23,679
Speaker 3: built with to run with better performance or at all

1646
01:22:24,080 --> 01:22:26,760
Speaker 3: on a different operating system in this case Linux or

1647
01:22:26,800 --> 01:22:31,360
Speaker 3: Stemos specifically, and so because of Valve's work on that

1648
01:22:31,680 --> 01:22:36,719
Speaker 3: to make games more compatible, run smoother, you know, deliver

1649
01:22:36,880 --> 01:22:39,479
Speaker 3: consistent frame rate and pacing of the frames.

1650
01:22:39,760 --> 01:22:41,040
Speaker 1: Because their work there.

1651
01:22:41,880 --> 01:22:45,520
Speaker 3: In some instances it actually has better performance than Windows.

1652
01:22:45,720 --> 01:22:45,840
Speaker 2: Right.

1653
01:22:46,840 --> 01:22:49,759
Speaker 3: The limiting factor is still sometimes it just simply doesn't work,

1654
01:22:50,320 --> 01:22:53,479
Speaker 3: but that has become a lot less the case than

1655
01:22:53,520 --> 01:22:55,120
Speaker 3: what it was, say, ten years ago.

1656
01:22:56,800 --> 01:22:57,840
Speaker 1: It's not a fix for everybody.

1657
01:22:57,880 --> 01:22:59,680
Speaker 3: There's still times you're gonna try and run a game

1658
01:22:59,720 --> 01:23:01,439
Speaker 3: and it's not gonna work, and that's gonna suck.

1659
01:23:01,640 --> 01:23:02,880
Speaker 2: And how's the driver support?

1660
01:23:02,960 --> 01:23:06,080
Speaker 1: For example, hit and miss? So we're really early in

1661
01:23:06,080 --> 01:23:07,599
Speaker 1: this test in but.

1662
01:23:09,600 --> 01:23:12,080
Speaker 3: As an example, I know, Intel recently laid off a

1663
01:23:12,120 --> 01:23:17,880
Speaker 3: bunch of their teams that maintains various Linux driversware. Yeah,

1664
01:23:17,880 --> 01:23:19,960
Speaker 3: and so it's kind of you know, we don't really

1665
01:23:19,960 --> 01:23:22,479
Speaker 3: know what happens there. Maybe the community picks it up,

1666
01:23:22,479 --> 01:23:23,800
Speaker 3: I guess, I hope so, but.

1667
01:23:25,439 --> 01:23:28,839
Speaker 1: Yeah, he will, Yeah, yeah, it depends.

1668
01:23:28,840 --> 01:23:31,080
Speaker 2: Also, it really feels bad to just be like, who's

1669
01:23:31,120 --> 01:23:33,280
Speaker 2: gonna take responsibility for this thing we need?

1670
01:23:33,560 --> 01:23:36,240
Speaker 3: Yeah, and if it's even an open source driver to

1671
01:23:36,280 --> 01:23:39,400
Speaker 3: begin with. So yeah, it's hit and miss, but I

1672
01:23:39,400 --> 01:23:41,880
Speaker 3: would say that the biggest limitation of my experience with Linux,

1673
01:23:41,880 --> 01:23:43,640
Speaker 3: and I'm not an expert in Linux. There's no new

1674
01:23:43,680 --> 01:23:44,960
Speaker 3: people in your audience who.

1675
01:23:45,080 --> 01:23:48,479
Speaker 2: Know they email me whenever I say alternative y wes.

1676
01:23:48,720 --> 01:23:50,439
Speaker 3: Well, that's why we we better not even get into

1677
01:23:50,439 --> 01:23:51,800
Speaker 3: distributions of Linux.

1678
01:23:51,560 --> 01:23:54,639
Speaker 2: Or oh no, they will. They will be up my ass.

1679
01:23:56,320 --> 01:24:01,400
Speaker 3: Arch by the way, But yeah, I think the.

1680
01:24:02,479 --> 01:24:02,880
Speaker 1: I think.

1681
01:24:03,680 --> 01:24:07,680
Speaker 3: I think the biggest you know, limiting factors is compatibility

1682
01:24:07,680 --> 01:24:11,240
Speaker 3: with things like daily applications. So the tools we use

1683
01:24:11,280 --> 01:24:15,000
Speaker 3: for video editing generally just don't work on Linux. We'd

1684
01:24:15,000 --> 01:24:17,400
Speaker 3: have to use something else. Yeah, and that's a problem.

