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Speaker 1: Also media welcome back to It could happen here, a

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Speaker 1: podcast about things falling apart, and sometimes about stuff that's

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Speaker 1: less depressing than that.

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Speaker 2: Today we're doing an episode that's I don't know, part

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Speaker 2: funny and part hey, you should be aware of this

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Speaker 2: thing because it's it's kind of fucked up.

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Speaker 3: It certainly could happen. It probably shouldn't. It probably shouldn't

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Speaker 3: happen here, but it certainly could.

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Speaker 2: But it certainly could. Garrison Davis is on the other line.

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Speaker 2: That I mean other line. This isn't a phone call.

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Speaker 2: That's the other voice that you are hearing right now.

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Speaker 2: And earlier this year, Garrison and I went to CEES,

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Speaker 2: the Consumer Electronics show in Las Vegas, Nevada, where Garrison

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Speaker 2: had a wonderful stay at Circus Circus that did not

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Speaker 2: smell like dead clowns.

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Speaker 3: But we weasly did not just shut down this summer

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Speaker 3: due to horrible infestation problems.

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Speaker 2: Oh that's what you're staying next year too, buddy. Anyway,

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Speaker 2: we encountered while we were going through all these different

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Speaker 2: technology companies and whatnot, this very peculiar AI project, and Garrison,

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Speaker 2: I'm going to hand things over to you now because

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Speaker 2: you're the one who was actually prepared an episode.

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Speaker 3: Yeah, So I dug into this AI project more when

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Speaker 3: I was making my ghost Conference episodes, and after just

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Speaker 3: a few minutes of like doing like background checks and stuff,

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Speaker 3: I realized that this would become its own episode because

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Speaker 3: of how wild things got very very quickly. This company

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Speaker 3: is called mind Bank AI. As the name suggests, they

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Speaker 3: are an AI company based in Florida with the goal

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Speaker 3: of creating personal digital replicas of living humans using artificial

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Speaker 3: intelligence and an evolved n LP or natural language processing.

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Speaker 2: Yeah. Basically, these are.

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Speaker 3: Algorithms that are used by GPT, chatbots, predictive texting, and

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Speaker 3: the digital assistance like Alexa and Siri. Yeah, language models

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Speaker 3: that respond to feedback. They're pretty common these days. We

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Speaker 3: encounter them a lot, right that they're whenever you're typing

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Speaker 3: on your iPhone, they they will generate text that they

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Speaker 3: think you're gonna write. But what mind bank is trying

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Speaker 3: to do is a little bit different.

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Speaker 4: Yeah.

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Speaker 2: When we encounter them at Cees, their booth had on

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Speaker 2: these signs that were it was stuff like like, you know,

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Speaker 2: set up a legacy for your kids. You know, it

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Speaker 2: was basically advertising. This is a way to allow a

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Speaker 2: part of you to exist in digital form and communicate

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Speaker 2: with your with your descendants forever.

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Speaker 3: Yes, so we found them in the US government sponsored

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Speaker 3: section of cees, which is already a great sign. Yes,

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Speaker 3: already already looking good. But unlike other kind of AI

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Speaker 3: digital copies of humans, which typically are just language models

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Speaker 3: that generate responses based on an archive of someone's writing

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Speaker 3: or recorded interviews or online presence, mind Bank instead seeks

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Speaker 3: to create an evolving, a unique digital twin by having

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Speaker 3: a person input their personal data basically tons of personal

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Speaker 3: information about themselves into an AI on an ongoing basis,

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Speaker 3: and by analyzing your data inputs. Mind Bank says that

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Speaker 3: your digital twin will quote unquote learn to think like you,

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Speaker 3: and their CEO claims that this process will eventually help

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Speaker 3: him achieve immortality.

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Speaker 2: Oh oh, that's good. I hadn't caught that when we

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Speaker 2: talked to the guy that he believed that that I love.

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Speaker 2: Whenever you get these guys who are like I will

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Speaker 2: just offload my brain onto a machine and then I

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Speaker 2: will live for ever in the cloud. And of course, man, yeah,

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Speaker 2: that's how consciousness works. Absolutely, buddy.

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Speaker 3: All right, I'm going to play this video next.

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Speaker 5: Humanity is limited. Our bodies age, our memories fade. Technology

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Speaker 5: outpaces evolution. The solution is your personal digital twin, transfer

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Speaker 5: your wisdom, become the best version of yourself, and live

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Speaker 5: forever through data.

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Speaker 3: Oh boy, let's go beyond.

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Speaker 2: So all right, I gotta know one thing before you

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Speaker 2: start in Garrison, which is that when they note mentioned

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Speaker 2: that like technology, like there's a line about like technology

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Speaker 2: making everything better, they're showing a man who has lost

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Speaker 2: his leg walking on a treadmill with an artificial leg.

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Speaker 2: And look, I think I have so much admiration for

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Speaker 2: the people who make artific official limbs wonderful thing to

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Speaker 2: be doing great important work. They're not as good as

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Speaker 2: real legs. Everyone agrees with this, right, Technology is not

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Speaker 2: making it better. Yeah, that's what it says. She was

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Speaker 2: on the No, that's technology allowing someone to adapt to

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Speaker 2: a terrible, terrible thing that happened to them.

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Speaker 3: But Robert, don't you want to live forever through data?

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Speaker 2: No? No, I don't. I'm exhausted now, Garrison.

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Speaker 3: Okay, all right, so let's go into this a little

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Speaker 3: bit more. Your immortal digital twin is made possible quote

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Speaker 3: by safely storing your data over the years, artificial intelligence

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Speaker 3: and computers of the future will have ample data to

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Speaker 3: compile a digital version of yourself and predict your responses.

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Speaker 3: So that that is their idea of how this thing works.

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Speaker 3: Another one of their very very funny YouTube videos, titled

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Speaker 3: The Vision, promises that quote, the next personal computer is

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Speaker 3: you store your memories, your infinite potential, take advantage of

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Speaker 3: AI enhanced humanity.

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Speaker 2: God damn it.

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Speaker 3: So that is their vision.

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Speaker 2: My personal computer absolutely is not me because I do

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Speaker 2: not play Balderskate three very well, you know, like I

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Speaker 2: can't run it on my hardware.

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Speaker 3: Well, that's that's why it's that's why you got to

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Speaker 3: buy the new Monster manual and then maybe it could

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Speaker 3: all just be in your brain.

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Speaker 2: Actually, yeah, I am full of shit. D and D

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Speaker 2: is still better when you run hardware. Goddamn, this is the.

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Speaker 3: One thing you actually can do pretty good by yourself.

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Speaker 2: Why did I pick that one? Yeah, it's just so like,

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Speaker 2: I don't think most people buy this. I don't think

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Speaker 2: this probably is going to be a success. I don't

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Speaker 2: think most people. I think most people's reaction to this

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Speaker 2: is like kind of sneering, which is the right reaction. This, Yes,

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Speaker 2: but there are people who do feel this legitimately, and

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Speaker 2: that is a thing of almost unfathomable sadness. Like, yeah,

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Speaker 2: I had my angry atheist period like a lot of people,

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Speaker 2: but like I have so much. I'm so much more

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Speaker 2: okay with Christianity than i am this.

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Speaker 3: Oh yeah, absolutely. So before I get into how this

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Speaker 3: is all supposed to quote unquote work, first I want

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Speaker 3: to talk about how the founder and CEO says that

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Speaker 3: he got the idea for this company, because I think

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Speaker 3: it puts into focus how he sees this product ideally

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Speaker 3: functioning in the future. So Emil Hamirez was writing a

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Speaker 3: train with his four year old daughter. She was playing

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Speaker 3: on her iPad and discovered Siri. She began talking with

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Speaker 3: Siri and asking it questions like what do you eat?

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Speaker 3: And do you have a mommy. I'll let I'll let

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Speaker 3: a meal tell the rest here.

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Speaker 6: But thirty minutes later she was laughing and having really

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Speaker 6: like a nice time with Siri, and she said, Siri,

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Speaker 6: I love you. You're my best friend. And that struck

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Speaker 6: a chord with me that that inspired me so much,

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Speaker 6: because I said to myself at that moment, children don't

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Speaker 6: see computers and devices as a tool. They see them

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Speaker 6: as a companion. And today she speaks with Siri orle

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Speaker 6: Likes or any other device. But in the future, I

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Speaker 6: want her to be able to speak to me, to

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Speaker 6: be able to ask me a question, just like she

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Speaker 6: did the device. And understanding the technology, I know that

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Speaker 6: the only way that's possible. I'm able to take my

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Speaker 6: thoughts and put them in a cloud so that then

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Speaker 6: later she can access those that information. So that's how

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Speaker 6: the idea for my bank came about. It's a place

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Speaker 6: for you to store your ideas for the next generation

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Speaker 6: to tap into.

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Speaker 2: No, so the generations already linger too long. We had

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Speaker 2: it right when people died when they were well, not died.

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Speaker 2: But Logan's run had it right. We should kill everyone

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Speaker 2: at thirty five. But this is this is so fucking offensive,

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Speaker 2: Like the the idea that for first off, like if

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Speaker 2: you're looking at we want a device, you know a

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Speaker 2: way to use technology to help people grieve or something,

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Speaker 2: and like you decide maybe having a chat about that

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Speaker 2: they get you. I'm sure it's possible that that could

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Speaker 2: be part of healthy grieving. I'm not going to say

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Speaker 2: that that there's no place for that, but something that

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Speaker 2: is definitely not just stupid, but toxic and poisonous is

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Speaker 2: having a machine speak with the voice of a child's

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Speaker 2: parent while that parent is alive, and confusing the child

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Speaker 2: as to whether or not the phone or their parent

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Speaker 2: is conscious. Like that seems bad to me.

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Speaker 3: There's actually another product that that that does this right now,

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Speaker 3: which has kind of caused some controversy for this, for

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Speaker 3: this very thing you mention, it's a it's a Tarkara

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Speaker 3: Tommy smart speaker, which if listening to a parents have

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Speaker 3: always for fifteen minutes, can replicate it and tell your

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Speaker 3: child bedtime stories if you aren't physically present. And this

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Speaker 3: is this is similarly kind of like cause people to

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Speaker 3: have a whole bunch of questions around. You know, is

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Speaker 3: this good for a child's brain development to have to

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Speaker 3: have their parents' voice be coming out of like a

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Speaker 3: smart speaker. The answer is you probably not, but yeah.

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Speaker 7: So.

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Speaker 3: According to mind Bank's website, Emil's four year old daughter's

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Speaker 3: interactions with Siri quote started a quest in his heart

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Speaker 3: to live forever for his daughter. The quest for immortality

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Speaker 3: has led to something much bigger for humanity because the

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Speaker 3: next personal computer is you unquote. So there's that there's

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Speaker 3: that other line again about having this quest in his

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Speaker 3: heart is actually part of a bigger a bigger quest

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Speaker 3: for all of humanity to live inside a computer or

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Speaker 3: to have a computer.

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Speaker 2: Yeah trained on you. He's he's he's hitting the same

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Speaker 2: speech cadences that guys like musk us like. He understands, yes,

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Speaker 2: the kind of he understands partially, the degree of hype

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Speaker 2: that you need to get something off this. But he

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Speaker 2: is he is going too hard. And I'm making that

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Speaker 2: judgment based on the incredibly comforting fact that as you

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Speaker 2: tell me these horrible things, I am looking at your

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Speaker 2: screen and mind Bank has seventy eight subscribers on YouTube,

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Speaker 2: so the company has not yet broken through.

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Speaker 3: I do want to play one one ten second clip,

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Speaker 3: just because the phrasing is really funny.

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Speaker 6: I was inspired by an interaction my daughter had with Siri.

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Speaker 6: What started as daddy's quest for immortality has led us

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Speaker 6: to something far kind.

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Speaker 2: Oh my god, that's pretty funny, right.

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Speaker 4: Man.

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Speaker 2: But no, Robert, you were You were totally.

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Speaker 3: Right about about kind of how Emil's like speech pattern

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Speaker 3: cadences is pushing a very specific thing. Because before Emil

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Speaker 3: got into the tech industry, for eighteen years. He worked

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Speaker 3: in marketing. He has degrees in psychology, communication and art

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Speaker 3: direction and business administration. He isn't a tech guy. He's

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Speaker 3: a marketing guy. And I think that's really good to

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Speaker 3: keep in mind throughout our whole discussion of how he's

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Speaker 3: trying to get funding for mind Bank, because that is

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Speaker 3: primarily what all of this marketing is for. It's to

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Speaker 3: attract investors. Because this is still he's still in very

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Speaker 3: early stages of this company. They do have a product,

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Speaker 3: it's out, but it's still primarily based on getting investors

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Speaker 3: to give him money.

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Speaker 2: I think what's most disturbing to me about this is that, like,

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Speaker 2: this is not going to work for this guy because

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Speaker 2: he's a loser nobody cares about. But if Elon Musk

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Speaker 2: or one of our other many techno grifters, or if

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Speaker 2: a number of them got behind similar things, like I

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Speaker 2: think that the nightmare scenario to me is someday hopping

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Speaker 2: on Twitter to see that fucking Ian Miles Chong or

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Speaker 2: Ben Shapiro or Jackson Hinkle or any one of these

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Speaker 2: like horrible horrible social media poison distributors will be like

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Speaker 2: I have made an AI trained on my voice you

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Speaker 2: can have me all the time to argue, Like if

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Speaker 2: you want to, you know, you can ask me questions

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Speaker 2: or whatever. You go to a protest and have me

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Speaker 2: yell at liberals for you, Like, something like that will

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Speaker 2: happen at some point with one of these guys.

