Speaker 1: Welcome to tech Stuff, a production of iHeart Podcasts and
Speaker 1: Kaleidoscope iMOS vloscan and carries out again this week. So
Speaker 1: today I'll bring you the headlines, including what Google Search
Speaker 1: sounds like and why you're out of stock Cereal may
Speaker 1: be the result of a cyber attack on today's tech
Speaker 1: support segment. Semaphor's read Albergotti casts AI companies in the
Speaker 1: Wizard of Oz.
Speaker 2: The funniest part of this whole thing, honestly, was reaching
Speaker 2: out to all of these companies and explaining to them
Speaker 2: why they are the Munchkins or the wicked Witch of
Speaker 2: the East or the West.
Speaker 1: All of that in the Weekend Tech. It's Friday, June twentieth.
Speaker 1: In summary, today's headlines are about Summary's perhaps the most
Speaker 1: ubiquitous artifact of the age of AI, and today we
Speaker 1: have two stories about AI summaries, one about a new
Speaker 1: AI feature on Google Search and the other about Wikipedia's
Speaker 1: turn away from AI. We'll start with Google. As you
Speaker 1: might know, Google has this product called Notebook LM, which
Speaker 1: allows users to feed their own research sources, PDFs, websites, spreadsheets,
Speaker 1: whatever it may be, and Notebook LM will analyze the
Speaker 1: data in all kinds of different ways. One of these
Speaker 1: ways is a quote audio overview, where users can generate
Speaker 1: this two hander deep dive podcast where a male voice
Speaker 1: and a female voice talk each other through whatever the
Speaker 1: topic at hand is. Now, Google is bringing this feature
Speaker 1: to its search results. According to Ours Technica, the feature
Speaker 1: hasn't been fully rolled out yet. Users have to opt
Speaker 1: in by going to labs dot Google dot com slash
Speaker 1: search and turning on audio overviews. There seems to be
Speaker 1: a wait list, but one of our producers was able
Speaker 1: to turn the future before news spread too far, and
Speaker 1: here's what she found in the search results. Underneath the
Speaker 1: section that says quote, people also ask, there's an oval
Speaker 1: button that says generate audio overview. When you click it,
Speaker 1: it starts working because even AI podcasts take a little
Speaker 1: bit of time to cook. So while you wait, Google
Speaker 1: tells you exactly what it's doing, which is quote, understanding
Speaker 1: the query intent, researching websites, generating transcript, and then in
Speaker 1: less than a minute, an audio player appears. So our
Speaker 1: producer searched in Google, what is two plus two? The
Speaker 1: resulting audio overview was two and a half minutes long,
Speaker 1: which already tickled her spidery senses. But before we listen
Speaker 1: to the audio, we checked out all the websites listed
Speaker 1: underneath the clip as sources. They were a Reddit thread
Speaker 1: asking why some people think two plus two equals five,
Speaker 1: a link to study dot com, a Wikipedia page for
Speaker 1: two plus two equals five, as well as a link
Speaker 1: to a TikTok meme around the question of two plus two,
Speaker 1: which I couldn't really understand, let and explain. And underneath
Speaker 1: all these links is another message quote generative AI is experimental.
Speaker 1: So here's the beginning of that two and a half
Speaker 1: minute audio overview for what's two plus two?
Speaker 2: So?
Speaker 3: What's two plus two? Seems like a no brainer, right four?
Speaker 3: End of story.
Speaker 4: Well, that's what we learn in grade school at least.
Speaker 4: But the idea that two plus two could equal something
Speaker 4: other than four pops up in some pretty interesting places,
Speaker 4: like where.
Speaker 3: I'm picturing some kind of crazy math equation.
Speaker 4: Now it's less about complex math and more about, shall
Speaker 4: we say, bending reality a little.
Speaker 1: The podcast has then launched into a discussion of instances
Speaker 1: where some people might say two plus two equals five,
Speaker 1: like in All Wells dystopian novel nineteen eighty four, in
Speaker 1: which he ponders a totalitarian government that might insist two
Speaker 1: plus two equals five. It also includes a joke about
Speaker 1: it mathematician, an engineer, and a lawyer answering two plus
Speaker 1: two questions two plus two will always before that. The
Speaker 1: AI podcast hosts had this to say in conclusion, it's.