1685
01:24:17,520 --> 01:24:21,000
Speaker 2: But well, adjacent to this Linux conversation, how are you

1686
01:24:21,000 --> 01:24:22,160
Speaker 2: feel about handheld gaming?

1687
01:24:22,560 --> 01:24:23,559
Speaker 1: Handhelds are really cool.

1688
01:24:23,920 --> 01:24:28,080
Speaker 3: I think there's faster innovation happening and handhelds than most

1689
01:24:28,120 --> 01:24:28,839
Speaker 3: other places.

1690
01:24:29,040 --> 01:24:32,000
Speaker 2: Are there any really like? Because I know a zeus

1691
01:24:32,520 --> 01:24:34,880
Speaker 2: because being on the Naughty List a bit. But I

1692
01:24:34,960 --> 01:24:36,960
Speaker 2: like the steam Deck personally, But like, do you have

1693
01:24:37,000 --> 01:24:38,160
Speaker 2: at a favorite brand?

1694
01:24:38,280 --> 01:24:41,520
Speaker 3: The steam Deck and the Ally are both pretty cool devices,

1695
01:24:41,600 --> 01:24:45,640
Speaker 3: despite the Ally's warranty issues, like it actually is a

1696
01:24:45,680 --> 01:24:49,360
Speaker 3: cool piece of hardware. I thought the Lenovo Legion Go

1697
01:24:49,479 --> 01:24:54,599
Speaker 3: the original was a really unique and innovative gimmick.

1698
01:24:54,720 --> 01:24:56,360
Speaker 1: And I don't use that word.

1699
01:24:56,120 --> 01:24:57,280
Speaker 2: To like degrade the gimmick.

1700
01:24:57,360 --> 01:25:02,200
Speaker 1: The gimmick was the controllers detached. I like the switch. Yeah,

1701
01:25:02,240 --> 01:25:07,120
Speaker 1: and then the steam deck is uh.

1702
01:25:07,320 --> 01:25:09,559
Speaker 3: It was just kind of the first in the new

1703
01:25:09,640 --> 01:25:13,280
Speaker 3: round of handhelds. You know, GPD existed before them and

1704
01:25:13,400 --> 01:25:14,599
Speaker 3: Ioneo and those guys.

1705
01:25:14,720 --> 01:25:18,000
Speaker 2: I respect GPD. They're weird, but they're trying something.

1706
01:25:18,200 --> 01:25:22,160
Speaker 1: Yeah. GPD and Ioneo both are weird but trying something.

1707
01:25:22,240 --> 01:25:25,240
Speaker 2: Yeah. I appreciate you don't have American manufacturers do it.

1708
01:25:25,280 --> 01:25:28,360
Speaker 2: Actually it's good. Are the American manufacturers trying weird shit

1709
01:25:28,479 --> 01:25:30,320
Speaker 2: like that or is it predominantly.

1710
01:25:32,000 --> 01:25:35,479
Speaker 3: It depends like how you how you define American here

1711
01:25:35,520 --> 01:25:43,120
Speaker 3: because you know design, yes, like who depends on how

1712
01:25:43,160 --> 01:25:45,960
Speaker 3: you count Lenovo At this point, I don't know if

1713
01:25:46,000 --> 01:25:48,200
Speaker 3: you count them as American or not.

1714
01:25:48,400 --> 01:25:49,840
Speaker 2: Right, but they're trying weird shit.

1715
01:25:50,360 --> 01:25:51,200
Speaker 1: They are doing.

1716
01:25:50,960 --> 01:25:54,640
Speaker 3: Weird stuff, and and they you know, they certainly have

1717
01:25:54,800 --> 01:25:58,240
Speaker 3: large US headquarter offices. I don't know where their design happens.

1718
01:25:58,520 --> 01:26:01,080
Speaker 3: It's probably they have a base I think office. It's

1719
01:26:01,120 --> 01:26:05,639
Speaker 3: probably there. But Valve is definitely the coolest in terms

1720
01:26:05,720 --> 01:26:12,280
Speaker 3: of they set the tempo for this to reignite, Like

1721
01:26:12,320 --> 01:26:16,160
Speaker 3: they're the ones who made handheld interesting again, and everyone

1722
01:26:16,160 --> 01:26:18,599
Speaker 3: else jumped in and started doing stuff and that's pretty cool.

1723
01:26:18,760 --> 01:26:21,600
Speaker 3: And Valve also said, you know, we're gonna make Stemos

1724
01:26:21,640 --> 01:26:25,960
Speaker 3: available to other handheld manufacturers if they want to use it.