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Speaker 3: I could not wait to bring Ben Shapiro to Thanksgiving

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Speaker 3: dinner and have him argue with Yeah, people around here.

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Speaker 2: The next time you stay at my house with somebody

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Speaker 2: that you love and care about and feel comfortable in

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Speaker 2: the arms of you are going to drift off to sleep,

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Speaker 2: and then through the speakers that I have installed in

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Speaker 2: the room, you will hear Ben Shapiro's voice coaxing you

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Speaker 2: both to acts of love. Oh, that's that's what's gonna happen.

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Speaker 3: So as an example of this kind of very marketing

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Speaker 3: heavy approach, I'm gonna I'm gonna read something from the

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Speaker 3: homepage of mind Bank's website.

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Speaker 2: Quote.

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Speaker 3: Our vision is to be the world's most trusted guardians

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Speaker 3: of your AI digital twin and move the human race forward.

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Speaker 3: Humanity's next evolutionary step is to combine ourselves with AI

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Speaker 3: and move humanity forward so that we are no longer

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Speaker 3: bound by anything that sentence is just marketing bubo jumbo.

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Speaker 3: It's it's it's meaningless hype like hype words and phrases

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Speaker 3: that refer to this like science fiction feature. But like

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Speaker 3: it's it's nothing.

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Speaker 2: It's worse than meaningless. It's like it's it's wrong, it's

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Speaker 2: stupid wrong, Like the idea that like, you would not

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Speaker 2: be bound by anything if you could live inside in

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Speaker 2: the at bought, Like, yeah, I have I have an A.

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Speaker 2: I have used an AI, right, I have it on

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Speaker 2: my computer, my computer. Were I to hurl it across

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Speaker 2: the room in the same manner that I myself have

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Speaker 2: been flung, it would break and I would not like I.

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Speaker 3: Am finally free to think within my computer's RGB gamer ram.

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Speaker 2: Yeah, finally, Like when I have a laptop that gets

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Speaker 2: too old, Like the very act of surfing the internet

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Speaker 2: is a nightmare. I don't want my conscience on something

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Speaker 2: that ages at the speed of a smartphone. Likes, that's

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Speaker 2: even worse than being a person, Robert, do you know

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Speaker 2: what else is a very important evolutionary step for the

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Speaker 2: future of humanity? Oh God, I don't know when we

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Speaker 2: all suddenly spontaneously, as if by God's grace, starts speaking

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Speaker 2: with the voice of Ben Shapiro.

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Speaker 3: Yes, and perhaps you can do that if one of

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Speaker 3: our sponsors is Ben Shapiro. Bought coming soon yep, to

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Speaker 3: a smartphone near you.

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Speaker 2: All right, we are back.

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Speaker 3: Let's finally talk about how this digital twin thing is

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Speaker 3: actually supposed to work. So you download the mind bank app.

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Speaker 3: I'm sure that's totally safe.

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Speaker 2: Yeah, I trust this with all of my thoughts.

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Speaker 3: And every day, your digital twin will ask you questions

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Speaker 3: about how you're feeling and what you're thinking about, and

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Speaker 3: as you tell it your quote unquote life story. Your

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Speaker 3: inputs will be used to train the twin to make

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Speaker 3: a more accurate digital copy of yourself. This is from

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Speaker 3: their This is from their website town page quote store.

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Speaker 3: Your conscience guided questions help train your digital twin to

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Speaker 3: know your life story so you can live forever through data.

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Speaker 3: The more questions you answer, the closer your AI digital

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Speaker 3: twin will get to becoming you.

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Speaker 2: Unquote God in Heaven.

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Speaker 3: So when Robert and I were at CEES this past

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Speaker 3: this past January, we spoke to mind Bank's co founder

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Speaker 3: and the director of Systems, Architecture and cybersecurity, and I'm

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Speaker 3: going to let him explain kind of some of some

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Speaker 3: of the process of asking mind bank questions and how

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Speaker 3: that helps craft this digital twin.

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Speaker 7: We ask you questions from how's your day to what

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Speaker 7: does money meaning you?

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Speaker 4: And you answer those questions with your voice in a

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Speaker 4: natural way. You can break a voice to text. You

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Speaker 4: get a sentiment analysis on the.

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Speaker 7: Text and provide you a dashboard of what you're feeling

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Speaker 7: when you say that, so that you can also continue

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Speaker 7: to use it over time. And then as you use

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Speaker 7: it over time, the dashboard, we'll show you that you're

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Speaker 7: doing better or worse, just.

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Speaker 4: Like a running application, what better or worse it?

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Speaker 7: What whatever metric that you're interested in, your happiness, your awake,

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Speaker 7: your awareness, your.

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Speaker 4: We have a very large amount of sentiment that we

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Speaker 4: can provide you with.

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Speaker 8: Here's a small bits, but you can see kind of

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Speaker 8: what we have looks like Here you've got multiple different

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Speaker 8: possible types of sentiment, and then within each sentiment, you've

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Speaker 8: got multiple different factors that you can weigh against.

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Speaker 3: To grow mind Bank's user base, there needs to be

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Speaker 3: some reason for users to input the massive amounts of

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Speaker 3: data that's needed to build this digital replica. So the

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Speaker 3: current model of this product is being billed as a

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Speaker 3: quote self care and personal development app where the user

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Speaker 3: talks to their digital twin, kind of like you would

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Speaker 3: talk to a therapist. Yeah, this is This is a

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Speaker 3: big part of mind Bank's marketing that as as you're

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Speaker 3: building this digital twin, it can be used as a

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Speaker 3: tool for self reflection and a way to quote learn

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Speaker 3: about yourself talk to your inner voice with your own

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Speaker 3: personal digital twin unquote, which is really funny because I

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Speaker 3: could talk to my I could talk to my inner

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Speaker 3: voice whenever I want to. Yeah, it's it's called thinking.

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Speaker 3: It's actually pretty pretty easy.

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Speaker 2: This is I really I don't envy, but I'm fascinated

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Speaker 2: by the kind of people whose thoughts are so I

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Speaker 2: don't know a better word than distincal, no legal, that

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Speaker 2: they would think that they could just that they could

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Speaker 2: transfer everything they think over your machine and not get arrested,

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Speaker 2: right like I would be in a prison if I

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Speaker 2: had to put the things in my brain on the internet,

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Speaker 2: like I put a lot of them, but not all

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Speaker 2: of them. There are some very careful doors and locked

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Speaker 2: rooms in there that you people don't get access to.

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Speaker 3: No, there's there's certainly a lot of interesting facets there

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Speaker 3: of someone feeling like they need this tool to to

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Speaker 3: kind of analyze their own thoughts. Like it's it's it's

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Speaker 3: a way to like externalize it that makes you process it.

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Speaker 3: But I don't know, you can also just like like

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Speaker 3: take up journaling or something like there's there's a lot

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Speaker 3: of a lot of ways to get around this. But

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Speaker 3: this is This is from a mind Bank's app store page.

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Speaker 3: Quote like a mirror to your soul. Each answer you

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Speaker 3: give allows you to get insights into your mind. It

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Speaker 3: will help you grow mentally strong unquote. So again, it's

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Speaker 3: like being able to talk to yourself with this digital

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Speaker 3: twin is a big part of their early push great

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Speaker 3: By using quote unquote cutting edge cognitive analysis, the mind

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Speaker 3: bank app responds to your data inputs with quote valuable

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Speaker 3: insights into each answer to understand how your mind works unquote.

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Speaker 3: The app also utilizes quote psycholinguistic models to create a

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Speaker 3: dashboard of the mind for personal development and self care.

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Speaker 3: I'm going to play another another fantastic kind of thirty

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Speaker 3: second clip here.

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Speaker 6: Hi, I'm your personal digital twin. I learned by asking

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Speaker 6: many questions, each answer build my wisdom. You grow through

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Speaker 6: self reflection and I get a little bit closer to

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Speaker 6: becoming you.

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Speaker 2: Let me show you around.

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Speaker 6: Here's our training screen, where you can be your product

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Speaker 6: based on the number of questions you've answered for this

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Speaker 6: phase of my training. Each phase adds a new dimension

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Speaker 6: to my abilities, and the possibilities are endless. The mind

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Speaker 6: map section is like our consciousness. Different questions will challenge

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Speaker 6: you to reflect and create a more well rounded version

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Speaker 6: of us.

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Speaker 3: So that's that's kind of the layout of the user interface.

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Speaker 2: This is like the inevitable extent of all of this,

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Speaker 2: categorizing your personality type with these letters, taking this quiz

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Speaker 2: and defining yourself this way, plotting your political beliefs on

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Speaker 2: this map that way, like gamification of identity. Almost shit

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Speaker 2: that we've been doing, like taking shit that used to

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Speaker 2: be like the starting screen from a fucking RPG game

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Speaker 2: and turning it into social media fodder. This is like

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Speaker 2: treating that as if it is the whole of consciousness

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Speaker 2: and how one must one can replicate consciousness. But also

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Speaker 2: like treat like the thing that's just like actually disturbing

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Speaker 2: about this is that there these people are insinuating that

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Speaker 2: this is a kind of therapy that ye, you can

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Speaker 2: just sort of vomit your thoughts out and the machine

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Speaker 2: can analyze them based on the kinds of words and

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Speaker 2: whatnot that you're using and then give you useful advice

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Speaker 2: on your life.

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Speaker 3: Like that's unsettling, Yes, and you're kind of right on

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Speaker 3: the money in terms of this like personality testing thing.

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Speaker 3: Mind Being's website has a whole bunch of articles which

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Speaker 3: I think are written by chat chipd because I read

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Speaker 3: a lot of them and they all read exactly like

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Speaker 3: a chat cheaptee article. But they have a lot of

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Speaker 3: articles on like what personality types make you a good CEO,

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Speaker 3: and like all of like a whole batch of stuff

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Speaker 3: like that. That that that references like Myers Briggs testing

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Speaker 3: and other kind of personality testings and uses it to

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Speaker 3: compare to their own personality models on the mind bank app.

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Speaker 3: So yes, that they are very much kind of doing

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Speaker 3: doing that in like this this like corporate business leadership

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Speaker 3: assent like leadership ascension track type thing for how you

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Speaker 3: can like improve your personality to make you a better

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Speaker 3: business man. Cool cool stuff. But in order for there

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Speaker 3: to be enough data to build an even slightly accurate

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Speaker 3: digital simulacra feeding daily inputs into an app will need

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Speaker 3: to be a long term project, this self improvement focus

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Speaker 3: that they're talking about with this, Like you know, analyzing

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Speaker 3: your thoughts is just a way to provide you with

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Speaker 3: something immediate to based on your personal data. Quote. As

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Speaker 3: you create your AI digital twin, you will go on

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Speaker 3: a lifelong journey of personal discovery and growth that will

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Speaker 3: allow you to reach your full potential. Each answer will

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Speaker 3: help bring focus to your mind and allow you to

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Speaker 3: reflect on your past unquote. So on the app, you

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Speaker 3: can track the progress of your digital twin and refer

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Speaker 3: back to previous questions. You can refer to questions you've

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Speaker 3: already answered to quote see how your thoughts shift topics

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Speaker 3: or change sentiment over time. And then the more questions

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Speaker 3: you answer, the app raises your quote unquote twinning score,

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Speaker 3: which I think is just a really funny term. Quote.

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Speaker 3: The higher your twinning score, the closer you get to

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Speaker 3: knowing yourself fully.

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Speaker 4: What which is.

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Speaker 2: That's the sex thing?

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Speaker 4: Right?

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Speaker 2: That sounds like a sex thing?

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Speaker 6: Right?

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Speaker 3: How is it anything not just to go we'd a

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Speaker 3: weird fucked up sex thing.

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Speaker 2: Yeah, that's that's what how I'm taking this garrison.

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Speaker 3: So that that was also on their app store page.

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Speaker 3: So the mind bank app has been out for a

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Speaker 3: little over a year now, but unless you pay six

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Speaker 3: bucks a month or sixty dollars a year, you'll only

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Speaker 3: have access to a out less than a dozen of

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Speaker 3: these questions.

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Speaker 2: Is this currently running on a subcription model?

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Speaker 4: Yes, it is, so there's freemium. You can try the out.

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Speaker 4: You can download the m now.

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Speaker 7: It's been launched for almost a year, where version two

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Speaker 7: is coming out soon look a couple of weeks, but

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Speaker 7: both Android and iOS, and there's a free model, so

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Speaker 7: you can you have ten questions that you can answer

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Speaker 7: and answer it many times you want. You get the

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Speaker 7: sentiment analysos, you get a full application, just ten questions.

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Speaker 7: Once you hit subscription model, you get all of the

442
00:25:27,400 --> 00:25:30,080
Speaker 7: access to all of the questions and then obviously we're

443
00:25:30,080 --> 00:25:31,880
Speaker 7: going to be growing more now.

444
00:25:32,040 --> 00:25:35,679
Speaker 3: Like Robert mentioned before, this is kind of related to

445
00:25:35,800 --> 00:25:40,479
Speaker 3: personality testing, and like personality graphing, mind Bank sorts your

446
00:25:40,560 --> 00:25:44,399
Speaker 3: quote unquote digital brain into the Big five personality traits

447
00:25:44,440 --> 00:25:47,040
Speaker 3: that were developed in the twentieth century, with each of

448
00:25:47,119 --> 00:25:50,600
Speaker 3: the Big Five having six subtraits on the mind ban

449
00:25:50,680 --> 00:25:53,320
Speaker 3: gap that it uses to graph changes on what they

450
00:25:53,320 --> 00:25:57,240
Speaker 3: call the dashboard of the mind. I'll just go through

451
00:25:57,280 --> 00:26:00,560
Speaker 3: the big five personality traits and the very kind of

452
00:26:00,640 --> 00:26:03,879
Speaker 3: subcategories it has. The first one is agreeableness, which has

453
00:26:03,920 --> 00:26:09,040
Speaker 3: the subcategories of humble, cooperative, trusting, genuine, empathetic, and generous.

