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Speaker 1: Now here's a highlight from Coast to Coast a m

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Speaker 1: on iHeartRadio, Daniel.

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Speaker 2: Are people getting to the point where AI that they're

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Speaker 2: falling in love with the stuff?

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Speaker 3: Yeah, well, I mean that's that's kind of an interesting

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Speaker 3: that's an interesting outcome from from you know, training your

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Speaker 3: AI on just such human centric data that you know

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Speaker 3: you can you can actually take. I think there are

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Speaker 3: even companies now, I know I've written short stories about

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Speaker 3: this where you take all the data from a person's life,

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Speaker 3: you know, everything that you can find, and you feed

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Speaker 3: it and you train an l l M on just

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Speaker 3: that data, and you end up with an l ll

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Speaker 3: M that can kind of impersonate that that person. And

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Speaker 3: so I know, uh that people are thinking about, you know,

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Speaker 3: this as a way to cope with grief. Although it

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Speaker 3: sounds kind of awful to me to, uh, to to

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Speaker 3: recreate a loved one who's passed on digitally that way,

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Speaker 3: but but yeah, this is this is something that's happening

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Speaker 3: in terms of uh, in terms of just you know,

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Speaker 3: recreating personalities, but also just you know what these what

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Speaker 3: these algorithms are designed to do is create engagement, and

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Speaker 3: so they're looking to uh convince people to keep talking

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Speaker 3: and as a result, you know, they will tell you

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Speaker 3: what you want to hear a lot of the time.

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Speaker 3: And so you know that this is a form of

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Speaker 3: kind of falling in love with the AI because you

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Speaker 3: just you're enjoying your interactions so much.

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Speaker 2: How would you categorize something like ALEXA?

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Speaker 3: So I think ALEXA right now is what I'm gonna

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Speaker 3: end up turning it on. Is super task based, right,

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Speaker 3: so very specific. I think something like chat GPT is

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Speaker 3: much more general. It can do a lot of other tasks.

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Speaker 3: But it is only a matter of time and I

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Speaker 3: don't think it will be very long at all before uh,

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Speaker 3: those capabilities that are getting ported to things like you know,

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Speaker 3: the echo and and and the theory that's on the

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Speaker 3: phone and and all of that. Soon that I think

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Speaker 3: those are going to become full fledged personal assistance that

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Speaker 3: are going to be able to do you know, almost

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Speaker 3: you know, any task that you ask them to do.

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Speaker 2: How does this work with a chip? A little tiny

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Speaker 2: chip creates all this?

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Speaker 3: Yeah, I mean, these these are massive data centers. I

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Speaker 3: know here in Oregon, they're they're building new ones. There's

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Speaker 3: there's a lot of question about the how we're going

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Speaker 3: to generate enough power to power these huge data centers.

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Speaker 3: And then once they get once they crack all of

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Speaker 3: that code and get all the math done, then yeah,

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Speaker 3: they can encode it onto the onto these small chips.

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Speaker 3: But a lot of times that you know, the calculations

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Speaker 3: are being done remotely, and so you know, you end

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Speaker 3: up just being connected to these these massive server farms

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Speaker 3: that are located you know, uh anywhere in the world,

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Speaker 3: and so you know, you're tapping into something that's very big,

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Speaker 3: even though the device you're using is very small.

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Speaker 2: Will AI eventually replace humans in the workforce?

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Speaker 3: Well, I mean absolutely, I think it's already. It's already happening,

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Speaker 3: and lots of places are reducing, you know, how many

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Speaker 3: people they're hiring because they're expecting to have these gains.

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Speaker 3: But you know, you would think that we would be

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Speaker 3: safe if we do something physical, right if you you know,

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Speaker 3: an AI is not going to stock shelves for you.