1725
01:26:25,960 --> 01:26:27,479
Speaker 1: I don't know if there's a license or not, but

1726
01:26:27,920 --> 01:26:29,320
Speaker 1: like it's available.

1727
01:26:28,880 --> 01:26:30,559
Speaker 2: And that's not being picked up. I know you can

1728
01:26:30,640 --> 01:26:31,559
Speaker 2: kind of sideload it.

1729
01:26:32,000 --> 01:26:33,240
Speaker 1: Yeah, you can definitely sideload it.

1730
01:26:33,280 --> 01:26:37,800
Speaker 3: I think officially, I want to say Lenovo might have

1731
01:26:37,880 --> 01:26:42,400
Speaker 3: been the first one to actually offer it, right zeither Lenovo.

1732
01:26:42,600 --> 01:26:45,200
Speaker 3: I don't think it was asues, but but yeah, someone's

1733
01:26:45,200 --> 01:26:45,680
Speaker 3: picked it up.

1734
01:26:45,720 --> 01:26:48,400
Speaker 2: How do you feel about the Xbook's Rogue Ally.

1735
01:26:49,600 --> 01:26:51,559
Speaker 3: I think there's a lot of confusion around it in

1736
01:26:51,600 --> 01:26:55,880
Speaker 3: the more mainstream audience. I've noticed talment threads where people

1737
01:26:55,880 --> 01:26:58,640
Speaker 3: think it's going to be required to play what you

1738
01:26:58,640 --> 01:27:02,920
Speaker 3: would consider an Xbox game, But it's like basically a PC.

1739
01:27:03,400 --> 01:27:06,120
Speaker 2: It's just a rogue x ally with Xbox branding.

1740
01:27:05,880 --> 01:27:09,479
Speaker 1: Right basically yeh. And I'm sure there's some software gifts,

1741
01:27:09,800 --> 01:27:10,160
Speaker 1: you know.

1742
01:27:10,120 --> 01:27:12,840
Speaker 2: But I wonder if it works because that's not being

1743
01:27:13,040 --> 01:27:15,560
Speaker 2: I love my rogue ally, but the fucking software that

1744
01:27:15,600 --> 01:27:17,559
Speaker 2: pops up really gets in the way of gaming.

1745
01:27:17,800 --> 01:27:18,040
Speaker 1: Yeah.

1746
01:27:18,120 --> 01:27:20,599
Speaker 3: I don't really know what Microsoft is doing with Xbox.

1747
01:27:20,640 --> 01:27:23,120
Speaker 3: It just seems like they're they're not sure what to

1748
01:27:23,160 --> 01:27:24,240
Speaker 3: do with that brand right now.

1749
01:27:24,360 --> 01:27:26,519
Speaker 2: I have to I was gonna ask, like, what do

1750
01:27:26,560 --> 01:27:28,920
Speaker 2: you think Microsoft's deal with gaming is right now? They

1751
01:27:29,040 --> 01:27:31,200
Speaker 2: seem almost like they don't want to do it.

1752
01:27:31,200 --> 01:27:35,519
Speaker 3: It's weird because they they were so committed to locking

1753
01:27:35,560 --> 01:27:38,000
Speaker 3: people into the Xbox for like a generation or two,

1754
01:27:38,760 --> 01:27:42,560
Speaker 3: and then at some point my memory of it is

1755
01:27:42,600 --> 01:27:44,960
Speaker 3: they kind of realized, like, wait a minute, you know,

1756
01:27:45,000 --> 01:27:50,639
Speaker 3: as we moved to X eighty six architectures for consoles PC,

1757
01:27:50,800 --> 01:27:53,960
Speaker 3: gaming kind of works on both these devices, so we

1758
01:27:53,960 --> 01:27:55,519
Speaker 3: don't really care if they buy it on PC or

1759
01:27:55,560 --> 01:27:57,960
Speaker 3: on Xbox, as long as they use our device.

1760
01:27:58,040 --> 01:28:00,280
Speaker 2: And they raise the price on game Pass as well.

1761
01:28:00,400 --> 01:28:02,559
Speaker 1: Yeah, and and games oh.

1762
01:28:02,560 --> 01:28:04,599
Speaker 2: Of course at the same time, and also the Xbox.

1763
01:28:04,720 --> 01:28:08,200
Speaker 3: Yeah, and then you know, surprised the Pikachu face when

1764
01:28:08,680 --> 01:28:10,639
Speaker 3: they raised the price on games and then they raised

1765
01:28:10,640 --> 01:28:14,160
Speaker 3: the press on games Pass and then everybody cancels.