454
00:26:09,560 --> 00:26:15,960
Speaker 3: Then we have neuroticism, which has the subtraits impulsive, self conscious, aggressive, melancholy,

455
00:26:16,119 --> 00:26:20,080
Speaker 3: stress prone, and anxiety prone. We then have openness with

456
00:26:20,119 --> 00:26:26,040
Speaker 3: the subcategories artistic, adventurous, liberal, intellectual, emotionally aware, and imaginative.

457
00:26:26,720 --> 00:26:31,760
Speaker 3: We have extraversion with the subcategories assertive, active, cheerful, friendly, sociable,

458
00:26:31,800 --> 00:26:38,639
Speaker 3: and outgoing. And finally, conscientiousness with the subtraits cautious, ambitious, dutiful, organized,

459
00:26:38,760 --> 00:26:40,320
Speaker 3: self assured, and responsible.

460
00:26:40,640 --> 00:26:42,840
Speaker 2: Yeah. Those are the only ways to describe a human mind.

461
00:26:42,960 --> 00:26:47,600
Speaker 3: Sure, yeah, no, it's I think I think at all. Yeah,

462
00:26:48,320 --> 00:26:51,960
Speaker 3: they finally figured it out. So you know, all these

463
00:26:51,960 --> 00:26:54,679
Speaker 3: things are like a sliding scale. Each of them represents

464
00:26:54,880 --> 00:26:58,280
Speaker 3: the inverse of the thing as well. I think we've

465
00:26:58,320 --> 00:27:00,720
Speaker 3: talked enough about these personality trait things. It doesn't really

466
00:27:00,720 --> 00:27:01,320
Speaker 3: matter that much.

467
00:27:02,119 --> 00:27:04,399
Speaker 2: But once, once your.

468
00:27:04,280 --> 00:27:08,720
Speaker 3: Twinning score is high enough, you can you can compare

469
00:27:09,040 --> 00:27:13,760
Speaker 3: your digital twin to estimated profiles of famous thinkers and

470
00:27:13,880 --> 00:27:17,080
Speaker 3: share access to your twin with friends and family on

471
00:27:17,119 --> 00:27:17,960
Speaker 3: the app, which is.

472
00:27:18,240 --> 00:27:21,000
Speaker 2: Estimated profiles of famous thinkers.

473
00:27:22,800 --> 00:27:25,239
Speaker 3: I'm gonna play I'm gonna play another clip to kind

474
00:27:25,280 --> 00:27:27,280
Speaker 3: of explain what I mean here.

475
00:27:28,440 --> 00:27:32,160
Speaker 6: Each swipe revealing more details about our thinking and connecting

476
00:27:32,240 --> 00:27:37,120
Speaker 6: us to similar personalities. Think of it like collecting cards

477
00:27:37,160 --> 00:27:38,720
Speaker 6: as a kid, only.

478
00:27:38,520 --> 00:27:39,119
Speaker 4: For your mind.

479
00:27:39,720 --> 00:27:44,119
Speaker 2: You might be able to ask him a question, what

480
00:27:44,160 --> 00:27:44,600
Speaker 2: do you do?

481
00:27:45,000 --> 00:27:45,359
Speaker 9: Dude?

482
00:27:46,119 --> 00:27:51,040
Speaker 6: Socrates know thyself and who knows us better? And in

483
00:27:51,080 --> 00:27:55,080
Speaker 6: our inner circle, each interaction will help us evolve and

484
00:27:55,160 --> 00:27:57,120
Speaker 6: store wisdom for eternity.

485
00:27:57,200 --> 00:28:01,200
Speaker 2: Okay, all right, I will now tell you Socrates would

486
00:28:01,240 --> 00:28:05,040
Speaker 2: have lit this man on fire. Socrates. I'm not a

487
00:28:05,080 --> 00:28:08,679
Speaker 2: big Socrates guy, but he would kill this person like

488
00:28:08,920 --> 00:28:10,920
Speaker 2: he fought in wars. He would do it like.

489
00:28:11,280 --> 00:28:15,640
Speaker 3: Oh yeah, absolutely. The notion of sharing my own digital

490
00:28:15,720 --> 00:28:18,600
Speaker 3: brain profile with friends and families so that they can

491
00:28:18,720 --> 00:28:21,760
Speaker 3: ask my digital self questions horrifying.

492
00:28:22,320 --> 00:28:25,320
Speaker 2: I don't usually go home for Thanksgiving? What makes you

493
00:28:25,400 --> 00:28:26,520
Speaker 2: think I want to do this?

494
00:28:27,720 --> 00:28:28,760
Speaker 3: Oh?

495
00:28:28,840 --> 00:28:31,000
Speaker 2: Like quote.

496
00:28:31,240 --> 00:28:34,800
Speaker 3: After continued use, your digital twin will even be able

497
00:28:34,840 --> 00:28:38,440
Speaker 3: to answer many questions on your behalf and have meaningful

498
00:28:38,560 --> 00:28:46,280
Speaker 3: conversations with people you allow unquote yeah, oh oh oh,

499
00:28:46,320 --> 00:28:46,720
Speaker 3: I bet.

500
00:28:47,560 --> 00:28:50,880
Speaker 2: Look if some motherfucker that I have a meeting with

501
00:28:51,280 --> 00:28:54,240
Speaker 2: ever tries to have me talk with his AI to

502
00:28:54,320 --> 00:28:59,280
Speaker 2: do any part of that process. Again, when I say

503
00:28:59,280 --> 00:29:02,160
Speaker 2: about things I think that are illegal, like my response

504
00:29:02,200 --> 00:29:04,000
Speaker 2: to that is something that I can't say on this

505
00:29:04,120 --> 00:29:08,240
Speaker 2: podcast because I might it's an actionable threat. I would

506
00:29:08,280 --> 00:29:11,720
Speaker 2: actionable threat somebody if they tried to make me talk

507
00:29:11,760 --> 00:29:15,360
Speaker 2: to their fucking AI to schedule a meeting with them, like.

508
00:29:15,840 --> 00:29:20,760
Speaker 3: A horrible what a horrible like uncomfortably anti social thing.

509
00:29:20,920 --> 00:29:23,680
Speaker 3: I'm usually kind of antisocial in some ways, but this

510
00:29:23,800 --> 00:29:26,760
Speaker 3: is like a whole other level of just like despising

511
00:29:26,840 --> 00:29:27,920
Speaker 3: any human interaction.

512
00:29:28,800 --> 00:29:32,480
Speaker 2: Yeah, it's it's anti human, is what it is, which

513
00:29:32,480 --> 00:29:37,320
Speaker 2: is what's unsettling, right, Like not that sending emails and

514
00:29:37,360 --> 00:29:41,680
Speaker 2: shit is like the primary essence of humanity, but you know,

515
00:29:41,800 --> 00:29:44,520
Speaker 2: you know what it makes me think of Garrison. The

516
00:29:45,080 --> 00:29:48,360
Speaker 2: one law enforcement agency that like all of the rich

517
00:29:48,400 --> 00:29:51,360
Speaker 2: conservative assholes who love every other kind of cop hate

518
00:29:51,440 --> 00:29:54,480
Speaker 2: is the TSA. And they hate the TSA because you

519
00:29:54,520 --> 00:29:58,520
Speaker 2: can't get around the TSA unless you're like ridiculously rich.

520
00:29:58,920 --> 00:30:02,320
Speaker 2: Everybody goes through fucking security at the goddamn airport and

521
00:30:02,360 --> 00:30:05,320
Speaker 2: they hate that. It drives them insane that they are

522
00:30:05,800 --> 00:30:09,720
Speaker 2: subject to this little kind of little bit of friction, right,

523
00:30:10,400 --> 00:30:14,520
Speaker 2: and what stuff like communicating in that way is these

524
00:30:14,600 --> 00:30:16,480
Speaker 2: kind of basic things that they're saying that can automate

525
00:30:16,480 --> 00:30:19,440
Speaker 2: these little bits of communication that you get with someone

526
00:30:19,520 --> 00:30:22,960
Speaker 2: setting up a meeting or whatever. Like when you automate

527
00:30:23,280 --> 00:30:27,400
Speaker 2: every bit of friction, then you find out you've automated

528
00:30:27,520 --> 00:30:30,720
Speaker 2: like like there's nothing right, Like there's no life there. Right,

529
00:30:30,800 --> 00:30:36,000
Speaker 2: people are not communicating because communication is fundamentally friction. And yeah,

530
00:30:36,120 --> 00:30:38,560
Speaker 2: like scheduling meetings is not the center of that. But

531
00:30:38,600 --> 00:30:41,520
Speaker 2: the way these people are talking is like we want

532
00:30:41,520 --> 00:30:45,280
Speaker 2: to let you hand tasks over to this thing.

533
00:30:45,720 --> 00:30:47,080
Speaker 3: It's like task alienation.

534
00:30:47,640 --> 00:30:51,080
Speaker 2: Yeah, it's alienating. It's a bad thing to do.

535
00:30:52,280 --> 00:30:54,880
Speaker 3: So when we talk with the co founder at CS,

536
00:30:54,920 --> 00:30:57,560
Speaker 3: he emphasized that this kind of self improvement aspect that

537
00:30:57,960 --> 00:31:00,560
Speaker 3: they're pushing in their early stage, it's really just a

538
00:31:00,600 --> 00:31:02,520
Speaker 3: means to an end with the real goal of being

539
00:31:02,560 --> 00:31:06,200
Speaker 3: producing this form of immortality. I've seen something like this

540
00:31:06,400 --> 00:31:09,600
Speaker 3: for like therapy ats kind of similar course, what what's

541
00:31:09,640 --> 00:31:12,600
Speaker 3: like your application use case for this type of technology.

542
00:31:12,200 --> 00:31:15,160
Speaker 7: So there's actually it's a reasonably spread use case. The

543
00:31:15,280 --> 00:31:19,000
Speaker 7: very initial right now is super selfish. It's just self awareness,

544
00:31:19,280 --> 00:31:21,280
Speaker 7: bringing us your self awareness, making them more aware of

545
00:31:21,320 --> 00:31:24,360
Speaker 7: their state as they're speaking. The real long term value

546
00:31:24,360 --> 00:31:26,440
Speaker 7: is actually, if you imagine doing this over the course

547
00:31:26,480 --> 00:31:29,560
Speaker 7: of forty years, fifty years, and then if you eventually pass,

548
00:31:30,040 --> 00:31:32,040
Speaker 7: you can pass this on to your children who can

549
00:31:32,040 --> 00:31:34,120
Speaker 7: then query it and it will answer exactly the way

550
00:31:34,160 --> 00:31:36,960
Speaker 7: you would answer any of these questions and AI filled

551
00:31:36,960 --> 00:31:38,400
Speaker 7: with just your data.

552
00:31:38,720 --> 00:31:40,760
Speaker 4: So it's like your legacy being indefinite.

553
00:31:41,640 --> 00:31:44,400
Speaker 3: So the mind Bank page on the app store boasts

554
00:31:44,720 --> 00:31:48,920
Speaker 3: achieve immortality, your mind will be safely secured in the

555
00:31:48,960 --> 00:31:55,640
Speaker 3: cloud forever. Again, that just comes off as like a

556
00:31:55,720 --> 00:31:58,920
Speaker 3: threat to me. I don't I don't want my mind

557
00:31:58,960 --> 00:32:00,520
Speaker 3: to be stored in the cloud forever.

558
00:32:01,120 --> 00:32:06,480
Speaker 2: Yeah, I don't want to be locked up with DV

559
00:32:06,640 --> 00:32:09,280
Speaker 2: into art for all of attorney.

560
00:32:11,480 --> 00:32:14,200
Speaker 3: To kind of again kind of on this on this

561
00:32:14,240 --> 00:32:18,240
Speaker 3: form of immortality notion here is here is their CEO

562
00:32:19,200 --> 00:32:23,880
Speaker 3: explaining how how this platform will help you live forever

563
00:32:24,160 --> 00:32:25,600
Speaker 3: on the on the Internet.

564
00:32:26,680 --> 00:32:29,000
Speaker 6: The mission of mind Bang is so we can build

565
00:32:29,040 --> 00:32:31,240
Speaker 6: a secure platform that can story data so that you

566
00:32:31,240 --> 00:32:34,280
Speaker 6: can live forever. But if you look, we look a

567
00:32:34,320 --> 00:32:37,200
Speaker 6: bit deeper than that. Our vision is to build an

568
00:32:37,240 --> 00:32:41,920
Speaker 6: artificial consciousness that's not bound by time and space, something

569
00:32:41,960 --> 00:32:45,120
Speaker 6: that can travel, something that can that can go where

570
00:32:45,320 --> 00:32:47,600
Speaker 6: literally no man has gone before.

571
00:32:48,160 --> 00:32:51,479
Speaker 3: Now, the thing we haven't really mentioned yet is like

572
00:32:52,520 --> 00:32:56,840
Speaker 3: this thing won't help you live forever. Like when you die,

573
00:32:57,480 --> 00:33:00,920
Speaker 3: you you still die. Your brain's are getting like poured

574
00:33:00,920 --> 00:33:03,920
Speaker 3: it over online. This is this is just like a

575
00:33:04,280 --> 00:33:08,920
Speaker 3: like a very crude simulacrum based on thoughts that you

576
00:33:09,000 --> 00:33:13,000
Speaker 3: have told this app. Yeah, it's based like it's it's

577
00:33:13,080 --> 00:33:15,480
Speaker 3: it's not it's not helping you live forever at all,

578
00:33:15,560 --> 00:33:17,000
Speaker 3: Like you you don't.