Speaker 3: Kind of mind bending when you think about it. This
Speaker 3: simple little equation can represent so much more than just
Speaker 3: basic addition.
Speaker 4: It really does. It's a reminder to question things, to
Speaker 4: consider different viewpoints, and to be aware of how easily
Speaker 4: fax can be twisted or manipulated.
Speaker 1: My personal view is that the notebook LM product can
Speaker 1: be pretty great if you want to bring a bunch
Speaker 1: of your own narrowly bounded set of data or research
Speaker 1: into one place and then here it played back to
Speaker 1: you in podcast form. More power to you. The last
Speaker 1: time I use it myself was over the holidays when
Speaker 1: I was going to go and see the Nutcracker Ballet,
Speaker 1: and I kind of wanted to know what to expect
Speaker 1: so that I'd be able to enjoy it more. And
Speaker 1: I've fed Notebook LM the Wikipedia page about the Nutcracker,
Speaker 1: some reviews, some other information, and it summarized all of
Speaker 1: that and turn it into a ten minute podcast which
Speaker 1: I listen to on the way to the ballet, and
Speaker 1: I honestly think that gave me a better enjoyment of
Speaker 1: the ballet because I knew the context, but I wouldn't
Speaker 1: have actually done the work myself of reading all the materials.
Speaker 1: So that was kind of a cool use case. That said,
Speaker 1: I don't think when I search for something like what's
Speaker 1: two plus two, I need a audio conversational summary of
Speaker 1: the randomness of the Internet. It just doesn't really seem
Speaker 1: very relevant, and it seems more than anything like a
Speaker 1: solution in search of a problem, which brings us to
Speaker 1: our next story. There's another Internet titan that tried out
Speaker 1: an AI feature recently. Wikipedia. On June second, the organization
Speaker 1: that hosts and maintains Wikipedia, called the Wikimedia Foundation, announced
Speaker 1: it would run an experiment with AI. The project, called
Speaker 1: Simple Article Summaries, would provide AI writeups at the top
Speaker 1: of Wikipedia entries. It was an attempt to make the
Speaker 1: denser Wikipedia articles more accessible, and the experiment was set
Speaker 1: to last two weeks, with summaries generated by an NLM
Speaker 1: called Aya by Coheer. Then came the criticism. According to
Speaker 1: a form media, the announcement was met with replies from
Speaker 1: Wikipedia editors who warned that AI summaries were a very
Speaker 1: bad idea. One editor pointed out that AI's ability to
Speaker 1: get things wrong could damage the platform's reputation, which is
Speaker 1: something that editors and the organization have worked very hard
Speaker 1: on for a very long time. Another editor said quote,
Speaker 1: just because Google has rolled out it's AI summaries doesn't
Speaker 1: mean we need to one up them. Some even threatened
Speaker 1: to quit if Wikipedia didn't roll back the summaries. And
Speaker 1: here's the thing. Wikipedia relies on its editor's passion for
Speaker 1: the website to keep this participatory encyclopedia running. So after
Speaker 1: the editor upraw and just a day after the announcement
Speaker 1: of the experiment, Wikimedia said they would pause it, but
Speaker 1: that they were also still interested in AI summaries. It's
Speaker 1: not clear when they might try them out again, but
Speaker 1: it is clear how human editors feel about them. I'm
Speaker 1: not somebody who's implacably opposed to AI summaries. In fact,
Speaker 1: I use them myself. But what was really important to
Speaker 1: remember is that AI summaries rely on the input of
Speaker 1: human work and ingenuity, and with that in mind, I
Speaker 1: read this article in the financial time that I wanted
Speaker 1: to share. It had the headline AI alone cannot solve
Speaker 1: the productivity problem, and it talks about something I had
Speaker 1: no idea about, which is the average scientist today produces
Speaker 1: fewer breakthrough ideas per dollar spent than their counterpart in
Speaker 1: the sixties, and that despite all the headlines about progress,
Speaker 1: progress is actually becoming more incremental. And here's the part
Speaker 1: of the article that really got me thinking. Quote, had
Speaker 1: the nineteenth century focused solely on better looms and plows,
Speaker 1: we would enjoy cheap cloth and abundant grain, but there
Speaker 1: would be no antibiotics, jet engines, or rockets. Economic miracles
Speaker 1: stem from discovery, not repeating tasks at greater speed. The
Speaker 1: article went on to make the point that large language
Speaker 1: models gravitate towards statistical consensus. So think about it. If
Speaker 1: there were NLMs back before the Wright Brothers, all the
Speaker 1: data that the model was trained on would have suggested
Speaker 1: that human flight was absolutely impossible. Wikipedia is not going
Speaker 1: to solve the larger problem of fostering human ingenuity in
Speaker 1: an age of statistical consensus, But at least for now,
Speaker 1: you can rest assured that the articles you read on
Speaker 1: it will be written and driven and created by humans.