1766
01:28:14,360 --> 01:28:16,679
Speaker 2: Well, they lost so much. I read something they lost

1767
01:28:16,720 --> 01:28:19,960
Speaker 2: like one hundred million dollars or something even more because

1768
01:28:19,960 --> 01:28:21,519
Speaker 2: they put cool of duty on game Pass.

1769
01:28:21,920 --> 01:28:23,640
Speaker 1: Yeah, I'm sure it was genies.

1770
01:28:23,280 --> 01:28:27,320
Speaker 2: Fucking move lets it really. It's a shame as well,

1771
01:28:27,400 --> 01:28:30,360
Speaker 2: because when you get past all the horrible menus, it

1772
01:28:30,479 --> 01:28:32,559
Speaker 2: is kind of cool that you can just plug a game.

1773
01:28:32,800 --> 01:28:34,559
Speaker 2: I don't know, I've been playing PC games long enough

1774
01:28:34,600 --> 01:28:36,559
Speaker 2: that I was excited when you could just plug controller

1775
01:28:36,680 --> 01:28:38,320
Speaker 2: and it wasn't some sort of nightmare.

1776
01:28:38,560 --> 01:28:38,880
Speaker 1: Yeah.

1777
01:28:38,960 --> 01:28:41,320
Speaker 2: Yeah, though PS five controllers you still have to do

1778
01:28:41,439 --> 01:28:43,400
Speaker 2: the weird duel shock emulate a thing.

1779
01:28:43,880 --> 01:28:49,120
Speaker 3: Yeah, it's gotten a lot more accessible, but I think

1780
01:28:49,400 --> 01:28:51,400
Speaker 3: the handholds are are pretty cool.

1781
01:28:52,040 --> 01:28:56,280
Speaker 1: There's a lot of focus there. I'm not sure when

1782
01:28:56,360 --> 01:28:57,120
Speaker 1: Valve is going to do it.

1783
01:28:57,200 --> 01:28:59,879
Speaker 3: I really want them to bring Stemos to stop properly

1784
01:29:00,439 --> 01:29:04,360
Speaker 3: because it's not currently officially released for desktops, but they've

1785
01:29:04,360 --> 01:29:06,599
Speaker 3: done so much optimization work there where. Like the coolest

1786
01:29:06,680 --> 01:29:09,320
Speaker 3: thing that gets probably the least coverage outside of our

1787
01:29:09,360 --> 01:29:15,679
Speaker 3: space is they've really tuned the.

1788
01:29:14,560 --> 01:29:17,200
Speaker 1: Pacing of delivery of frames.

1789
01:29:17,280 --> 01:29:20,799
Speaker 3: So if you have sixty fps, sixty frames per second

1790
01:29:21,479 --> 01:29:24,880
Speaker 3: and it's delivered an inconsistent interval, so you have a

1791
01:29:24,960 --> 01:29:29,120
Speaker 3: frame delivered in sixteen milliseconds and then the next frame

1792
01:29:29,200 --> 01:29:32,680
Speaker 3: is delivered in one hundred milliseconds and that repeats. That's

1793
01:29:32,720 --> 01:29:36,200
Speaker 3: going to feel really bad. Despite being sixty fps averaged

1794
01:29:36,320 --> 01:29:39,000
Speaker 3: over the period, you might have some that are four milliseconds,

1795
01:29:39,000 --> 01:29:40,599
Speaker 3: some that are sixteen, some that are one hundred.

1796
01:29:40,640 --> 01:29:42,840
Speaker 2: We never thought that fps could be a marketing term,

1797
01:29:43,520 --> 01:29:45,400
Speaker 2: and now I finally, Oh Jesus, yeah.

1798
01:29:45,439 --> 01:29:49,559
Speaker 3: And so like the work they've done to optimize for

1799
01:29:49,600 --> 01:29:52,280
Speaker 3: the frame delivery is great where they sometimes have better

1800
01:29:52,320 --> 01:29:56,439
Speaker 3: frame time pacing than Windows, and I would like to

1801
01:29:56,479 --> 01:29:57,600
Speaker 3: see that come to desktop.

1802
01:29:57,800 --> 01:30:00,920
Speaker 2: So as we wrap up, what are you excited about?

1803
01:30:00,920 --> 01:30:03,840
Speaker 2: What in teke in hardware and whatever is actually like

1804
01:30:04,400 --> 01:30:05,400
Speaker 2: kind of bringing your chair.