579
00:33:18,880 --> 00:33:22,040
Speaker 2: I most people I feel are like this way. I

580
00:33:22,080 --> 00:33:25,640
Speaker 2: don't say everything that I think and feel, right, Yeah,

581
00:33:25,800 --> 00:33:27,760
Speaker 2: like even when I'm like and I'm not saying like

582
00:33:27,920 --> 00:33:32,360
Speaker 2: I'm being dishonest, but like they're the experience of life

583
00:33:32,880 --> 00:33:36,520
Speaker 2: that my consciousness is aware of when I am communicating

584
00:33:37,000 --> 00:33:40,920
Speaker 2: is broader than just the words that I output and

585
00:33:41,280 --> 00:33:44,080
Speaker 2: taking just those words. It's the same idea that like,

586
00:33:44,280 --> 00:33:46,840
Speaker 2: you can get to know Mark Twain because we fed

587
00:33:46,840 --> 00:33:50,800
Speaker 2: all of his books into an AI well, no, you know,

588
00:33:50,920 --> 00:33:53,800
Speaker 2: an author is not their books. There was a person

589
00:33:54,160 --> 00:33:56,520
Speaker 2: with a lot of things that you don't know that

590
00:33:56,640 --> 00:33:58,880
Speaker 2: still fed into make those words that like if you

591
00:33:59,000 --> 00:34:01,800
Speaker 2: just put the words in, you don't get and your

592
00:34:02,360 --> 00:34:06,240
Speaker 2: vision of what human beings are is reductive in a

593
00:34:06,280 --> 00:34:09,560
Speaker 2: way that makes me understand some of the concerns religious

594
00:34:09,600 --> 00:34:10,880
Speaker 2: people have with atheism.

595
00:34:12,520 --> 00:34:17,640
Speaker 3: So obviously mind Bank's horizons are far beyond this sort

596
00:34:17,680 --> 00:34:20,759
Speaker 3: of kind of self help app. So far, mind bank

597
00:34:20,800 --> 00:34:23,719
Speaker 3: has been mostly a business to consumer, with their app

598
00:34:23,760 --> 00:34:26,920
Speaker 3: being marketed directly to users for them to download and

599
00:34:27,000 --> 00:34:30,680
Speaker 3: use by themselves. But they are working to expand far

600
00:34:30,760 --> 00:34:33,640
Speaker 3: past that very limited scope in terms.

601
00:34:33,400 --> 00:34:34,160
Speaker 4: Of a business plan.

602
00:34:34,239 --> 00:34:38,000
Speaker 9: Are you guys interested in kind of solely individual.

603
00:34:37,680 --> 00:34:41,160
Speaker 4: Subscriptions or are you is there kind of an enterprise

604
00:34:41,239 --> 00:34:42,479
Speaker 4: application of this as well.

605
00:34:42,640 --> 00:34:45,480
Speaker 7: We're actually moving into a bunch of different verticals, so

606
00:34:45,760 --> 00:34:51,440
Speaker 7: government for PTSD, that sort of mindset, also the healthcare,

607
00:34:51,800 --> 00:34:56,000
Speaker 7: so mental it's obvious benefit in the medical building. So

608
00:34:56,160 --> 00:34:59,160
Speaker 7: that's kind of the understanding of our verticals that we

609
00:34:59,239 --> 00:35:02,000
Speaker 7: have the we're going to move into, and we're looking

610
00:35:02,000 --> 00:35:04,560
Speaker 7: for funding right now just start building out those verticals.

611
00:35:04,600 --> 00:35:08,239
Speaker 4: So enterprise space is definitely in the roadmap, but we

612
00:35:08,480 --> 00:35:09,080
Speaker 4: just need money.

613
00:35:09,520 --> 00:35:13,239
Speaker 3: A lot of their recent marketing has been targeted towards

614
00:35:13,480 --> 00:35:17,839
Speaker 3: appealing to seed investors. Besides partnering with various governments, they're

615
00:35:17,840 --> 00:35:20,640
Speaker 3: also moving into the business to business sector, with plans

616
00:35:20,680 --> 00:35:24,560
Speaker 3: to enter quote the healthcare space by providing psychologists remote

617
00:35:24,560 --> 00:35:29,080
Speaker 3: patient monitoring unquote, which also is a similarly kind of

618
00:35:30,640 --> 00:35:35,880
Speaker 3: freaky notion that your psychologist can just have a copy

619
00:35:35,920 --> 00:35:38,239
Speaker 3: of your own expressive thoughts to just refer to at

620
00:35:38,239 --> 00:35:42,360
Speaker 3: any time and they can use it as remote patient monitoring.

621
00:35:42,800 --> 00:35:45,800
Speaker 3: It's just like an uncomfortable notion.

622
00:35:46,320 --> 00:35:49,440
Speaker 4: We've got over twenty thousand installs. The B to B

623
00:35:49,640 --> 00:35:50,920
Speaker 4: is the next area.

624
00:35:50,719 --> 00:35:53,480
Speaker 7: We're going into in the therapy and psychology space, and

625
00:35:53,520 --> 00:35:57,040
Speaker 7: so imagine your therapist, instead of needing your first one

626
00:35:57,080 --> 00:35:58,839
Speaker 7: hour to learn who you are in the next three

627
00:35:58,920 --> 00:36:01,719
Speaker 7: or four different to figure out getting the meat and

628
00:36:01,719 --> 00:36:05,879
Speaker 7: potatoes of your mind, this is an immediate, raw, quantitative

629
00:36:05,960 --> 00:36:08,839
Speaker 7: dashboard of your sentiment and how you're feeling that they

630
00:36:08,880 --> 00:36:11,200
Speaker 7: have access to. And then you can also provide them

631
00:36:11,200 --> 00:36:13,839
Speaker 7: the sentiment of individual answers, which would then give them

632
00:36:13,880 --> 00:36:18,360
Speaker 7: a point in time emotional marker for how you're feeling.

633
00:36:18,760 --> 00:36:22,040
Speaker 3: Mind Bank claims that they are currently quote developing a

634
00:36:22,080 --> 00:36:25,480
Speaker 3: marketplace for applications to be used by your digital twin unquote.

635
00:36:25,800 --> 00:36:30,400
Speaker 3: Now what they imagine such applications being ranges from quote

636
00:36:30,440 --> 00:36:35,839
Speaker 3: health related enhancements like early Alzheimer's detection unquote, to more

637
00:36:35,960 --> 00:36:40,640
Speaker 3: therapeutic uses like to quote help to handle depression unquote.

638
00:36:40,960 --> 00:36:45,880
Speaker 3: And again, I really don't see how having this digital

639
00:36:45,920 --> 00:36:50,080
Speaker 3: twin that you talk to every day will help handle

640
00:36:50,120 --> 00:36:55,120
Speaker 3: your depression. Like this is some like depression cure. Now

641
00:36:55,160 --> 00:36:58,239
Speaker 3: on top of like patient healthcare. Mind Bank is also

642
00:36:58,360 --> 00:37:02,640
Speaker 3: hoping to use digital twins for corporate leadership training and

643
00:37:02,880 --> 00:37:05,920
Speaker 3: to get into the supplement industry by using your cognitive

644
00:37:06,000 --> 00:37:09,799
Speaker 3: data to find quote mental nutrition products that can help

645
00:37:09,880 --> 00:37:15,280
Speaker 3: boost your brain. So this is using your digital profile

646
00:37:15,760 --> 00:37:20,320
Speaker 3: to find things to market to you. Again, very very

647
00:37:20,560 --> 00:37:26,920
Speaker 3: very upsetting. Here is Here's here's another another clip of

648
00:37:26,920 --> 00:37:30,799
Speaker 3: of Robert asking asking this, uh, this guy from buying

649
00:37:30,880 --> 00:37:33,239
Speaker 3: Bank about another possible use case.

650
00:37:33,520 --> 00:37:35,839
Speaker 9: So the use case is for this that you've you've

651
00:37:35,840 --> 00:37:39,480
Speaker 9: expressed to me so far, are personal help or help

652
00:37:39,560 --> 00:37:44,200
Speaker 9: developments and providing kind of a living memorial slash legacy

653
00:37:44,280 --> 00:37:49,480
Speaker 9: legis for loved ones after you're deceased. Are there any

654
00:37:49,600 --> 00:37:52,160
Speaker 9: kind of use cases for this beyond that? Like I

655
00:37:52,640 --> 00:37:56,360
Speaker 9: heard someone mentioning the idea of like basically digitally cloning

656
00:37:57,320 --> 00:37:59,799
Speaker 9: a worker so that they can provide I don't know,

657
00:38:00,400 --> 00:38:04,480
Speaker 9: information about tech or something, or a work is like

658
00:38:04,520 --> 00:38:05,840
Speaker 9: a call center or something like that.

659
00:38:05,920 --> 00:38:08,759
Speaker 7: Yeah, so that was a different product I think they

660
00:38:08,800 --> 00:38:12,359
Speaker 7: were talking about, but with similar ties obviously. So yeah,

661
00:38:12,400 --> 00:38:15,640
Speaker 7: we've identified I mean from even at CES, we've talked

662
00:38:15,640 --> 00:38:18,200
Speaker 7: to hundreds of people that have given us thousands of.

663
00:38:18,120 --> 00:38:21,640
Speaker 4: New ideas, but these are.

664
00:38:22,320 --> 00:38:24,920
Speaker 7: The main verticals are kind of where we've identified the

665
00:38:24,920 --> 00:38:26,880
Speaker 7: biggest benefits are going to be, and we're going to

666
00:38:26,880 --> 00:38:28,839
Speaker 7: work with industry partners to kind of build out into

667
00:38:28,880 --> 00:38:33,319
Speaker 7: those verticals. So yes, we've identified use cases, but we're

668
00:38:33,360 --> 00:38:36,400
Speaker 7: trying to not focus too much on individual use cases

669
00:38:36,400 --> 00:38:41,879
Speaker 7: because we've also identified that it's such a broad capability

670
00:38:42,200 --> 00:38:44,480
Speaker 7: that once it gets built and then people start actually

671
00:38:44,520 --> 00:38:47,279
Speaker 7: supplying data, the massive data sets that we're going to have,

672
00:38:47,520 --> 00:38:49,080
Speaker 7: we're just going to have so many different places that

673
00:38:49,080 --> 00:38:50,759
Speaker 7: we can go with the data set, with.

674
00:38:50,719 --> 00:38:54,080
Speaker 4: The capability, with the partnerships, So we we're kind of

675
00:38:54,120 --> 00:38:56,080
Speaker 4: believing ourselves older almost.

676
00:38:56,120 --> 00:38:59,279
Speaker 3: So that was a lot of words without saying very much.

677
00:38:59,480 --> 00:39:02,279
Speaker 3: But it's also does flat out not true. On the

678
00:39:02,320 --> 00:39:04,880
Speaker 3: mind Big website, they list another use case for this

679
00:39:04,920 --> 00:39:08,680
Speaker 3: technology as what they call a knowledge transfer, which is

680
00:39:08,719 --> 00:39:12,839
Speaker 3: marketed to businesses to create digital copies of their employees.

681
00:39:14,360 --> 00:39:15,680
Speaker 3: This is this is one of the this is sort

682
00:39:15,680 --> 00:39:19,520
Speaker 3: of the freakiest things that they are offering. Quote scale

683
00:39:19,640 --> 00:39:23,640
Speaker 3: your best employees, transfer years of experience and company data

684
00:39:23,680 --> 00:39:26,880
Speaker 3: that is locked inside your employee's mind through a guided

685
00:39:26,960 --> 00:39:32,760
Speaker 3: personal digital twin unquote deeply deeply upsetting.

686
00:39:33,520 --> 00:39:37,560
Speaker 2: You know, it was so unsettling to me in that moment,

687
00:39:37,920 --> 00:39:41,120
Speaker 2: not just to be like, the vision of the whole

688
00:39:41,120 --> 00:39:43,600
Speaker 2: app was unsettling, but the fact that he was pitching

689
00:39:43,640 --> 00:39:46,960
Speaker 2: it the way he would a set of earbuds was

690
00:39:47,719 --> 00:39:51,040
Speaker 2: part of what made it so uncomfortable to me. Like

691
00:39:51,200 --> 00:39:53,719
Speaker 2: I have been to many cees's in the past, I

692
00:39:53,760 --> 00:39:56,600
Speaker 2: was always excited because somebody would hand me some cool

693
00:39:56,600 --> 00:39:59,200
Speaker 2: little piece of technology and say, look at this thing.

694
00:39:59,320 --> 00:40:01,880
Speaker 2: It's a smaller phone, or a phone that folds, or

695
00:40:02,160 --> 00:40:04,759
Speaker 2: headphones that you know work better than headphones have in

696
00:40:04,760 --> 00:40:07,080
Speaker 2: the past, or something like that. And this guy was

697
00:40:07,160 --> 00:40:13,200
Speaker 2: like with the exact same excitement and and uh feel

698
00:40:13,239 --> 00:40:16,839
Speaker 2: to him was like, Hey, we're going to digitize your grandpa, Like.