Speaker 1: I've got a couple more headlines for you, including why
Speaker 1: you might be struggling to get your favorite box of cereal.
Speaker 1: Tech Crunch reports that some grocery stores are reeling from
Speaker 1: the effects of a cyber attack. United Natural Foods or UNFI,
Speaker 1: is a large food distribution company that provide it's fresh
Speaker 1: produce and products to over thirty thousand stores across the US.
Speaker 1: Whole Foods uses the company as its primary distributor. Earlier
Speaker 1: this month, UNFI experienced a cyber attack that caused them
Speaker 1: to shut down their electronic ordering systems. The system is
Speaker 1: now back online after more than ten days, but grocery
Speaker 1: stores are still waiting on some of their stock. And
Speaker 1: this isn't just an issue in the US. Cyber attacks
Speaker 1: are also roiling UK supermarkets. The thing is, grocery chains
Speaker 1: are a prime target for hackers because they have these large,
Speaker 1: interconnected supply chains, which by definition have multiple failure points.
Speaker 1: They also have treasure trows with customer data, and of course,
Speaker 1: when shoppers can't get what they want at the store,
Speaker 1: angst and headlines are sure to follow. Finally, for today's headlines,
Speaker 1: ads are a huge business for social media platforms, and
Speaker 1: TikTok is aiming to lower the cost of production for
Speaker 1: its partners. According to The Verge, TikTok is adding new
Speaker 1: capabilities to give advertisers the ability to upload images and
Speaker 1: give text prompts that can then be used to generate
Speaker 1: video advertisements. The videos can include virtual avatars holding or
Speaker 1: modeling different products, just like an influencer mine for brands
Speaker 1: that they partner with. TikTok has said that all this
Speaker 1: content generated using AI will be labeled as such and
Speaker 1: will go through quote multiple rounds of safety review. The
Speaker 1: biggest story is that influencer marketing transformed the ad industry
Speaker 1: over the last decade, and it will be interesting to
Speaker 1: see what AI influencers can actually do because, unlike say,
Speaker 1: fashion models, whose job it is to show what products
Speaker 1: will look like when they're worn, influencers have thrived when
Speaker 1: they make a case for a product based on their
Speaker 1: personal experience. After the break, we bring you a production
Speaker 1: of The Wizard of Oz starring your favorite tech giants.
Speaker 1: Stay with us on this show. We've talked about tech
Speaker 1: upstarts like open ai and its model, chatchipt Anthropic and
Speaker 1: its model, Clawed at Length, and We've also talked about
Speaker 1: the numerous tech giants racing to gain or defend market
Speaker 1: share with AI products of their own, including Meta, Google, Apple, Amazon,
Speaker 1: and Microsoft. It's a crowded field, but also an open
Speaker 1: one in terms of knowing who will ultimately prevail, and
Speaker 1: it can get quite dramatic their acquisitions, partnerships to get
Speaker 1: contentious legal fights and hedge rolling at big tech companies
Speaker 1: as they fight to stay in the game, and recently
Speaker 1: there have been some big AI power moves. Meta has
Speaker 1: just made its largest investments since acquiring WhatsApp, putting fourteen
Speaker 1: billion dollars into a company called Scale Ai. So we
Speaker 1: thought it'd be helpful to outline them many players the air,
Speaker 1: current positions, and what might be on the horizon. And
Speaker 1: here to walk us all through it is read Albagotti,
Speaker 1: who's the tech editor Sema fool Read Welcome to tech Stuff.
Speaker 2: Thanks for having me. Good to be here.
Speaker 1: You came up with a very creative paradigm for helping
Speaker 1: your readers make sense of all the different players in
Speaker 1: the AI race. Tell us a little bit about it.