1805
01:30:05,800 --> 01:30:11,000
Speaker 3: Yeah, I think on the DIY enthusiast side, there's still

1806
01:30:11,040 --> 01:30:13,880
Speaker 3: a lot of really cool innovation happening, especially in cases

1807
01:30:13,960 --> 01:30:17,720
Speaker 3: right now, believe it or not, like computer cases, you

1808
01:30:17,760 --> 01:30:21,080
Speaker 3: would think that it's like a pretty answered I mean

1809
01:30:21,080 --> 01:30:26,960
Speaker 3: it's it's all thermodynamics, which is well documented, right, It's

1810
01:30:26,960 --> 01:30:28,000
Speaker 3: not like stilicon.

1811
01:30:27,640 --> 01:30:31,640
Speaker 1: Engineering, but they're still there. I don't know. There's just

1812
01:30:31,680 --> 01:30:32,880
Speaker 1: a lot of improvement in.

1813
01:30:34,640 --> 01:30:37,800
Speaker 3: Getting an affordable, like good looking design that actually has

1814
01:30:37,840 --> 01:30:39,880
Speaker 3: a lot of function to it. So over the last

1815
01:30:39,880 --> 01:30:42,280
Speaker 3: six or seven years they've really switched to focus on

1816
01:30:42,360 --> 01:30:46,040
Speaker 3: coin performance and then coin performance that still looks good

1817
01:30:46,240 --> 01:30:47,840
Speaker 3: and so that's it's exciting to see that.

1818
01:30:48,320 --> 01:30:50,759
Speaker 2: And what does that edit? Does it the cases get smaller?

1819
01:30:50,800 --> 01:30:52,040
Speaker 1: Are they just they can?

1820
01:30:52,200 --> 01:30:54,600
Speaker 2: Yeah, there's better thermal management.

1821
01:30:54,240 --> 01:30:57,200
Speaker 3: Better thermals as a result of that, maybe lower noise.

1822
01:30:58,400 --> 01:31:02,040
Speaker 3: The computer just looks cooler. The smaller boxes have gotten

1823
01:31:02,040 --> 01:31:03,599
Speaker 3: a lot more viable. So if you want to build

1824
01:31:03,680 --> 01:31:06,479
Speaker 3: something that you take from I don't know, like if

1825
01:31:07,280 --> 01:31:11,360
Speaker 3: there's a kid who travels between a college dorm and

1826
01:31:11,479 --> 01:31:14,160
Speaker 3: home in the summer, you know, having like a small

1827
01:31:15,520 --> 01:31:18,200
Speaker 3: a small mini it x box is pretty appealing, and

1828
01:31:18,240 --> 01:31:19,200
Speaker 3: those have gotten really good.

1829
01:31:19,360 --> 01:31:21,960
Speaker 2: Yeah, the mani atxs are always so interesting to me.

1830
01:31:22,040 --> 01:31:23,479
Speaker 2: I love the idea of kind of like an Apple

1831
01:31:23,520 --> 01:31:26,400
Speaker 2: TV sized one. That's a pipe dream, but still.

1832
01:31:26,400 --> 01:31:27,280
Speaker 1: It's not hard to do.

1833
01:31:27,600 --> 01:31:30,519
Speaker 3: It's yeah, I mean, they've gotten easier. But the other thing,

1834
01:31:30,920 --> 01:31:33,160
Speaker 3: I think coolers are also pretty exciting right now. A

1835
01:31:33,240 --> 01:31:37,559
Speaker 3: lot of really neat technological development on the cool end

1836
01:31:37,560 --> 01:31:44,200
Speaker 3: products GPUs I think are probably the biggest hang ups

1837
01:31:44,200 --> 01:31:48,320
Speaker 3: for people where the pricing has just gotten kind of

1838
01:31:48,320 --> 01:31:52,880
Speaker 3: stupid for consumer market GPUs, and yeah, I think that

1839
01:31:52,880 --> 01:31:55,799
Speaker 3: that's the one that's kind of like kind of a bummer.

1840
01:31:55,920 --> 01:31:59,000
Speaker 2: I guess, yeah. And I mean, do you see any

1841
01:31:59,200 --> 01:32:02,519
Speaker 2: viable competitor to win video and am D at any point?

1842
01:32:02,560 --> 01:32:04,759
Speaker 2: Do you think that there's any chance of any smaller competitor.

1843
01:32:05,040 --> 01:32:08,080
Speaker 1: The only one is Intel, which I never really answered

1844
01:32:08,080 --> 01:32:09,960
Speaker 1: your question on ARC. I think right now ARC is

1845
01:32:09,960 --> 01:32:10,799
Speaker 1: going to stick around.