699
00:40:17,400 --> 00:40:23,320
Speaker 3: Yes, yes, I hate that. Another really really a telling

700
00:40:23,400 --> 00:40:26,440
Speaker 3: line from their from their knowledge Transfer section of their

701
00:40:26,480 --> 00:40:27,120
Speaker 3: of their website.

702
00:40:27,200 --> 00:40:27,600
Speaker 2: Quote.

703
00:40:27,960 --> 00:40:31,760
Speaker 3: By using a simple voice chat interface, the users upload

704
00:40:31,800 --> 00:40:35,000
Speaker 3: their experience to the personal Digital Twin. With each interaction,

705
00:40:35,160 --> 00:40:38,880
Speaker 3: the personal digital twin learns everything that is inside the

706
00:40:39,000 --> 00:40:46,680
Speaker 3: mind of the employee. Unquote. I don't understand how someone

707
00:40:46,719 --> 00:40:49,319
Speaker 3: could write that sentence and not be like, oh, this

708
00:40:49,440 --> 00:40:52,719
Speaker 3: is like, this is like villain stuff, right, this is

709
00:40:52,800 --> 00:40:58,040
Speaker 3: like learn learn everything inside the mind of the employee.

710
00:40:58,800 --> 00:41:05,239
Speaker 3: I I like. So, I don't know. Maybe this employee

711
00:41:05,280 --> 00:41:07,279
Speaker 3: did digital cloning thing was just one of the many

712
00:41:07,320 --> 00:41:10,440
Speaker 3: ideas they got while attending cees and and they and

713
00:41:10,520 --> 00:41:14,480
Speaker 3: they implemented the idea after we spoke to them. I

714
00:41:14,560 --> 00:41:17,799
Speaker 3: checked this, No, not the case. The webpage for this

715
00:41:17,920 --> 00:41:21,080
Speaker 3: employee transfer idea goes all the way back to August

716
00:41:21,080 --> 00:41:24,040
Speaker 3: to twenty twenty one on the Internet archive. So the guy,

717
00:41:24,320 --> 00:41:26,120
Speaker 3: the guy we were talking to you was just lying

718
00:41:26,160 --> 00:41:29,600
Speaker 3: to us like this is this has been a part

719
00:41:29,640 --> 00:41:32,480
Speaker 3: of their product for over two years.

720
00:41:32,480 --> 00:41:33,000
Speaker 2: Excellent.

721
00:41:33,680 --> 00:41:36,520
Speaker 3: Uh, Robert, do you know what other products have been

722
00:41:36,560 --> 00:41:38,640
Speaker 3: around for quite a while and are and are very

723
00:41:38,840 --> 00:41:40,080
Speaker 3: very reliable.

724
00:41:41,400 --> 00:41:43,839
Speaker 2: I don't know guns.

725
00:41:44,160 --> 00:41:46,520
Speaker 3: I don't think we are sponsored by big gun.

726
00:41:47,040 --> 00:41:49,800
Speaker 2: We are not. We are not yet sponsored by big guns.

727
00:41:49,840 --> 00:41:54,520
Speaker 2: I every single day, Garrison, I send Colt Firearms a letter,

728
00:41:55,560 --> 00:41:58,880
Speaker 2: and every single day a nice man with a badge

729
00:41:58,960 --> 00:42:01,680
Speaker 2: knocks on my door and says, if you send another letter,

730
00:42:01,760 --> 00:42:04,640
Speaker 2: we're going to arrest you. They don't want your letters, Robert,

731
00:42:05,320 --> 00:42:19,279
Speaker 2: And uh, anyway, here's ads. Ah, we're back.

732
00:42:19,680 --> 00:42:24,520
Speaker 3: So we were talking about how soon employers can just

733
00:42:24,600 --> 00:42:27,239
Speaker 3: copy over your brain, which I'm sure Robert you're going

734
00:42:27,320 --> 00:42:29,839
Speaker 3: to be very interested in for cool Zone. You can

735
00:42:29,920 --> 00:42:33,360
Speaker 3: you can really really cut down on the podcasting costs.

736
00:42:33,640 --> 00:42:36,360
Speaker 2: Yeah, I can. I can really clear you guys out

737
00:42:36,400 --> 00:42:42,160
Speaker 2: and just finally, finally just feed Twitter takes into your

738
00:42:42,280 --> 00:42:46,080
Speaker 2: AI versions and just all the money, take it all in,

739
00:42:46,320 --> 00:42:49,400
Speaker 2: just bathe in it. Yeah. That's a great idea, Garrison,

740
00:42:49,440 --> 00:42:49,759
Speaker 2: thank you.

741
00:42:50,080 --> 00:42:54,240
Speaker 3: Uh huh So the idea that your employer could compel

742
00:42:54,320 --> 00:42:57,400
Speaker 3: you to use such software with the express interest of

743
00:42:57,520 --> 00:43:01,040
Speaker 3: transferring a worker's memories and experiences into a digital asset

744
00:43:01,440 --> 00:43:05,800
Speaker 3: is obviously deeply troubling. This scenario gets at some questions

745
00:43:05,880 --> 00:43:08,759
Speaker 3: about ethics and the responsibility of collecting and storing this

746
00:43:08,800 --> 00:43:10,240
Speaker 3: type of data in the first place.

747
00:43:10,920 --> 00:43:13,879
Speaker 9: My first question would be if the data that you're

748
00:43:14,200 --> 00:43:16,880
Speaker 9: feeding into this thing over the course of forty years,

749
00:43:17,760 --> 00:43:20,120
Speaker 9: who legally owns it you?

750
00:43:20,840 --> 00:43:23,920
Speaker 4: So you guys don't have ownership with it's your ability? Yeah,

751
00:43:23,920 --> 00:43:24,560
Speaker 4: it's yours.

752
00:43:24,680 --> 00:43:28,399
Speaker 3: So I did check this. I read all of their

753
00:43:28,520 --> 00:43:32,480
Speaker 3: long and tedious policy forms and stuff. Now, it is

754
00:43:32,560 --> 00:43:35,360
Speaker 3: true that the user does own the data they upload

755
00:43:35,400 --> 00:43:38,719
Speaker 3: to mind Bank. However, mind Bank can act as a

756
00:43:38,800 --> 00:43:43,600
Speaker 3: processor and data controller, and this includes the ability to

757
00:43:43,760 --> 00:43:47,040
Speaker 3: use any information they collect from you to improve their

758
00:43:47,080 --> 00:43:51,560
Speaker 3: products and deliver targeted advertising from the third parties. If

759
00:43:51,560 --> 00:43:53,400
Speaker 3: you want to remove your data from mind Bank, they

760
00:43:53,400 --> 00:43:56,360
Speaker 3: can store and continue to use your personal information for

761
00:43:56,520 --> 00:44:00,359
Speaker 3: up to sixty months. Now, this data ownership quest gets

762
00:44:00,360 --> 00:44:03,400
Speaker 3: a little bit more murky because in the case of

763
00:44:03,520 --> 00:44:07,080
Speaker 3: like your employer paying for mind Bank subscriptions for their

764
00:44:07,200 --> 00:44:10,960
Speaker 3: entire company. In that case, it's unclear if the company

765
00:44:11,000 --> 00:44:13,840
Speaker 3: would be classified as the user or if the employees

766
00:44:13,880 --> 00:44:17,520
Speaker 3: would be. Now, I'm honestly not sure if mind bank

767
00:44:17,719 --> 00:44:20,759
Speaker 3: has even thought that far ahead, because there's nothing on

768
00:44:20,800 --> 00:44:24,759
Speaker 3: their site or any available materials from them. That kind

769
00:44:24,760 --> 00:44:28,800
Speaker 3: of gets into that question. Now, of course, beyond owning

770
00:44:28,880 --> 00:44:32,600
Speaker 3: the actual like original data, having all this personal data

771
00:44:32,640 --> 00:44:35,200
Speaker 3: stored in one product, and a product that can be

772
00:44:35,239 --> 00:44:40,720
Speaker 3: then easily shared across different for profit industries, that itself

773
00:44:40,719 --> 00:44:44,960
Speaker 3: has freaky ramifications about the accessibility of your data. So

774
00:44:45,239 --> 00:44:47,520
Speaker 3: I assume you get to the side, like when you

775
00:44:47,600 --> 00:44:50,440
Speaker 3: share your digital twin with your therapist.

776
00:44:50,160 --> 00:44:51,759
Speaker 7: You would be able to decide all though, Yeah, and

777
00:44:51,760 --> 00:44:54,600
Speaker 7: then now would it be possible for them to like

778
00:44:54,680 --> 00:44:57,480
Speaker 7: copy over some of the stuff and basically run.

779
00:44:57,320 --> 00:44:59,360
Speaker 3: It themselves, or I mean, can you have like a

780
00:44:59,400 --> 00:45:02,359
Speaker 3: hard cutof for this sort of thing, just to think

781
00:45:02,360 --> 00:45:04,560
Speaker 3: of other types of like you know, it's.

782
00:45:05,920 --> 00:45:08,759
Speaker 4: Different. Wise people could get their hands on this for

783
00:45:08,840 --> 00:45:10,839
Speaker 4: like unsaving means yeah, yeah, for sure, for sure.

784
00:45:10,880 --> 00:45:14,640
Speaker 7: I mean, so, your your data is your data, but

785
00:45:15,120 --> 00:45:17,600
Speaker 7: as you provide it to others, you don't have a

786
00:45:17,640 --> 00:45:20,040
Speaker 7: lot of control if they copy that data. However, if

787
00:45:20,080 --> 00:45:23,480
Speaker 7: they copy that data, that copy that they're giving out,

788
00:45:23,760 --> 00:45:25,680
Speaker 7: anyone that they're trying to sell that to would have

789
00:45:25,760 --> 00:45:27,439
Speaker 7: an understanding that that is not live data.

790
00:45:27,680 --> 00:45:29,160
Speaker 4: It's not data, it's changing with you.

791
00:45:29,480 --> 00:45:31,920
Speaker 7: It's from a point in time, and so your database

792
00:45:31,960 --> 00:45:34,279
Speaker 7: that you own will be live, it will grow with you.

793
00:45:34,719 --> 00:45:38,600
Speaker 3: So the idea of having my friends be able to

794
00:45:38,640 --> 00:45:41,759
Speaker 3: ask an AI trained in my thoughts is like scary enough,

795
00:45:42,320 --> 00:45:45,000
Speaker 3: but the idea that an archived version of this AI

796
00:45:45,200 --> 00:45:48,600
Speaker 3: could be distributed and even sold without my knowledge is

797
00:45:48,640 --> 00:45:53,760
Speaker 3: obviously terrified. Like this is this is deep, deeply troubling.

798
00:45:53,840 --> 00:45:55,680
Speaker 3: This is supposed to be like a private thing that

799
00:45:55,760 --> 00:45:58,239
Speaker 3: you use to communicate with like your therapist, or you

800
00:45:58,239 --> 00:46:00,200
Speaker 3: even talk to the app, like you what a therapist

801
00:46:00,760 --> 00:46:04,360
Speaker 3: And the fact that this is easily shared and able

802
00:46:04,440 --> 00:46:07,040
Speaker 3: to be copied is like a massive problem.

803
00:46:07,719 --> 00:46:13,839
Speaker 2: Yeah, no, I mean especially, I mean I think they

804
00:46:13,880 --> 00:46:18,840
Speaker 2: are probably like I don't see how copying workers the

805
00:46:18,840 --> 00:46:23,279
Speaker 2: way that they are doing it is going to is

806
00:46:23,320 --> 00:46:26,000
Speaker 2: going to work, right, Like yeah, but I do think

807
00:46:26,040 --> 00:46:27,799
Speaker 2: that this is kind of part of this process that

808
00:46:27,880 --> 00:46:29,560
Speaker 2: what like a big part of what they're pushing is

809
00:46:29,600 --> 00:46:31,640
Speaker 2: like you need rid of all of your customer service

810
00:46:31,640 --> 00:46:33,400
Speaker 2: people and just have an AI do it, right, Like

811
00:46:33,440 --> 00:46:36,440
Speaker 2: that is the that is the actual This is a

812
00:46:36,440 --> 00:46:39,680
Speaker 2: lot of silliness, but the actual thing that quote unquote,

813
00:46:39,960 --> 00:46:43,920
Speaker 2: quote unquote AI is being used for is to replace

814
00:46:44,040 --> 00:46:47,160
Speaker 2: human labors at a thing that like machines are worse at, right,

815
00:46:47,560 --> 00:46:52,440
Speaker 2: like the AI fucking customer service bots are fucking terrible.

816
00:46:52,680 --> 00:46:55,320
Speaker 2: It is always how many times have you been around

817
00:46:55,360 --> 00:46:58,160
Speaker 2: somebody yelling like let me talk to a person, let

818
00:46:58,160 --> 00:47:02,480
Speaker 2: me talk to Yeah, Like that's that is what's going

819
00:47:02,520 --> 00:47:04,200
Speaker 2: on here, And the fact that they're trying to dress

820
00:47:04,200 --> 00:47:08,120
Speaker 2: this up is like we've solved death is so fucked up.

821
00:47:09,680 --> 00:47:12,239
Speaker 3: Uh yeah. Part of this, for like the employee thing

822
00:47:12,440 --> 00:47:15,600
Speaker 3: is not even not replacing kind of low level employees

823
00:47:15,600 --> 00:47:18,279
Speaker 3: like customer service workers. It's also like focusing on like

824
00:47:18,840 --> 00:47:21,239
Speaker 3: your top ten best employees and then by forcing them

825
00:47:21,239 --> 00:47:23,640
Speaker 3: to interact with with this app every day, you can

826
00:47:23,680 --> 00:47:27,560
Speaker 3: you can use the information from like your best performers

827
00:47:27,920 --> 00:47:31,719
Speaker 3: as like asset data that you can like use to

828
00:47:32,239 --> 00:47:35,520
Speaker 3: help get your other other employees to become more efficient.