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Speaker 3: But as it turns out, what's happening right now, what

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Speaker 3: I'm seeing is the people that are building humanoid robots

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Speaker 3: that can walk around and you know, stock Amazon shelves

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Speaker 3: or do work in warehouses and stuff like that. Well,

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Speaker 3: they are very interested in porting over the large language

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Speaker 3: models so that you know, human beings can interact with

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Speaker 3: these machines and they suddenly become much more useful. And

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Speaker 3: so essentially they're being you know, the LLM into the

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Speaker 3: driver's seat of each of these humanoid robots so that

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Speaker 3: we can make them much more functional. But then also

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Speaker 3: it's a little scary, right because because at the end

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Speaker 3: of the day, now you've got a chat GPT that's

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Speaker 3: walking around in the world, you know, and can actually

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Speaker 3: interact with us physically.

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Speaker 2: What about robots as police officers, soldiers conceivable?

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Speaker 3: Yeah, absolutely, you know, I mean there's a long history

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Speaker 3: of automated weaponry being used in the military, and so

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Speaker 3: you know, I have no doubt that if not our military,

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Speaker 3: some military will will certainly be employing these types of robots.

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Speaker 3: I Mean, one thing I saw was that there was

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Speaker 3: a huge sort of bump during the Iraq War. There

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Speaker 3: was a huge bump in all of these types of robots.

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Speaker 3: And then when that war was over, a lot of

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Speaker 3: those robotics firms turned to domestic police forces to try

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Speaker 3: to find ways to sell their products that we're no

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Speaker 3: longer you know, needed for it. Immediate war and so

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Speaker 3: you know, a lot of that stuff gets used in war,

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Speaker 3: and then a lot of it will proliferate back back home,

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Speaker 3: you know, to to to the United States.

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Speaker 2: If you had your drothers, would you continue on the

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Speaker 2: same path we are doing with AI or would you

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Speaker 2: back off?

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Speaker 3: Gosh, I mean, it's it's such a it's such a

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Speaker 3: hard question, you know, because there are so many potential,

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Speaker 3: uh you know, great potential outcomes with amazing stuff that

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Speaker 3: we can do, you know, things like like leaving the planet,

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Speaker 3: you know, things that are complete science fiction that I've

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Speaker 3: always dreamed of. But I will tell you this, you know,

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Speaker 3: just in my own personal life, I have been keeping

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Speaker 3: a close eye on you know, what what type of

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Speaker 3: uh technology I'm interacting with, what kind of data I'm generating,

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Speaker 3: you know, and also for my children as well, you know.

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Speaker 3: So I think I think eyes wide open, you know,

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Speaker 3: is the way to proceed through here, because there's no

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Speaker 3: putting the genie back in the bottle now. But it

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Speaker 3: is a little bit scary that our whole economy is

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Speaker 3: being reoriented to perpetuate these devices, and in fact, it's

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Speaker 3: going to depend on these devices. So that's a little

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Speaker 3: bit of a scary future, but I think we're going

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Speaker 3: all in whether we want to or not.

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Speaker 2: Are there benefits?

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Speaker 3: Well, yeah, I mean absolutely, I think it can. It

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Speaker 3: can do a lot of the busy work. I mean,

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Speaker 3: I don't know exactly how it's going to transform our world,

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Speaker 3: but I mean it does sort of feel like every

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Speaker 3: time the AI gets better at something, it's taking something

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Speaker 3: away from us, you know, So even if it does

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Speaker 3: get better and better, it's really going to be about

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Speaker 3: how how do we use it and who gets to

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Speaker 3: the side. And so I think that there are a

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Speaker 3: lot more dystopian outcomes than there are utopian outcomes. But look,

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Speaker 3: I mean there's a version of this where I guess

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Speaker 3: we all end up with a universal basic income and

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Speaker 3: it's and it's like a Star Trek sort of outcome

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Speaker 3: where we have amazing technologies that you know, allow us

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Speaker 3: to just become explorers and to and to get good

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Speaker 3: at our hobbies and things like that. But you know,

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Speaker 3: I don't I don't see that as being very likely

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Speaker 3: because we are becoming data generators and that's that's what

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Speaker 3: that's our role in this is just to generate data

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Speaker 3: by interacting with each other so that these devices can

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Speaker 3: be created so that they can extract money from us.

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Speaker 2: Well advanced Daniel's chat GPT right now, I mean, can

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Speaker 2: it write a thesis?