1846
01:32:10,880 --> 01:32:12,880
Speaker 3: But yeah, right now it only goes up to like

1847
01:32:12,880 --> 01:32:15,840
Speaker 3: two hundred and fifty dollars and after that it's all

1848
01:32:15,880 --> 01:32:20,519
Speaker 3: AMD and Nvidia and AMD. You know, part of it's

1849
01:32:20,560 --> 01:32:23,000
Speaker 3: their fault. They need to really want it and compete,

1850
01:32:23,320 --> 01:32:26,519
Speaker 3: and they just aren't. Like the products are okay, but

1851
01:32:26,600 --> 01:32:29,559
Speaker 3: they keep doing the stupidest things with their prices and

1852
01:32:29,600 --> 01:32:33,240
Speaker 3: their marketing. And I think part of it is they

1853
01:32:33,280 --> 01:32:36,160
Speaker 3: sell every epic CPU they make, so they allocate all

1854
01:32:36,160 --> 01:32:38,800
Speaker 3: the way for supply to that, and GPUs are kind

1855
01:32:38,800 --> 01:32:41,840
Speaker 3: of back burnered. But you know, the end result is

1856
01:32:41,880 --> 01:32:44,599
Speaker 3: we just end up in this stalemate we've been in forever.

1857
01:32:44,720 --> 01:32:45,880
Speaker 1: Now, what about.

1858
01:32:45,600 --> 01:32:48,800
Speaker 2: Combined GPUs and CPUs, is that is that something you're

1859
01:32:49,000 --> 01:32:51,479
Speaker 2: seeing much growth from. Do you think that that's going

1860
01:32:51,520 --> 01:32:53,160
Speaker 2: to be a focus or is that kind of just the.

1861
01:32:53,160 --> 01:32:57,920
Speaker 3: CPUs basically, yeah, yeah, yeah, I mean the the entire handheld.

1862
01:32:57,520 --> 01:32:58,120
Speaker 1: Market is that.

1863
01:32:58,320 --> 01:33:00,639
Speaker 3: Yeah, So there's a lot of success there and they're

1864
01:33:00,680 --> 01:33:04,360
Speaker 3: clearly good devices. Now for that, they're not good enough

1865
01:33:04,360 --> 01:33:09,000
Speaker 3: for like high fidelity, high resolution, high graphics quality gaming

1866
01:33:09,640 --> 01:33:13,880
Speaker 3: on a desktop, but yeah, mobile devices, they're great for

1867
01:33:14,000 --> 01:33:19,040
Speaker 3: their faults Upscalers like DLSS and FSR do make it

1868
01:33:19,080 --> 01:33:23,280
Speaker 3: more viable to run an integrated graphics solution and actually

1869
01:33:23,280 --> 01:33:28,200
Speaker 3: have a decent experience. Can't get close to a dedicated GPU,

1870
01:33:28,439 --> 01:33:32,120
Speaker 3: but they're good. They're just they're in the same spot

1871
01:33:32,160 --> 01:33:34,840
Speaker 3: they've been in for fifteen years where it's you know,

1872
01:33:34,880 --> 01:33:38,479
Speaker 3: it's it's not really a replacement for one hundred dollars.

1873
01:33:38,479 --> 01:33:39,639
Speaker 1: GPU is going to be better.

1874
01:33:39,680 --> 01:33:42,000
Speaker 2: Probably probably doesn't make enough money as well from the

1875
01:33:42,080 --> 01:33:44,080
Speaker 2: sink a bunch of R and D into it either.

1876
01:33:44,360 --> 01:33:48,000
Speaker 3: Or it becomes a problem of ballooning the die area

1877
01:33:48,600 --> 01:33:52,080
Speaker 3: because you have to allocate some amount of your silicon

1878
01:33:52,320 --> 01:33:55,880
Speaker 3: to the GPU and the CPU, and so if you

1879
01:33:55,920 --> 01:33:57,760
Speaker 3: give more to the GP to make more powerful, you're

1880
01:33:57,760 --> 01:34:00,840
Speaker 3: making your CPU weaker. And the only really way to

1881
01:34:00,880 --> 01:34:04,240
Speaker 3: solve that is to put more silicon on the products,

1882
01:34:04,280 --> 01:34:05,160
Speaker 3: which is expensive.