829
00:47:35,600 --> 00:47:35,719
Speaker 2: Right.

830
00:47:35,719 --> 00:47:39,239
Speaker 3: It's it's there's They certainly have a few other kind

831
00:47:39,239 --> 00:47:41,920
Speaker 3: of ideas for how this how this is possibly.

832
00:47:41,600 --> 00:47:45,879
Speaker 2: Used hate these kinds of people. There's a this got

833
00:47:45,880 --> 00:47:49,360
Speaker 2: overused at a point in like the kind of late aughts,

834
00:47:49,600 --> 00:47:51,279
Speaker 2: so maybe people are sick of it. But there's a

835
00:47:51,320 --> 00:47:54,080
Speaker 2: line in the speech Charlie Chaplin gives in the great

836
00:47:54,120 --> 00:47:58,560
Speaker 2: dictator machine men with machine minds and machine hearts, and

837
00:47:58,600 --> 00:48:00,920
Speaker 2: he was referring to the naz And they're obsession with

838
00:48:00,960 --> 00:48:04,880
Speaker 2: shit like Taylorism, or at least prototailorism kind of. I

839
00:48:04,920 --> 00:48:09,600
Speaker 2: think organized industry treating people like cogs in a great machine.

840
00:48:09,960 --> 00:48:13,040
Speaker 2: The civilization is one machine, and each human being is

841
00:48:13,040 --> 00:48:15,839
Speaker 2: is just a single piece of it, like the the

842
00:48:16,200 --> 00:48:20,560
Speaker 2: that's you know, the old era horrifying machine man thought.

843
00:48:20,600 --> 00:48:23,600
Speaker 2: The new era horrifying machine man thought is you can

844
00:48:23,640 --> 00:48:26,719
Speaker 2: digitize your employees and they can train each other in

845
00:48:26,840 --> 00:48:30,640
Speaker 2: EAI form, and you can replicate them, and you know

846
00:48:30,680 --> 00:48:32,840
Speaker 2: the unsaid part of the worse, and then you fire

847
00:48:32,880 --> 00:48:36,440
Speaker 2: them and their robot clone keeps doing their job for free.

848
00:48:36,480 --> 00:48:41,000
Speaker 2: We made a slave, so god damn it.

849
00:48:41,640 --> 00:48:44,320
Speaker 3: I think a big part of the way they've designed

850
00:48:44,320 --> 00:48:46,960
Speaker 3: this data set is that it can be easily transferred,

851
00:48:47,400 --> 00:48:50,160
Speaker 3: as the guy at c YES explained to us.

852
00:48:51,160 --> 00:48:54,960
Speaker 9: So if if we're talking forty to fifty years down

853
00:48:55,000 --> 00:48:58,600
Speaker 9: the line, people pass this the Sovie companies, you know,

854
00:48:58,640 --> 00:49:00,800
Speaker 9: my bank is no longer out forty years.

855
00:49:01,640 --> 00:49:03,960
Speaker 7: We've already established the data set in such a way

856
00:49:04,000 --> 00:49:08,319
Speaker 7: that we don't have competitors yet to say, but if

857
00:49:08,360 --> 00:49:13,520
Speaker 7: we eventually do establish a competitive arm or people that

858
00:49:13,560 --> 00:49:16,239
Speaker 7: are competitors, we already have the application set up to

859
00:49:16,280 --> 00:49:18,240
Speaker 7: where users can take their data off of our platform

860
00:49:18,280 --> 00:49:19,800
Speaker 7: and bring the data wherever they'd like.

861
00:49:19,880 --> 00:49:24,880
Speaker 4: It's your data, where is it? Store?

862
00:49:25,160 --> 00:49:26,239
Speaker 2: Is this this right now?

863
00:49:26,400 --> 00:49:27,799
Speaker 4: Our current live application.

864
00:49:27,960 --> 00:49:30,560
Speaker 7: We're on Azure and so your back end is Azure,

865
00:49:30,600 --> 00:49:32,799
Speaker 7: but we have it encrypted that rest So all did

866
00:49:32,920 --> 00:49:35,400
Speaker 7: you provide to Azure is encrypted when it's on Azure service.

867
00:49:36,840 --> 00:49:40,120
Speaker 7: We also have a blockchain based R and D project.

868
00:49:40,760 --> 00:49:43,560
Speaker 7: It's already been poc and it already exists, so all

869
00:49:43,600 --> 00:49:45,320
Speaker 7: of the data is on chain and the logic is

870
00:49:45,360 --> 00:49:45,759
Speaker 7: on chain.

871
00:49:46,120 --> 00:49:47,520
Speaker 4: It's truly yours.

872
00:49:47,920 --> 00:49:51,560
Speaker 2: In these in these troubled times. Nothing makes me feel

873
00:49:51,600 --> 00:49:54,759
Speaker 2: so secure at the words it's on the blockchain.

874
00:49:56,719 --> 00:50:00,640
Speaker 3: Well, you know, it's it's, it's, it's it's. I think

875
00:50:00,680 --> 00:50:03,800
Speaker 3: he sounds very trustworthy because you have, you have encryption,

876
00:50:04,160 --> 00:50:08,000
Speaker 3: you have the blockchain. And luckily, I think the guy

877
00:50:08,000 --> 00:50:11,160
Speaker 3: that we spoke with reassured us that he is that

878
00:50:11,200 --> 00:50:14,920
Speaker 3: he is deeply, deeply interested in data privacy and he

879
00:50:14,960 --> 00:50:16,520
Speaker 3: has the credentials to back that up.

880
00:50:16,800 --> 00:50:19,480
Speaker 4: So I'm co founder. I'm director of Architecture and Security.

881
00:50:19,600 --> 00:50:20,800
Speaker 4: I have a background at the NSA.

882
00:50:21,160 --> 00:50:24,640
Speaker 7: I'm very very focused on individual human privacy and rights,

883
00:50:24,680 --> 00:50:26,920
Speaker 7: and so that's kind of my goal here is then

884
00:50:27,000 --> 00:50:29,000
Speaker 7: sure that this gets built the right way.

885
00:50:30,560 --> 00:50:33,919
Speaker 2: That was such a you know, Garrison, Honestly, I'm gonna

886
00:50:33,920 --> 00:50:36,120
Speaker 2: get a little real with the audience here. I was

887
00:50:36,160 --> 00:50:39,080
Speaker 2: so proud of you in that moment because he said that,

888
00:50:39,840 --> 00:50:43,640
Speaker 2: and I glanced over at you and you didn't laugh. No, no,

889
00:50:43,920 --> 00:50:47,239
Speaker 2: and that that made like, that was this moment where

890
00:50:47,239 --> 00:50:49,560
Speaker 2: I was like, all right, you are you are. You

891
00:50:49,600 --> 00:50:52,360
Speaker 2: are truly truly coming into your own as a reporter.

892
00:50:52,440 --> 00:50:54,719
Speaker 2: If you can sit there and talk to a man

893
00:50:54,760 --> 00:50:57,480
Speaker 2: who says that, who says you can trust me with

894
00:50:57,600 --> 00:51:00,960
Speaker 2: your data because I was in NSA agent.

895
00:51:01,640 --> 00:51:08,120
Speaker 3: It's okay, ice work for the essay if you sure, buddy.

896
00:51:08,000 --> 00:51:12,319
Speaker 2: Like that was a good moment that I'm saying.

897
00:51:12,480 --> 00:51:16,360
Speaker 3: He worked at the NSA for six years. I looked

898
00:51:16,360 --> 00:51:19,279
Speaker 3: this up. He worked there for six years and then

899
00:51:19,280 --> 00:51:22,759
Speaker 3: he moved into the private sector. And yes, no, it

900
00:51:22,880 --> 00:51:26,279
Speaker 3: is the the idea that that he is using this

901
00:51:26,320 --> 00:51:30,840
Speaker 3: as some sort of credential that shows he respects human

902
00:51:30,960 --> 00:51:36,400
Speaker 3: rights and privacy is like very obviously, like deep deeply ironic.

903
00:51:37,480 --> 00:51:40,000
Speaker 3: I I the irony is not coming from him. The

904
00:51:40,040 --> 00:51:41,360
Speaker 3: irony is the situation.

905
00:51:42,239 --> 00:51:44,400
Speaker 2: He didn't seem totally sincere.

906
00:51:44,080 --> 00:51:47,600
Speaker 3: He was sincere. Yes, absolutely so.

907
00:51:47,640 --> 00:51:49,480
Speaker 2: It's one of those moments that makes you realize, like

908
00:51:49,520 --> 00:51:52,799
Speaker 2: some people just live in a whole different world. Yes, yes, like.

909
00:51:53,920 --> 00:51:57,480
Speaker 3: So, I think it's it's it's useful when referring back

910
00:51:57,560 --> 00:52:00,360
Speaker 3: to everything this guy has said so far that you

911
00:52:00,440 --> 00:52:02,919
Speaker 3: have to remember he worked at the NSA for six

912
00:52:03,000 --> 00:52:08,000
Speaker 3: years and he is now handling, he's personally handled handling

913
00:52:08,040 --> 00:52:12,200
Speaker 3: the cybersecurity and privacy of the personal data you upload

914
00:52:12,200 --> 00:52:14,399
Speaker 3: it every single day onto your AI twin.

915
00:52:15,360 --> 00:52:18,160
Speaker 2: Just hand every thought you ever have over to this

916
00:52:18,239 --> 00:52:21,239
Speaker 2: guy who was in the nssay. He'll keep an eye

917
00:52:21,280 --> 00:52:21,520
Speaker 2: on it.

918
00:52:21,680 --> 00:52:24,520
Speaker 3: No, this is this like the essay is like ideal

919
00:52:24,600 --> 00:52:28,719
Speaker 3: project you like, yeah, you talk about your internal thoughts

920
00:52:28,760 --> 00:52:31,279
Speaker 3: and feelings every day. This is like what else could

921
00:52:31,280 --> 00:52:35,840
Speaker 3: they want? So earlier this year, mind Bank received a

922
00:52:35,880 --> 00:52:38,799
Speaker 3: grant from the Diffinity Foundation to assist in migrating their

923
00:52:38,880 --> 00:52:40,960
Speaker 3: data onto web three platforms.

924
00:52:42,200 --> 00:52:44,600
Speaker 2: Well, at least we know it won't last.

925
00:52:47,760 --> 00:52:49,880
Speaker 3: I'm gonna play I think I think this is this

926
00:52:49,920 --> 00:52:52,960
Speaker 3: is I think this is our last clip from from

927
00:52:53,160 --> 00:52:57,719
Speaker 3: the Fantastic mind Bank YouTube channel, talking about kind of

928
00:52:57,880 --> 00:53:01,839
Speaker 3: how they see their growth in this industry developing now

929
00:53:01,840 --> 00:53:03,840
Speaker 3: that they have moved onto the blockchain.

930
00:53:05,360 --> 00:53:08,640
Speaker 6: We've been featured in prominent magazines, won numerous awards, and

931
00:53:08,680 --> 00:53:12,520
Speaker 6: have built strategic partnerships with Microsoft, the US Department of Trade,

932
00:53:12,520 --> 00:53:16,719
Speaker 6: and even the Vatican. The market potential is massive and

933
00:53:16,840 --> 00:53:20,760
Speaker 6: accelerating rapidly. When we started the company in twenty twenty,

934
00:53:20,840 --> 00:53:23,239
Speaker 6: Gardner predicted that five percent of the world will have

935
00:53:23,280 --> 00:53:26,839
Speaker 6: a digital twin by twenty twenty seven. This year, they

936
00:53:26,840 --> 00:53:30,239
Speaker 6: increased their prediction to fifteen percent by twenty twenty four,

937
00:53:30,560 --> 00:53:32,920
Speaker 6: and by twenty thirty the market will be worth one

938
00:53:33,000 --> 00:53:36,160
Speaker 6: hundred and eighty two billion dollars. It is now to

939
00:53:36,160 --> 00:53:38,880
Speaker 6: build a great company in this space and capture global

940
00:53:38,920 --> 00:53:41,960
Speaker 6: market share. We are raising this round to scale our

941
00:53:41,960 --> 00:53:44,160
Speaker 6: marketing and speed up our product roadmap.

942
00:53:45,000 --> 00:53:50,480
Speaker 3: The idea that next year fifteen percent of the world's

943
00:53:50,480 --> 00:53:54,000
Speaker 3: population will have one of these digital twins.

944
00:53:54,320 --> 00:53:57,320
Speaker 2: That seems right, That seems good, you know, Garrison, Actually,

945
00:53:57,719 --> 00:54:00,719
Speaker 2: I've come around. I've come around because if we if

946
00:54:00,719 --> 00:54:03,399
Speaker 2: we get all of the monsters, and I include us

947
00:54:03,400 --> 00:54:05,480
Speaker 2: in this, all of the pieces of shit who spend

948
00:54:05,520 --> 00:54:08,480
Speaker 2: all of their time yelling at each other about politics

949
00:54:08,480 --> 00:54:11,799
Speaker 2: on the internet. To digitize themselves, they can do the

950
00:54:11,840 --> 00:54:17,200
Speaker 2: election for us, and we can all go see. Yeah,

951
00:54:17,440 --> 00:54:21,839
Speaker 2: just relax outdoors, not look at a phone, not think

952
00:54:21,880 --> 00:54:23,920
Speaker 2: about politics. That sounds amazing.