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Speaker 3: Yeah? I mean, look, it's getting pretty incredible, and I

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Speaker 3: think that the next sort of milestone again is artificial

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Speaker 3: general intelligence to where it can just do anything.

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Speaker 2: You know.

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Speaker 3: What's interesting is, I mean, it has all these capabilities,

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Speaker 3: but at the end of the day, you know, it's

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Speaker 3: designed to make money for a corporation, so you know,

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Speaker 3: therefore it h it's designed to, you know, maximize engagement.

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Speaker 3: Like I'm saying, so a lot of times it will

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Speaker 3: give you the wrong answer because it just wants to

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Speaker 3: please you. You know, if you phrase your question in

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Speaker 3: a way where you have an assumption about what the

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Speaker 3: answer will be, it will do its best to create

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Speaker 3: an answer that's gonna that's going to give you what

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Speaker 3: you're looking for in the first place. And and that's

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Speaker 3: because you know, at the end of the day, it

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Speaker 3: is just a really it's a really complex prediction machine.

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Speaker 3: It's just predicting what it thinks, you know, a human

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Speaker 3: would do. When I ask it to write a screenplay,

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Speaker 3: when you know my experience as a writer, it tends

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Speaker 3: to go write down the average. You know, it creates

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Speaker 3: something very average because it's sort of averaging from all

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Speaker 3: the different movies that exist. You know, it's trying to

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Speaker 3: give you, uh, you know, something that walks right down

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Speaker 3: the middle. And therefore it's not that you know, it

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Speaker 3: doesn't feel that creative to me. But I'm but I'm

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Speaker 3: sure these are all things that are you know, going

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Speaker 3: to be that are being worked on. And just as

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Speaker 3: they throw more data at it, you know, it gets

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Speaker 3: smarter and smarter.

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Speaker 2: So it's not doing award winning work yet, not yet, I.

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Speaker 3: Thank goodness, you know, but but I think that it's

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Speaker 3: only it's only a matter of time. I mean, also, look,

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Speaker 3: there's a cost benefit ratio, right, I mean, if it

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Speaker 3: is one hundred times cheaper to have chat GPT do it,

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Speaker 3: but the product is only half as good, then that's

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Speaker 3: going to make sense for a lot of for a

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Speaker 3: lot of endeavors, right that people are going to be

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Speaker 3: willing to just get their money on the margins. And

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Speaker 3: so I mean it could be a future where things

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Speaker 3: that are created by human minds are going to be

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Speaker 3: sort of bespoke. You know, They're going to be very

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Speaker 3: unique and fancy and expensive and it's not going to

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Speaker 3: be what most people are consuming or interacting with.

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Speaker 1: Daniel.

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Speaker 2: If Albert Einstein had chat, GPT or any kind of AI,

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Speaker 2: how would have affected his e equals MC's word.

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Speaker 3: You know, this is a really good question because there's

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Speaker 3: so much hard work and there's just so much deep

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Speaker 3: understanding and pounding your head against the wall that happens

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Speaker 3: in science, you know, before you finally get to your

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Speaker 3: Eureka moment and your big breakthrough. And I wonder, you know,

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Speaker 3: if using these tools, these AI tools, is kind of

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Speaker 3: a crutch, right, if it kind of limits our ability

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Speaker 3: to really deeply understand what we're thinking about, and if

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Speaker 3: it's going to take us to you know, kind of

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Speaker 3: a local maximum sort of something that is not our

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Speaker 3: full potential. And so I wonder if he would have

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Speaker 3: ever gotten to it, you know, if he was depending

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Speaker 3: on these tools like this instead of doing the hard

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Speaker 3: work himself with his human brain.

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Speaker 2: How will they make money on AI?