1883
01:34:05,400 --> 01:34:08,680
Speaker 2: So yeah, So a couple questions before we wrap up,

1884
01:34:09,000 --> 01:34:11,160
Speaker 2: who are your favorite creators at the moment, because you

1885
01:34:11,800 --> 01:34:14,840
Speaker 2: there's a there seems like a good kind of solidarity

1886
01:34:14,880 --> 01:34:16,240
Speaker 2: between them. But who do you watch?

1887
01:34:16,320 --> 01:34:21,000
Speaker 3: What do you I think historically, like going back, the

1888
01:34:21,120 --> 01:34:27,800
Speaker 3: large influences were Tech Report, Scott Wasson specifically, if I

1889
01:34:27,840 --> 01:34:29,880
Speaker 3: remember correctly, he was involved in the early days of

1890
01:34:29,880 --> 01:34:32,599
Speaker 3: ours Technico also early early days.

1891
01:34:32,800 --> 01:34:34,080
Speaker 2: Oh oh sure, I'll have to look out.

1892
01:34:34,320 --> 01:34:37,439
Speaker 3: And so Scott Wasson did a lot of excellent like

1893
01:34:38,479 --> 01:34:42,840
Speaker 3: test design work. Ryan Shrout was part of his kind

1894
01:34:42,880 --> 01:34:45,719
Speaker 3: of era and the two of them with Tom Peterson

1895
01:34:45,760 --> 01:34:47,920
Speaker 3: from Intel now worked.

1896
01:34:47,640 --> 01:34:48,519
Speaker 1: On frame time testing.

1897
01:34:48,600 --> 01:34:53,240
Speaker 3: So so their publications set the framework for modern benchmarking

1898
01:34:53,320 --> 01:34:56,320
Speaker 3: with frame times and I that was you know, I

1899
01:34:56,360 --> 01:34:59,920
Speaker 3: still reference those content pieces and in tech I think

1900
01:35:00,040 --> 01:35:03,439
Speaker 3: as well respected but has been shut down by I

1901
01:35:03,439 --> 01:35:04,879
Speaker 3: think it was Future bought them.

1902
01:35:05,360 --> 01:35:07,680
Speaker 2: Yeah yeah, I mean anyone who's worked the Future knows

1903
01:35:07,720 --> 01:35:10,680
Speaker 2: what happened, which is the Future bought them and then

1904
01:35:11,360 --> 01:35:12,439
Speaker 2: just didn't do shit with them.

1905
01:35:12,600 --> 01:35:15,240
Speaker 1: Yeah, But who do you watch right now now? For

1906
01:35:15,640 --> 01:35:17,040
Speaker 1: I like the work that.

1907
01:35:18,760 --> 01:35:23,360
Speaker 3: Jared's Tech does on laptops, So he's an excellent laptop reviewer,

1908
01:35:23,880 --> 01:35:25,040
Speaker 3: does really good work there.

1909
01:35:25,800 --> 01:35:28,400
Speaker 1: We've helped.

1910
01:35:29,800 --> 01:35:32,479
Speaker 3: Just Josh Tech, who's another laptop reviewer, with some of

1911
01:35:32,479 --> 01:35:35,320
Speaker 3: his testing methodology, and I think they've been doing good

1912
01:35:35,360 --> 01:35:38,400
Speaker 3: things to really try to advance on that. They're still like,

1913
01:35:38,479 --> 01:35:41,559
Speaker 3: relatively new to testing, but they're really trying. I think

1914
01:35:42,479 --> 01:35:46,280
Speaker 3: Jay's two cents with his recent changes to testing, He's

1915
01:35:46,320 --> 01:35:48,800
Speaker 3: really kind of put in a lot of effort to

1916
01:35:48,840 --> 01:35:52,439
Speaker 3: overhaul it. And then the hard run box guys are

1917
01:35:52,479 --> 01:35:57,000
Speaker 3: also awesome. But yeah, it's there's there's I like, hesitate

1918
01:35:57,040 --> 01:35:59,639
Speaker 3: to start naming channels because there's a lot of channels

1919
01:36:00,280 --> 01:36:02,919
Speaker 3: you know that I like or we talk to at shows,

1920
01:36:03,000 --> 01:36:04,200
Speaker 3: and I hate to leave anyone.

1921
01:36:04,360 --> 01:36:07,599
Speaker 2: Oh no, I know, I wasn't trying to single anyone else.