Speaker 2: Well, it all started because, like you said, I mean,
Speaker 2: there's this this huge race, and I was sort of
Speaker 2: going back and forth with my colleague Rachel Jones, talking
Speaker 2: about Okay, so like, what are the lanes that these
Speaker 2: companies are starting to take and how do we sort
Speaker 2: of define that? And I'm sort of writing this thing
Speaker 2: and it's kind of it's a little dry, it's a
Speaker 2: little heavy on the analysis, and Rachel's like, why don't
Speaker 2: we just make them Wizard of Oz characters? And I
Speaker 2: was like, that's a terrible idea. But then I thought
Speaker 2: more about it, and I thought, that's actually kind of
Speaker 2: a great idea. So you know, we decided to try
Speaker 2: to fit you know, each of the biggest players that
Speaker 2: we see in the field into these characters and the
Speaker 2: Wizard of Oz and sort of explain why. And I think, look,
Speaker 2: I mean the funniest part of this whole thing, honestly,
Speaker 2: was was reaching out to all of these companies and
Speaker 2: explaining to them why they are the Munchkins or the
Speaker 2: Wicked Witch of the East or the West, and you know,
Speaker 2: getting their responses and I thought, you know, actually, kind
Speaker 2: I kind of like this because the best part was
Speaker 2: when I got pushed back from these companies, right like,
Speaker 2: we are we are not this, we are this character
Speaker 2: just like, oh, actually I'm getting an insight now into
Speaker 2: like how you see yourself as a company. And so
Speaker 2: what I kind of hoped was, like, you know, we
Speaker 2: would this was like people would write in and say
Speaker 2: you're a complete idiot, like open Aye is not Dorothy,
Speaker 2: They're you know, the tin man or something like that.
Speaker 2: Just get people talking about what are the lanes here
Speaker 2: and how and how should we think about these these players.
Speaker 1: But that said, you did cast open Aiye as Dorothy.
Speaker 1: Why was that?
Speaker 2: Well, you know, Dorothy is is kind of the main character. Right.
Speaker 2: They are the Kleenex of chat bots, so to speak.
Speaker 2: They're the winner take all sort of consumer chat bot.
Speaker 2: They get all the press, but you know, at the
Speaker 2: same time, they require a lot of other you know,
Speaker 2: players in this space to make it possible. Right, So
Speaker 2: you know they they've borrowed technology from Google, right, you know,
Speaker 2: they're using the data centers or at Microsoft for such
Speaker 2: a huge part of that. So it's this supporting cast
Speaker 2: that kind of really makes them who they are. I think,
Speaker 2: so that was that was the justification there. Do you
Speaker 2: agree or do you want to do you want to
Speaker 2: fight me on that?
Speaker 1: Well, I think I'll you've thought about this more than
Speaker 1: I have. But I think I agree with you that
Speaker 1: despite my name, I think that I agree with you
Speaker 1: that that that opening I definitely has the main character
Speaker 1: energy in this story. But I have to ask you
Speaker 1: about her cost of supporting characters the tin man, the
Speaker 1: cowardly line, and the scarecrow. How do you assign each
Speaker 1: of these crucial pots?
Speaker 2: Well, okay, so let's start with Let's start with with Google,
Speaker 2: the cowardly lion. Google has, you know, all this power, right,
Speaker 2: They've developed this technology for years. You know, the attention
Speaker 2: is all you need paper, right like that. That's what
Speaker 2: really laid the groundwork for CHATCHYPT. But they kind of
Speaker 2: sat on it. And I think a lot of that
Speaker 2: was out of fear. You know, these chatbots go off
Speaker 2: the rails. They're crazy, Like, what are people going to
Speaker 2: say if we just start releasing this stuff into the wild.
Speaker 2: And so they didn't and they got beat right, chatchapt
Speaker 2: came out. Google has had to completely reorient itself around
Speaker 2: this race now.
Speaker 1: So what you're saying is is Google could have had
Speaker 1: market leadership here, and because of fears about cultural blowback
Speaker 1: or erosion of that cool business, they basically sat on
Speaker 1: the technology.
Speaker 2: Yeah, that's very well said. They're a big public company.