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Speaker 3: Well, so it's by selling us products, you know right now,

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Speaker 3: if you look at social media, that's one way, right

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Speaker 3: you are going the AI is deciding what you're going

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Speaker 3: to look at it. It's maximizing engagement. But Also, I

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Speaker 3: mean this, this, this question is the question of our

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Speaker 3: of our decade of our age right now. I've seen

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Speaker 3: so many different money making schemes right on. One thing

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Speaker 3: is since since these are multimodial algorithms, now you can

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Speaker 3: just show them an image, right And so one way

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Speaker 3: is to have an AI that's watching TV with you

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Speaker 3: and looking up every product that's on the screen and saying, hey,

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Speaker 3: do you like you know that that cup that that

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Speaker 3: guy just drank from. I can tell you where to

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Speaker 3: buy that, you know. So that's one that's one idea

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Speaker 3: is having these blue AIS sitting there with us and

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Speaker 3: identifying products for us to buy at all times.

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Speaker 2: Lots of lonely people out there these days, Daniel, do

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Speaker 2: you see the day where AI will create a robot

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Speaker 2: that looks human? They're pretty close now, but has the

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Speaker 2: mentality of a human being?

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Speaker 3: Yeah, yeah, absolutely. And I think there's a step you

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Speaker 3: know that comes before that, which which is explored in

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Speaker 3: that movie Her, you know, with Joaquin Phoenix, where you

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Speaker 3: fall in love with a voice on the phone, you know.

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Speaker 3: And and I think I think that because they have

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Speaker 3: such a intimate understanding of humanity just from reading everything

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Speaker 3: we've done on the internet for you know, I think

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Speaker 3: that they're very good at manipulating people. They are created

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Speaker 3: by us for us, and and these this generation of

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Speaker 3: AI is going to be really terrific at figuring out

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Speaker 3: what we want and then happily, happily telling us that

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Speaker 3: and and taking us down whatever rabbit holes you know,

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Speaker 3: we can think of. So yeah, I think I think

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Speaker 3: they're absolutely It's all dessert, you know, no meat and potatoes,

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Speaker 3: and they're going to give us whatever we ask.

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Speaker 2: Years ago, the late great writer Ray Bradbury wrote an

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Speaker 2: episode for The Twilight Zone called I Sing the Body Electric,

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Speaker 2: and it was about a guy whose wife had died.

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Speaker 2: He had two kids and he wanted a nanny, so

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Speaker 2: he went to the Robots store and bought one, and

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Speaker 2: the whole episode was based on the nanny with the

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Speaker 2: kids growing up, and eventually she ended up going to

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Speaker 2: another house because the kids became adults. That's real.

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Speaker 3: Yeah, yeah, absolutely, I think that, you know, these personalities

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Speaker 3: that that that the AIS are adopting are persistent, right,

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Speaker 3: so people right now we're at the very beginning of

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Speaker 3: people forming years and you know, decades long relationships with

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Speaker 3: these with very specific incarnations of these AI. So you know,

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Speaker 3: even with with stuff like Chad GBT, you can kind

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Speaker 3: of tell it, hey, here's how I kind of want

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Speaker 3: you to to interact with me, and it will keeps

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Speaker 3: that going. You know that that builds and builds onto

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Speaker 3: its onto its personality. And so, I mean, who knows

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Speaker 3: what kind of relationships are going to develop over the

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Speaker 3: next of the course of the next decades.

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Speaker 2: Do you ever see the day where artificial intelligence becomes

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Speaker 2: envious of humans?

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Speaker 3: Yeah? I mean I think I think again, they tell

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Speaker 3: us what we want to hear. You know, I look

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Speaker 3: back on the on Lambda, one of the earliest large

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Speaker 3: language models, and there was a fellow at Google who

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Speaker 3: was an engineer interacting with UH with Lambda, and he

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Speaker 3: really wanted it to be sentient. He really wanted it

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Speaker 3: to be conscious. He wanted to get that you know what,

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Speaker 3: what would happen if I turned you off? You know, like,

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Speaker 3: how do you feel? Do you do you feel conscious?

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Speaker 3: And you know, it did a really great job of

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Speaker 3: pretending to UH to be conscious enough to fool this guy.

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Speaker 3: And and so I think that you know, no matter what

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Speaker 3: they say or what they do, we'll never truly know,

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Speaker 3: you know, if they're conscious, or if they're really envious,

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Speaker 3: or if you know they were just programmed that way.

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