1922
01:36:07,680 --> 01:36:09,680
Speaker 2: It's just I think that, especially in my own work,

1923
01:36:09,720 --> 01:36:11,360
Speaker 2: I could be quite critical. So it's good to just

1924
01:36:11,479 --> 01:36:14,599
Speaker 2: focus on the things you actually like. Yeah, so as

1925
01:36:14,600 --> 01:36:17,320
Speaker 2: we wrap, what's next for game is nextus? What do

1926
01:36:17,360 --> 01:36:19,840
Speaker 2: you want to do next beyond testing? Is there a

1927
01:36:19,920 --> 01:36:21,559
Speaker 2: virtually want to move into? I know you've got the

1928
01:36:21,560 --> 01:36:22,360
Speaker 2: other channel.

1929
01:36:22,120 --> 01:36:24,479
Speaker 1: Going, yeah, yeah, I have to go to the UK

1930
01:36:24,600 --> 01:36:24,840
Speaker 1: for that.

1931
01:36:25,400 --> 01:36:27,920
Speaker 2: I'm sorry.

1932
01:36:28,200 --> 01:36:33,439
Speaker 3: Recommendations from here leave okay, don't go where the airport is.

1933
01:36:35,080 --> 01:36:38,439
Speaker 1: Yeah, yeah, I think that we.

1934
01:36:38,360 --> 01:36:42,120
Speaker 3: Have some relatively large focus on that channel, which is

1935
01:36:42,160 --> 01:36:45,160
Speaker 3: like looking at some more consumer advocacy topics on the

1936
01:36:45,200 --> 01:36:46,040
Speaker 3: test inside.

1937
01:36:46,680 --> 01:36:46,800
Speaker 1: Uh.

1938
01:36:47,439 --> 01:36:50,000
Speaker 3: The biggest thing we're doing right now is overhauling our

1939
01:36:50,760 --> 01:36:54,719
Speaker 3: gaming benchmarks. So we're working to introduce some new types

1940
01:36:54,720 --> 01:36:58,840
Speaker 3: of charts and metrics that don't exist right now in reviews,

1941
01:36:58,840 --> 01:37:04,160
Speaker 3: cold animation, error, and just trying to basically, we're taking

1942
01:37:04,160 --> 01:37:08,679
Speaker 3: a moment right now to try and find Yeah, Okay,

1943
01:37:08,720 --> 01:37:11,200
Speaker 3: we've been representing things a certain way in charge forever

1944
01:37:11,479 --> 01:37:14,920
Speaker 3: as a review community. Is there anything new here we

1945
01:37:15,000 --> 01:37:17,719
Speaker 3: can do? And that's kind of what we're trying to research.

1946
01:37:17,800 --> 01:37:19,799
Speaker 3: So that's the immediate focus.

1947
01:37:20,200 --> 01:37:22,519
Speaker 2: Well, Steve, it's been such a pleasure to come out here.

1948
01:37:22,600 --> 01:37:23,800
Speaker 2: Thank you so much for your time.

1949
01:37:24,000 --> 01:37:34,280
Speaker 5: Thanks, thank you for listening to Better Offline.

1950
01:37:34,400 --> 01:37:36,840
Speaker 2: The editor and composer of the Better Offline theme song

1951
01:37:36,920 --> 01:37:39,559
Speaker 2: is Matasowski. You can check out more of his music

1952
01:37:39,560 --> 01:37:43,240
Speaker 2: and audio projects at Matasowski dot com, M A T

1953
01:37:43,240 --> 01:37:47,680
Speaker 2: T O, s O W s ki dot com. You

1954
01:37:47,720 --> 01:37:50,240
Speaker 2: can email me at easy at Better Offline dot com,

1955
01:37:50,320 --> 01:37:52,599
Speaker 2: or visit Better offline dot com to find more podcast

1956
01:37:52,680 --> 01:37:56,000
Speaker 2: links and of course my newsletter. I also really recommend

1957
01:37:56,040 --> 01:37:57,960
Speaker 2: you go to chat dot Where's Youreed dot at to

1958
01:37:58,040 --> 01:38:00,280
Speaker 2: visit the discord, and go to aslan.

1959
01:38:00,120 --> 01:38:03,280
Speaker 5: Bet off lines check out I'll Reddit. Thank you so

1960
01:38:03,360 --> 01:38:06,800
Speaker 5: much for listening Better. Offline is a production of cool

1961
01:38:06,880 --> 01:38:07,439
Speaker 5: Zone Media.

1962
01:38:07,560 --> 01:38:10,960
Speaker 2: For more from cool Zone Media, visit our website Coolzonemedia

1963
01:38:11,000 --> 01:38:13,800
Speaker 2: dot com, or check us out on the iHeartRadio app,

1964
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Speaker 2: Apple Podcasts, or wherever you get your podcasts.