Speaker 2: They have to be sort of cautious, and you know,
Speaker 2: I think that's somewhat in there, has become part of
Speaker 2: their DNA. But they've had to get really bold, right
Speaker 2: and they started to release new products. The notebook LM
Speaker 2: is one of the big successes. They're throwing more spaghetti
Speaker 2: against the wall. They're finding that they actually do have courage, right,
Speaker 2: which you know, of course, if you've watched The Wizard
Speaker 2: of Oz, you know in the end they all kind
Speaker 2: of have the thing they thought they were missing. So
Speaker 2: you know, tin Man is Microsoft this well oiled machine.
Speaker 2: If you remember the tin Man was always putting oil
Speaker 2: and oil can. They seem a bit rigid, right, but
Speaker 2: in the end, like they kind of do have a heart.
Speaker 2: I mean I think they I had an interview with
Speaker 2: Satia Nadella recently and and Kevin Scott, the CTO, that
Speaker 2: it's really clear they really do want to sort of
Speaker 2: like enable these developers. I think they have sort of
Speaker 2: a I think a less ego, a bit more of
Speaker 2: a selfless kind of attitude around this stuff. They're building
Speaker 2: the infrastructure for this industry and letting others kind of
Speaker 2: use their creativity to benefit, so they really do have
Speaker 2: a heart in the end. And then I think Amazon,
Speaker 2: you know, this the scarecrow, right, no, no brain. When
Speaker 2: I think about the beginning of this race, you know,
Speaker 2: much like Google, people were really putting Amazon down and
Speaker 2: they thought, oh my god, they've completely missed this, like
Speaker 2: Amazon's got nothing here, and totally ignored the fact that
Speaker 2: actually they had been thinking about this for years. And
Speaker 2: even though you know, maybe they're sort of fighting for
Speaker 2: market share in this new AI race, I think they're
Speaker 2: pretty well positioned to profit from the growth and you know,
Speaker 2: just the the market demand for tokens for compute.
Speaker 1: Are they the market leaders in data centers Amazon today?
Speaker 2: Oh yeah, I mean for sure in the in the cloud,
Speaker 2: in the cloud business. And I think that the question
Speaker 2: though is, you know, can they remain the market leader
Speaker 2: in the AI you know era right, they've been the
Speaker 2: market leader in cloud in terms of just you know,
Speaker 2: normal compute AI data centers is it's a whole new ballgame.
Speaker 2: AI runs on what we would call a GPU, right,
Speaker 2: and so everyone is now you know, racing to add
Speaker 2: these GPUs or build new data centers that are built
Speaker 2: around these GPUs and it's a totally different business model
Speaker 2: and concept, so it kind of restarts the race in
Speaker 2: some ways.
Speaker 1: Okay, so we got Open Air as Dorothy, Microsoft as
Speaker 1: the tin Man, Google's the cowardly line, Amazon is the scarecrow.
Speaker 1: There are also some wizards and witches who need to
Speaker 1: be accounted for Glinda, the Wicked Witch of the West,
Speaker 1: and of course my namesake, the Wizard of Oz. Who's
Speaker 1: who in this cost.
Speaker 2: So let's start with Perplexity being, you know, the wicked Witch.
Speaker 2: As we found in Wicked. You know this, this witch
Speaker 2: was kind of misunderstood, and I think that's sort of
Speaker 2: how Perplexity became the absolute villain, especially in the media industry,
Speaker 2: because they, you know, were were I guess, republishing almost
Speaker 2: like articles without proper citation. I think they very quickly
Speaker 2: changed I mean, it wasn't a policy. I think it
Speaker 2: was a mistake and they very quickly changed them. And
Speaker 2: they're actually have all these media deals where there are
Speaker 2: revenue sharing agreements between Perplexity and the media companies. And
Speaker 2: I think that Wicked image is starting to fade a
Speaker 2: little bit from Perplexity. So I put them in the
Speaker 2: role of the Wicked Witch, and Arvin strinovas the CEO Perplexity,
Speaker 2: responded to me on Twitter with a I think AI
Speaker 2: generated repurposing of the song from Wicked.
Speaker 1: I've got the final close my eyes and leap. It's
Speaker 1: time to try to find Google. I think I'll try
Speaker 1: to find Google and you comple me down.