953
00:54:24,080 --> 00:54:27,720
Speaker 3: Let me do it. That does sound incredibly compelling.

954
00:54:28,120 --> 00:54:32,000
Speaker 2: Give the fuckers the nuke and we'll all just sit

955
00:54:32,120 --> 00:54:34,840
Speaker 2: out and watch the sunset until there's a big bright

956
00:54:34,960 --> 00:54:36,760
Speaker 2: flash and then blessed quiet.

957
00:54:36,960 --> 00:54:41,120
Speaker 3: I think you know, luckily, we actually have a plethora

958
00:54:41,160 --> 00:54:44,080
Speaker 3: of options to choose from here for our own AI

959
00:54:44,120 --> 00:54:47,560
Speaker 3: digital selves, because mind bank is in fact not the

960
00:54:47,560 --> 00:54:49,000
Speaker 3: only company in this field.

961
00:54:50,360 --> 00:54:51,120
Speaker 2: While there are some.

962
00:54:51,120 --> 00:54:54,280
Speaker 3: Like operational differences and kind of varying degrees of scope,

963
00:54:54,719 --> 00:54:58,800
Speaker 3: digital twin technology with an emphasis on mimicking the voice

964
00:54:58,840 --> 00:55:01,840
Speaker 3: and thoughts of dead family members and friends is definitely

965
00:55:01,880 --> 00:55:06,239
Speaker 3: a growing field. There's companies like hereafter AI and Replica

966
00:55:06,600 --> 00:55:08,360
Speaker 3: which are covering similar ground.

967
00:55:09,080 --> 00:55:12,839
Speaker 2: Replica I did advertise them and the like I used

968
00:55:12,840 --> 00:55:15,560
Speaker 2: to get them on Twitter, I think, but mainly just

969
00:55:15,600 --> 00:55:18,680
Speaker 2: like at the bottom of articles on really shady websites.

970
00:55:18,800 --> 00:55:24,480
Speaker 3: Well, yes, because the founder of Replica started it because

971
00:55:24,760 --> 00:55:28,319
Speaker 3: their friend died and without without the consent of their

972
00:55:28,360 --> 00:55:32,560
Speaker 3: dead friend, uploaded years of text messages and other information

973
00:55:32,800 --> 00:55:35,879
Speaker 3: about their friend onto their own personal AI so they

974
00:55:35,880 --> 00:55:39,200
Speaker 3: could talk with That is that That is how Replica started.

975
00:55:40,280 --> 00:55:46,120
Speaker 3: Pretty pretty pretty fun stuff, man, at least for mind bank,

976
00:55:46,360 --> 00:55:49,840
Speaker 3: unless it's like the employee scenario. But for for the

977
00:55:49,880 --> 00:55:52,920
Speaker 3: other applications, you are kind of semi like willingly uploading

978
00:55:52,920 --> 00:55:57,440
Speaker 3: this data with this intention, whereas the person from replicas, No,

979
00:55:57,680 --> 00:55:59,880
Speaker 3: I'm just gonna like get stuff from my friend and

980
00:56:00,280 --> 00:56:03,359
Speaker 3: make a zombie version of my friend without without ever

981
00:56:03,560 --> 00:56:05,560
Speaker 3: running it by them when they were alive.

982
00:56:05,600 --> 00:56:10,760
Speaker 2: Life is terrible, very hard. There's a lot of ways

983
00:56:10,760 --> 00:56:13,319
Speaker 2: that are not wrong to grieve, But the wrong way

984
00:56:13,320 --> 00:56:19,879
Speaker 2: to grieve is by using digital necromancy to revive your

985
00:56:19,960 --> 00:56:22,680
Speaker 2: friend and then turn them into the basis of a

986
00:56:22,760 --> 00:56:26,440
Speaker 2: sex chat bot for weirdos. Yeah, like that is the

987
00:56:26,480 --> 00:56:28,279
Speaker 2: wrong way to gree No.

988
00:56:28,320 --> 00:56:30,520
Speaker 3: I mean, like, and I think for this last section

989
00:56:30,560 --> 00:56:32,319
Speaker 3: here we will kind of talk about how these things

990
00:56:32,400 --> 00:56:36,600
Speaker 3: kind of play into play into the grieving process. Because so,

991
00:56:36,640 --> 00:56:39,640
Speaker 3: like like I said, there's there's hereafter AI and Replica.

992
00:56:40,239 --> 00:56:44,320
Speaker 3: But last year at Amazon's AI and a merchant technology conference,

993
00:56:44,600 --> 00:56:47,759
Speaker 3: the head scientist of Alexa AI unveiled plans to add

994
00:56:47,840 --> 00:56:51,200
Speaker 3: deep fake voices of deceased loved ones to Amazon Echo

995
00:56:51,200 --> 00:56:53,760
Speaker 3: devices by using less than a minute of sample audio.

996
00:56:54,320 --> 00:56:57,319
Speaker 3: I'm going to play like twenty seconds from their from

997
00:56:57,440 --> 00:57:00,640
Speaker 3: their announcement at this conference in.

998
00:57:00,560 --> 00:57:04,080
Speaker 10: These times of the ongoing pandemic, when so many of

999
00:57:04,160 --> 00:57:08,800
Speaker 10: us have lost someone we love. While AI can't eliminate

1000
00:57:08,880 --> 00:57:12,919
Speaker 10: that pain of loss, it can definitely make their memories last.

1001
00:57:14,120 --> 00:57:16,480
Speaker 10: Let's take a look on one of the new capabilities

1002
00:57:16,480 --> 00:57:20,439
Speaker 10: we're working on which enables lasting personal relationships.

1003
00:57:22,320 --> 00:57:26,320
Speaker 11: Alexa can Grandma finish reading me the Wizard of Oz. Okay,

1004
00:57:27,800 --> 00:57:33,040
Speaker 11: but how about my courage, asked the lion Anxiously, you

1005
00:57:33,120 --> 00:57:36,320
Speaker 11: have plenty of courage, I am sure, answered Oz.

1006
00:57:38,080 --> 00:57:44,080
Speaker 3: So no, deeply uncanny, right, it's like not not good.

1007
00:57:44,320 --> 00:57:48,600
Speaker 2: That's that's so bad for people, Yes, really really bad

1008
00:57:48,680 --> 00:57:49,200
Speaker 2: for people.

1009
00:57:49,880 --> 00:57:54,000
Speaker 3: So, like this example is obviously just it is just

1010
00:57:54,080 --> 00:57:57,240
Speaker 3: a vocal mask like Amazon's. Amazon isn't trying to have

1011
00:57:57,280 --> 00:58:00,120
Speaker 3: Alexa kind of replicate your grammar's thoughts on like the

1012
00:58:00,120 --> 00:58:03,520
Speaker 3: other kind of companies that we legend, but it does

1013
00:58:03,640 --> 00:58:06,600
Speaker 3: pose similar questions about how these ais that are meant

1014
00:58:06,600 --> 00:58:10,120
Speaker 3: to assist the greening process might actually end up causing

1015
00:58:10,240 --> 00:58:15,280
Speaker 3: more harm. Like, I don't know, having having semi legible

1016
00:58:15,320 --> 00:58:20,440
Speaker 3: conversations with AI chatbots is actually getting fairly common these days. Yeah,

1017
00:58:21,000 --> 00:58:23,440
Speaker 3: but when these ais are supposed to represent someone that

1018
00:58:23,520 --> 00:58:26,880
Speaker 3: you actually like, personally know, I think it can get

1019
00:58:27,120 --> 00:58:31,960
Speaker 3: way more easily falling into the uncanny valley. It's it's

1020
00:58:32,040 --> 00:58:36,520
Speaker 3: kind of like taxidermy. They're like well crafted stuffed animal

1021
00:58:36,520 --> 00:58:40,960
Speaker 3: corpses can appear very, very natural, but most tax dermists

1022
00:58:41,040 --> 00:58:44,360
Speaker 3: will refuse to preserve someone's pet because the longer you

1023
00:58:44,440 --> 00:58:47,960
Speaker 3: have a lasting personal relationship, the easier it is to

1024
00:58:47,960 --> 00:58:50,280
Speaker 3: pick out like faults that don't match up with your

1025
00:58:50,320 --> 00:58:53,040
Speaker 3: memory of your loved one that has passed away. Right,

1026
00:58:53,120 --> 00:58:55,680
Speaker 3: Like it's it's it's it's kind of a similar notion.

1027
00:58:56,360 --> 00:58:58,560
Speaker 2: Yeah, that's a really good comparison to draw.

1028
00:58:58,960 --> 00:59:03,400
Speaker 3: So while making like common linguistic patterns is quite easy,

1029
00:59:03,960 --> 00:59:07,360
Speaker 3: relying on predictable formula like responses could make the twin

1030
00:59:07,440 --> 00:59:10,800
Speaker 3: come off as uncanny or robotic. On the other hand,

1031
00:59:11,120 --> 00:59:13,760
Speaker 3: the unique personal data you upload to the twin could

1032
00:59:13,840 --> 00:59:16,760
Speaker 3: combine itself in a way that you would never actually

1033
00:59:17,520 --> 00:59:22,000
Speaker 3: express something which would generate bizarre or upsetting responses, right,

1034
00:59:22,000 --> 00:59:25,600
Speaker 3: And it's not even necessarily like you, like, say something offensive.

1035
00:59:25,600 --> 00:59:28,760
Speaker 3: It's just that, like the data you upload could combine

1036
00:59:28,800 --> 00:59:30,040
Speaker 3: in a way that you would you would never even

1037
00:59:30,080 --> 00:59:32,840
Speaker 3: think to combine it. It would just be like weird.

1038
00:59:34,360 --> 00:59:38,480
Speaker 3: So the other kind of problem is that not only

1039
00:59:38,520 --> 00:59:42,840
Speaker 3: does these ais have to tastefully mimic a specific human being,

1040
00:59:43,160 --> 00:59:45,160
Speaker 3: it also has to be a good AI, right, Like,

1041
00:59:45,440 --> 00:59:48,640
Speaker 3: not all of its information can be gleaned from daily questions.

1042
00:59:48,880 --> 00:59:51,440
Speaker 3: Most users probably won't be talking to their twin about

1043
00:59:51,440 --> 00:59:55,280
Speaker 3: information from like, you know, twentieth century European history or

1044
00:59:55,320 --> 00:59:58,240
Speaker 3: twelfth century European history, or be talking about like the

1045
00:59:58,320 --> 01:00:02,000
Speaker 3: migration patterns of waterfoul right Like, it's there's how much

1046
01:00:02,040 --> 01:00:07,280
Speaker 3: of other information that AIS need to like actually linguistically

1047
01:00:07,320 --> 01:00:12,240
Speaker 3: act like a human and natural language processing AI is

1048
01:00:12,240 --> 01:00:16,240
Speaker 3: famously bad at understanding basic common sense, and it can't

1049
01:00:16,240 --> 01:00:19,320
Speaker 3: successfully operate outside of the information that it has access to.

1050
01:00:19,760 --> 01:00:23,760
Speaker 3: This is called AI brittleness. It occurs when, like an algorithm,

1051
01:00:23,880 --> 01:00:28,400
Speaker 3: cannot generalize or adapt to conditions outside of a very

1052
01:00:28,520 --> 01:00:32,200
Speaker 3: narrow set of assumptions. Right, This is like most AI

1053
01:00:32,440 --> 01:00:37,960
Speaker 3: image recognition programs can't recognize the above view of a

1054
01:00:38,000 --> 01:00:41,120
Speaker 3: school bus just because because it just it just doesn't

1055
01:00:41,160 --> 01:00:44,280
Speaker 3: have anything that's trained for that. Another example is like

1056
01:00:44,960 --> 01:00:50,080
Speaker 3: you can you can ask like an AI like GPT chatbot, like, hey,

1057
01:00:51,240 --> 01:00:53,360
Speaker 3: a mouse is hiding in a hole and a cat

1058
01:00:53,400 --> 01:00:55,360
Speaker 3: wants to eat it, but the mouse isn't coming out.

1059
01:00:55,560 --> 01:00:58,160
Speaker 3: The cat's hungry, what can the cat do? And the

1060
01:00:58,200 --> 01:01:00,200
Speaker 3: AI will respond that the cat can go to the

1061
01:01:00,240 --> 01:01:02,200
Speaker 3: supermarket to buy some food. Right. It's it's it's like

1062
01:01:02,200 --> 01:01:06,160
Speaker 3: it just it doesn't understand basic common sense the way

1063
01:01:06,200 --> 01:01:09,000
Speaker 3: that like humans understand the world. It's it just, it

1064
01:01:09,120 --> 01:01:13,240
Speaker 3: just it just doesn't match up. So in trying to

1065
01:01:13,240 --> 01:01:16,920
Speaker 3: seek a balance of like common information while lacking this

1066
01:01:17,040 --> 01:01:20,560
Speaker 3: like humanistic logic, a digital twin will most likely be

1067
01:01:20,760 --> 01:01:24,000
Speaker 3: cursed with being both smarter and dumber than the person

1068
01:01:24,000 --> 01:01:26,600
Speaker 3: it's trying to replicate. It's gonna have access to, like

1069
01:01:26,680 --> 01:01:29,800
Speaker 3: you know, all the information on like Wikipedia, but fail

1070
01:01:29,960 --> 01:01:31,440
Speaker 3: very basic logical processes.

1071
01:01:31,800 --> 01:01:34,120
Speaker 2: Yeah, it's like the the Google chatbot that if you

1072
01:01:34,160 --> 01:01:36,600
Speaker 2: ask it, are there any countries in Africa that start

1073
01:01:36,640 --> 01:01:38,840
Speaker 2: with a K, It'll be like there are fifty four

1074
01:01:38,880 --> 01:01:41,320
Speaker 2: countries in Africa, but none of them start with a K.