Speaker 2: Right, So they're disrupting Google. Therefore they're they're really the
Speaker 2: good guys. So you know that was I thought that
Speaker 2: was fun. That was a fun response from Arvind. I think,
Speaker 2: you know, we put Apple as the role of Glinda,
Speaker 2: the good Witch, who you know sort of over over
Speaker 2: promises and underdelivers. I think that's sort of the you know,
Speaker 2: using a little bit of the old and the new
Speaker 2: Wicked version of that that character. Obviously, you know, that's
Speaker 2: based on the fact that they, you know, they had
Speaker 2: this huge event where they promised the world around you know, AI,
Speaker 2: they were going to do these amazing things with Siri
Speaker 2: and your phone, and it turns out, oh, they hadn't
Speaker 2: actually really built any of this, and it's not clear
Speaker 2: that they can.
Speaker 1: And what what's your reporting suggests? Why has it been
Speaker 1: such a bust?
Speaker 2: I think that was a train wreck that anybody who's
Speaker 2: been following Apple has kind of seen for a long
Speaker 2: time because they just have ignored AI and you don't
Speaker 2: see the Apple people are not really like mixing with
Speaker 2: the rest of Silicon Valley, and I think they just
Speaker 2: didn't quite understand this whole AI thing. And and I've
Speaker 2: also written that, you know, I this is a bit
Speaker 2: this is kind of my view, and I don't know,
Speaker 2: I haven't heard that any people agree with me on this,
Speaker 2: but I think they also, you know, because they position
Speaker 2: themselves as this privacy focused company, they that they also
Speaker 2: shied away from AI there because it does require gathering
Speaker 2: a lot of data right on people and personalizing things
Speaker 2: in ways that make people maybe feel like, oh, I'm
Speaker 2: being tracked or what have you. And it turns out
Speaker 2: that that's you know, that's now everything in the tech industry,
Speaker 2: and they're they're way behind.
Speaker 1: And then of course the Wizard, just by having a
Speaker 1: movie named after him, is actually no very important character.
Speaker 2: Right exactly. So I cast x Ai in the in
Speaker 2: the role of the Wizard. You know, I think x
Speaker 2: Ai has this huge, you know, colossus data center, right,
Speaker 2: and they've they've promised that, you know, it really kind
Speaker 2: of made me think of them as that is the
Speaker 2: fact that they're going to understand the secrets of the
Speaker 2: universe with AI that theirs is the Is that literally?
Speaker 4: Yeah?
Speaker 2: I mean this is like literally, you know. I mean
Speaker 2: I saw Elon Musk in a recent interview saying that
Speaker 2: their model grock is based on basic physics and that's
Speaker 2: where it gets its ground truth from. And so you know,
Speaker 2: their effort is to actually ultimately figure out, like, you know,
Speaker 2: a unifying theory of the universe. You know, I think
Speaker 2: that's a lot of it. It remains to be seen
Speaker 2: what's behind the curtain. There.
Speaker 1: Two other companies we haven't spoken about yet are Meta
Speaker 1: and Anthropy. Where do they fit in?
Speaker 2: Yeah, well so Anthropic I cast as in the role
Speaker 2: of the Munchkins. I felt a little bad doing that
Speaker 2: because you know, I think there's the Munchkins have this
Speaker 2: negative connotation. But actually I was reading about it and
Speaker 2: researching this article, reading about the Wizard of Oz and
Speaker 2: trying to understand the different characters on a more nuanced level.
Speaker 2: And without the Munchkins, there is no Wizard of Oz. Right.
Speaker 2: They they they're the people, They're the ones who populate
Speaker 2: this universe, right, And I think I think what Anthropic
Speaker 2: is doing, and I think a lot of people don't
Speaker 2: really realize this, is they have become the de facto
Speaker 2: coding model for AI, and that is really what's driving
Speaker 2: all this, you know, the excitement and AI right now,
Speaker 2: it's not so much chat GPT, even though I think
Speaker 2: that's what the broad population sort of thinks of. But
Speaker 2: in the tech industry, what I think really excites people
Speaker 2: is that this stuff, even if it never advances beyond
Speaker 2: just being able to generate code with AI, that's going
Speaker 2: to completely change the world because you know, code is
Speaker 2: already so powerful and can automate so many things. The
Speaker 2: reason that the whole world isn't running on code is
Speaker 2: that it's too expensive, and so Anthropic is kind of
Speaker 2: like bringing that power to the people.
Speaker 1: So when I read about vibe coding, though I read
Speaker 1: about CUSS or AI and stuff, But you're saying that
Speaker 1: Anthropic is a real big player in the world of
Speaker 1: vibe coding.
Speaker 2: Well, yeah, I mean Cursor is running on Anthropics code
Speaker 2: generation model, and so is Replet and you know a
Speaker 2: lot of others.
Speaker 1: I mean, it's Anthropic, it's really underpending this vibe coding
Speaker 1: revolution exactly what about Meta. It's a big week for them.
Speaker 1: I think you cost them in the in the movie
Speaker 1: before their then news announcement, But who are they and
Speaker 1: the Wizard of Alls? And did they did the news
Speaker 1: announcement change you're thinking at all?
Speaker 2: Well, of course, of course I'm going to make an
Speaker 2: argument that it didn't change my thinking.
Speaker 1: But I would I would.
Speaker 2: Encourage people to totally disagree with me and argue with
Speaker 2: me on this. But no, I mean Meta I cast
Speaker 2: as the yellow brick road. They're they're open sourcing these
Speaker 2: AI models, and similar to to Anthropic where it's like that,
Speaker 2: it's an amplified effect. Many companies are using Meta models,
Speaker 2: these Lama family of models to run their own custom
Speaker 2: software because you know, it's free and it could also
Speaker 2: be fine tuned, it can be run locally, so it's
Speaker 2: actually you know, having this big impact that a lot
Speaker 2: of people don't really see. And then of course this
Speaker 2: recent acquisition of Scale AI.
Speaker 1: You know, we'll see whether or how does that You
Speaker 1: don't talk about the.
Speaker 2: Yeah, you're right, I called it an acquisition, and it's not.
Speaker 2: I mean, it's a it's a forty nine percent of
Speaker 2: the company takeover, but not an actual takeover and and
Speaker 2: yes it's not an acquisition, but really kind of puts
Speaker 2: them in. The CEO, the co founder and CEO of
Speaker 2: Scale AI is now going to go work at Meta,
Speaker 2: but Scale will still continue as an independent company. What
Speaker 2: I think Meta is interested in them for is their
Speaker 2: ability to generate a lot of data, you know, to
Speaker 2: train these models. So you know, these AI models trained
Speaker 2: on the entire Internet. I'm sure you've kind of heard
Speaker 2: these people say that they sucked in all the data
Speaker 2: and the entire Internet and train on it. Well that's
Speaker 2: somewhat true. There are these huge databases that are free
Speaker 2: that anybody can train on, and they've sort of tapped
Speaker 2: that up, like using that data can has sort of
Speaker 2: They've gotten as far as they can with that, and
Speaker 2: now they have to generate more data and it's getting
Speaker 2: very expensive. And so companies like Scale have these huge
Speaker 2: networks of contractors who can generate a ton of data.
Speaker 2: And it's actually like PhDs and like you know, high
Speaker 2: level business executives who are doing this I think kind
Speaker 2: of for fun. I mean they're getting paid, but they
Speaker 2: sit there and they do like very complex stuff that
Speaker 2: can then be used by these models to learn and
Speaker 2: become much more you know, specialized in certain areas. And
Speaker 2: part of the deal with Meta is that Meta has
Speaker 2: sort of pre paid for a bunch of Scale services
Speaker 2: to get this data.
Speaker 1: So this is really giving itself a competitive edge. The
Speaker 1: New York Times ran a story saying though that this
Speaker 1: was like part of socker Bug's personal quest to build
Speaker 1: a super intelligence lab. So I wasn't sure how to
Speaker 1: balance that with Yeah, what I'd understood about Scale was
Speaker 1: that it was a company that sort of specialized in
Speaker 1: creating this very high value data that's not available organically.
Speaker 2: This is sort of my my take on this. I mean,
Speaker 2: it's easy to focus on, you know, the Scale CEO,
Speaker 2: Alexander Wang is going to run it, and it's all
Speaker 2: this talent. I mean, Wang is not an AI researcher.
Speaker 2: He knows a lot about the AI industry and he's
Speaker 2: one of the world's most experts on you know, data
Speaker 2: being used in AI. He was roommates with Sam Altman
Speaker 2: when basically the groundwork for chatch ept was being built,
Speaker 2: and that sort of brought him in. I mean, he
Speaker 2: didn't and I've listened to interviews with him where he said,
Speaker 2: like he didn't really understand what Opening Eye was doing,
Speaker 2: but it was clearly like this great opportunity and so yeah,
Speaker 2: I mean that help them with recruiting, and it's it's great,
Speaker 2: you know, it's great for marketing and it all, it
Speaker 2: all helps. But I think the bread and butter of
Speaker 2: that deal is really about Metas saying, well, Okay, we
Speaker 2: might not be the most cutting edge AI company right now,
Speaker 2: but we're putting a lot of money into having the
Speaker 2: best data.