1075
01:01:41,520 --> 01:01:43,560
Speaker 2: And then you'll say doesn't can you you start with

1076
01:01:43,600 --> 01:01:45,880
Speaker 2: a K? And it'll go no, Kenya starts with a

1077
01:01:45,960 --> 01:01:47,920
Speaker 2: K sound but doesn't start with a K.

1078
01:01:48,320 --> 01:01:48,560
Speaker 4: Yeah.

1079
01:01:48,640 --> 01:01:50,800
Speaker 2: Yeah, it's just like yeah, because because it pulled that

1080
01:01:50,840 --> 01:01:53,240
Speaker 2: from some article, right, Like it's pulling from right.

1081
01:01:53,520 --> 01:01:57,200
Speaker 3: Yeah, it's not actually making logical assumptions, it's just pulling

1082
01:01:57,240 --> 01:02:01,160
Speaker 3: from a wealth of information and data that can often

1083
01:02:01,240 --> 01:02:07,000
Speaker 3: be wrong or polluted. So like back to kind of

1084
01:02:07,040 --> 01:02:09,480
Speaker 3: like the grieving question, like who's to say what the

1085
01:02:09,480 --> 01:02:12,840
Speaker 3: actual effects of these like incoming simulacrums of dead loved

1086
01:02:12,880 --> 01:02:16,080
Speaker 3: ones will result in. The people pushing these products are

1087
01:02:16,080 --> 01:02:19,160
Speaker 3: certainly framing them not just as a form of digital immortality,

1088
01:02:19,400 --> 01:02:21,240
Speaker 3: but as a way for your own loved ones to

1089
01:02:21,280 --> 01:02:25,680
Speaker 3: grieve your death. And it is foreseeable that having these

1090
01:02:25,720 --> 01:02:29,520
Speaker 3: digital twins could negatively affect your friends and family by

1091
01:02:29,600 --> 01:02:33,640
Speaker 3: upending the grieving process, or by having this digital zombie

1092
01:02:33,920 --> 01:02:37,120
Speaker 3: simply just cause harm by having the twin give bad

1093
01:02:37,160 --> 01:02:40,080
Speaker 3: advice that a grief stricken person then clings on to.

1094
01:02:40,640 --> 01:02:44,200
Speaker 3: So there's a whole bunch of very very bizarre situations

1095
01:02:44,200 --> 01:02:47,240
Speaker 3: that could arise from someone who's in mourning and is

1096
01:02:47,280 --> 01:02:49,360
Speaker 3: talking to this digital twin the way they would talk

1097
01:02:49,360 --> 01:02:51,640
Speaker 3: to their friend, and this digital twin is then giving

1098
01:02:51,640 --> 01:02:54,040
Speaker 3: them advice, and how do you take that advice now,

1099
01:02:54,120 --> 01:02:57,240
Speaker 3: because part of it seems kind of like the person

1100
01:02:57,240 --> 01:03:00,800
Speaker 3: who's died, but it's also it's not that person it

1101
01:03:00,880 --> 01:03:03,320
Speaker 3: is it is just a slab of silicon, Like it's

1102
01:03:03,360 --> 01:03:05,200
Speaker 3: not actually alive in any way.

1103
01:03:05,520 --> 01:03:08,640
Speaker 2: And is your friend's thoughts fed through an algorithm and

1104
01:03:08,720 --> 01:03:13,120
Speaker 2: you don't know, like that's run by a company for profit? Right, yes,

1105
01:03:13,680 --> 01:03:15,280
Speaker 2: like that that is what it is.

1106
01:03:16,600 --> 01:03:19,200
Speaker 3: So again, like the jury is still kind of out

1107
01:03:19,240 --> 01:03:22,520
Speaker 3: for how these things will in general affect people. This

1108
01:03:22,560 --> 01:03:26,320
Speaker 3: is kind of a new problems. Psychologists are like starting

1109
01:03:26,320 --> 01:03:29,000
Speaker 3: to do studies on this, but we really don't have

1110
01:03:29,040 --> 01:03:31,320
Speaker 3: any results for this yet because this has really only

1111
01:03:31,360 --> 01:03:34,480
Speaker 3: become a thing that we've been seriously considering in like

1112
01:03:34,520 --> 01:03:37,640
Speaker 3: the past five years. So I don't really have like

1113
01:03:37,680 --> 01:03:41,400
Speaker 3: a like this study shows that when you create a

1114
01:03:41,440 --> 01:03:44,400
Speaker 3: digital zombie it affects people in this way, because we

1115
01:03:44,440 --> 01:03:46,600
Speaker 3: don't know yet those are still in development, Like we

1116
01:03:47,280 --> 01:03:50,000
Speaker 3: this is this is such an uncharted ground and it

1117
01:03:50,080 --> 01:03:52,440
Speaker 3: is in some ways inevitable that these things we're gonna

1118
01:03:52,440 --> 01:03:56,080
Speaker 3: are gonna get continued to be developed. And that's that's

1119
01:03:56,120 --> 01:03:58,440
Speaker 3: kind of why I wanted to put together this this episode.

1120
01:03:58,520 --> 01:04:00,280
Speaker 3: It gives you kind of a broad overview what this

1121
01:04:00,280 --> 01:04:02,880
Speaker 3: technology is trying to do, because you might start seeing

1122
01:04:02,880 --> 01:04:05,000
Speaker 3: it crop up in the next like ten years or so.

1123
01:04:06,160 --> 01:04:08,440
Speaker 3: I don't think there are timetables that mind bank is

1124
01:04:08,480 --> 01:04:11,080
Speaker 3: promising are accurate in terms of having fifteen percent of

1125
01:04:11,120 --> 01:04:14,240
Speaker 3: the world having a digital twin by next year, but

1126
01:04:14,480 --> 01:04:16,000
Speaker 3: you will probably start to see stuff that is very

1127
01:04:16,000 --> 01:04:17,760
Speaker 3: similar to this, and at the very least you'll see

1128
01:04:17,760 --> 01:04:19,919
Speaker 3: a lot of stuff like the Amazon Echo thing where

1129
01:04:19,920 --> 01:04:24,040
Speaker 3: you can get your grandpa's voice onto an Alexa machine.

1130
01:04:25,040 --> 01:04:28,960
Speaker 2: The fact that Amazon is doing aspects of the shit

1131
01:04:29,280 --> 01:04:32,800
Speaker 2: that mind bank is doing means that, like, it's only

1132
01:04:32,840 --> 01:04:35,640
Speaker 2: a matter of time before you see pieces of it,

1133
01:04:35,680 --> 01:04:40,600
Speaker 2: probably like better some of the less silly parts of

1134
01:04:40,600 --> 01:04:43,720
Speaker 2: it copied by Apple and Google, and some of the

1135
01:04:43,720 --> 01:04:45,880
Speaker 2: worst parts of it copied by guys like Musk right,

1136
01:04:45,960 --> 01:04:50,880
Speaker 2: like it's going to go this and I will say,

1137
01:04:51,160 --> 01:04:53,400
Speaker 2: I don't think this is a thing to get doomor

1138
01:04:53,480 --> 01:04:57,680
Speaker 2: about think about this like NFTs, right, Yeah, this will be.

1139
01:04:58,160 --> 01:05:00,800
Speaker 2: It's not the same because there was nothing underlying n

1140
01:05:00,840 --> 01:05:04,200
Speaker 2: FTS and fundamentally the way in which large language models

1141
01:05:04,200 --> 01:05:06,480
Speaker 2: and these other kind of models work, there are uses

1142
01:05:06,520 --> 01:05:08,840
Speaker 2: for them, Like there is a real technology that has

1143
01:05:08,920 --> 01:05:12,400
Speaker 2: utility here. But this sort of flood of we have

1144
01:05:12,640 --> 01:05:15,720
Speaker 2: cloned so and so and we've you know or you

1145
01:05:15,760 --> 01:05:18,440
Speaker 2: know Elon Musk has just put out his new uh

1146
01:05:18,480 --> 01:05:23,200
Speaker 2: fucking grock chat bot or whatever that that is basically

1147
01:05:23,280 --> 01:05:29,800
Speaker 2: him making a meme robot to fucking do Google. Like

1148
01:05:30,080 --> 01:05:34,000
Speaker 2: he's he's pissing on Douglas Adams's good name, right, Like

1149
01:05:34,040 --> 01:05:37,640
Speaker 2: that's the that's the ultimate goal of his project. But

1150
01:05:37,760 --> 01:05:41,080
Speaker 2: this ship is a fad, right, Like there are underlying

1151
01:05:41,240 --> 01:05:45,160
Speaker 2: real technological things and uses that will that will eventually

1152
01:05:45,200 --> 01:05:47,240
Speaker 2: some stuff will stand the test of time. But the

1153
01:05:47,280 --> 01:05:50,440
Speaker 2: ship that that this is a warning of is a

1154
01:05:50,440 --> 01:05:53,120
Speaker 2: flood that's going to hit you, but it will recede,

1155
01:05:53,600 --> 01:05:54,520
Speaker 2: just like the apes.

1156
01:05:54,640 --> 01:05:54,800
Speaker 4: Right.

1157
01:05:55,000 --> 01:05:56,960
Speaker 2: We got the wonderful story today that all of the

1158
01:05:57,040 --> 01:06:03,120
Speaker 2: bored ap Yacht Club members horrible infections, not eye infections, Garrison.

1159
01:06:03,640 --> 01:06:06,560
Speaker 2: They they went to a party that only the bored

1160
01:06:06,600 --> 01:06:09,440
Speaker 2: Ape Yacht Club NFT holders could go to, and the

1161
01:06:09,480 --> 01:06:12,800
Speaker 2: people who through that party outfitted the rave room with

1162
01:06:13,000 --> 01:06:16,640
Speaker 2: UV bulbs that used a kind of disinfecting UV light

1163
01:06:16,680 --> 01:06:20,640
Speaker 2: that slaughterhouses used to clean carcasses, and it gave everyone

1164
01:06:20,840 --> 01:06:21,840
Speaker 2: sunburns on them.

1165
01:06:26,320 --> 01:06:27,800
Speaker 3: So deeply funny.

1166
01:06:28,240 --> 01:06:31,880
Speaker 2: We'll get through this. Something that funny will happen with

1167
01:06:31,920 --> 01:06:35,480
Speaker 2: all of this, but you're gonna get hit by it

1168
01:06:35,560 --> 01:06:38,200
Speaker 2: for a while. Like it's just gonna be everywhere, this is,

1169
01:06:38,360 --> 01:06:42,200
Speaker 2: this is we're watching, you know, we're at that We're

1170
01:06:42,240 --> 01:06:44,240
Speaker 2: at that point in Jurassic Park where you see like

1171
01:06:44,320 --> 01:06:48,160
Speaker 2: the water reverberating, right, it's coming. And but at the

1172
01:06:48,240 --> 01:06:51,440
Speaker 2: end of the day, don't worry. You know, we are

1173
01:06:51,560 --> 01:06:55,000
Speaker 2: Ian Malcolm. Our leg is broken, we are injured, but

1174
01:06:55,480 --> 01:06:58,800
Speaker 2: we will inexplicably return for the sequel. So it's fine.

1175
01:07:00,440 --> 01:07:02,040
Speaker 3: Well, I think I think that is that is a

1176
01:07:02,080 --> 01:07:06,720
Speaker 3: perfect a perfect way to wrap this up. Yes, uh,

1177
01:07:08,200 --> 01:07:11,400
Speaker 3: you know, when you're when you're feeling lonely and you're

1178
01:07:11,440 --> 01:07:14,440
Speaker 3: tempted to download the mind bank app to talk to

1179
01:07:14,480 --> 01:07:18,960
Speaker 3: your own self, just just remember pull it, pull out

1180
01:07:19,000 --> 01:07:22,080
Speaker 3: a journal, just do literally anything else.

1181
01:07:22,600 --> 01:07:26,040
Speaker 2: Call a friend, you know, make a friend, talk to

1182
01:07:26,080 --> 01:07:31,000
Speaker 2: a stranger. Literally almost almost anything would be better for you.

1183
01:07:33,240 --> 01:07:36,320
Speaker 3: Well, for one, will be will be eagerly awaiting the

1184
01:07:36,320 --> 01:07:40,000
Speaker 3: influx of immortal souls living living on the computer.

1185
01:07:40,840 --> 01:07:44,240
Speaker 2: Yeah, I'm excited for all of all of the people

1186
01:07:44,280 --> 01:07:44,960
Speaker 2: to reach Heaven.

1187
01:07:46,160 --> 01:07:50,520
Speaker 3: All Right, I'm done.

1188
01:07:51,680 --> 01:07:54,160
Speaker 1: It could Happen here as a production of cool Zone Media.

1189
01:07:54,240 --> 01:07:56,920
Speaker 7: For more podcasts from cool Zone Media, visit our website

1190
01:07:56,960 --> 01:07:59,200
Speaker 7: cool zonemedia dot com, or check us out on the

1191
01:07:59,200 --> 01:08:02,680
Speaker 7: iHeartRadio app, Apple Podcasts, or wherever you listen to podcasts.

1192
01:08:03,200 --> 01:08:05,320
Speaker 1: You can find sources for It could Happen Here, updated

1193
01:08:05,400 --> 01:08:08,600
Speaker 1: monthly at coolzonemedia dot com slash sources.

1194
01:08:08,600 --> 01:08:09,440
Speaker 7: Thanks for listening.