Speaker 1: Read this the question that is normally a cache, but
Speaker 1: in this case, I think it's appropriate. How did this
Speaker 1: movie end?
Speaker 2: Well, they all get to the Emerald City, which is Agi,
Speaker 2: and it was all set in motion by this tornado
Speaker 2: which is chatchbt. No, I don't think we know this
Speaker 2: one hasn't This one hasn't ended yet. I think it's
Speaker 2: I think there are many alternate endings, just like all
Speaker 2: the Wicked and and and probably other fan fiction around
Speaker 2: the Wizard of Oz.
Speaker 1: But if you look looking at the landscape, maybe you
Speaker 1: had to bet on you had to bet on one company.
Speaker 1: I mean, who do you think is really positioning themselves
Speaker 1: in the smallest way for this immediate future of AI.
Speaker 2: Yeah, if you had to bet on one company that's
Speaker 2: a that is a really that's a tough one. I mean,
Speaker 2: because you know, I don't think this is a winner
Speaker 2: take all race either. I think that if you look
Speaker 2: at the compute layer, I mean, this is a growing
Speaker 2: pie that will be divided up. I mean, Opening Eye
Speaker 2: might be winner take all in the consumer chat bots space.
Speaker 2: I could see them becoming sort of the Google of
Speaker 2: of of that era. But you know, I look at
Speaker 2: Google right now and I think they have there. It's
Speaker 2: interesting because I think, on the one hand, they have
Speaker 2: so much promise. I mean, they have the best models
Speaker 2: right now, they're applying them in the most diverse ways,
Speaker 2: right they have because one is waymo right. They have robotaxis,
Speaker 2: which are probably ultimately just gonna run on Gemini at
Speaker 2: some point in the future. They they're doing stuff in
Speaker 2: other you know, humanoid robotics as well. But they've also
Speaker 2: got these, you know, they've got their own consumer chat bots,
Speaker 2: They've got you know, a lot of consumer distribution in
Speaker 2: the software space. So I think they're very they're set
Speaker 2: up for success. The interesting part though, is that their
Speaker 2: core business of search advertising is also It's like, it's
Speaker 2: not even just that it's under threat, but like the
Speaker 2: whole the whole concept of of like the Internet economy
Speaker 2: running off of advertising dollars is up in the air,
Speaker 2: like we don't even know if that's the future. So
Speaker 2: they're challenged and they're having to completely change, like reorient
Speaker 2: themselves as a company. But at the same time, they
Speaker 2: have such promise, so I don't know, I mean, it
Speaker 2: would be sort of it's sort of like a gamble
Speaker 2: to put money on anything. But I mean, I think
Speaker 2: they're just very well positioned. I think them in open AI,
Speaker 2: I mean open a eye, just what they've built is
Speaker 2: so is so valuable, and not because of their models,
Speaker 2: not because they have the best AI, but because they're
Speaker 2: just they've they've become this consumer products now and that
Speaker 2: is we've seen in history that like that is something
Speaker 2: that you know just will be hugely valuable in the
Speaker 2: long run. It's kind of like their game to lose there.
Speaker 1: On that note, read, thank you so much for your time,
Speaker 1: Thank you so much.
Speaker 2: It was great.
Speaker 1: That's it for this week for tech stuff. I'mos Voloshin.
Speaker 1: This episode was produced by Eliza Dennis and Victoria Domingez.
Speaker 1: It was executive produced by me Karen Price and Kate
Speaker 1: Osborne for Kaleidoscope and Katrina Norvel for iHeart Podcasts. But
Speaker 1: he Fraser is our engineer. Jack Insley makes this episode
Speaker 1: and Kyle Murdoch wrote our theme song. Join us next
Speaker 1: Wednesday for text Stuff the Story, when we'll share an
Speaker 1: in depth conversation with Yasmin Green, the CEO of Jigsaw,
Speaker 1: about the tech that could change town halls forever. Please rate, review,
Speaker 1: and reach out to us at Tech Staff Podcast at
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