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Right, so get, we're diving deep into AI today and asking you a question that's got a lot of people talking.

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Does AI actually need to experience reality in order to really, truly understand it?

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And we've got a whole bunch of research articles here.

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And one of the things that just kind of jumped out was this idea that computers can be

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so good at things like chess.

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Right.

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But then they just totally fail at things we humans find so simple, like driving.

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Yeah.

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It's kind of a paradox, wouldn't you say?

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It really is.

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And, you know, it gets to the core of how AI and human intelligence might be fundamentally different.

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Oh.

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You see, humans are constantly bombarded with sensory data all the time.

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Right.

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What we see, what we hear, what we feel.

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Yeah.

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Our brains process all that information so fast to make sense of the world.

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Wow.

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That's how we learn and adapt so quickly.

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So it's like our brains are just hardwired for learning in the real world from the get go.

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Absolutely.

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But AI systems, especially the ones that are getting all the attention these days,

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they seem to be really excelling in areas that are very language based.

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Yeah.

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I mean, look at these LLMs, these large language models.

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Right.

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They can write poems, generate code, even pass the bar exam.

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It's incredible.

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Yeah.

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So could language itself be the key to AI understanding reality?

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Maybe all that real world experience isn't actually necessary.

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Well, that's a really great question.

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Yeah.

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It's a question that has a lot of very smart people debating and...

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I bet.

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You know, language is definitely powerful.

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Yeah.

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It's how we communicate complex ideas, pass on knowledge.

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You could think of it as a sort of compressed code that contains a vast amount of information and

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wisdom.

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Right.

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But is that enough for AI to build a complete model of reality?

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Yeah.

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Well, that's where the debate gets really interesting.

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Yeah.

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Because even if an AI can process language, like a pro, does it actually understand what

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those words represent in the real world?

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That's the key.

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Like if you tell an LLM about a sunset, can it really grasp the beauty, the colors, the

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feeling of the warmth on your skin?

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That gets to the core of the argument for embodied AI.

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This is the idea that true intelligence actually requires some grounding in reality,

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whether it's physical or simulated.

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I see.

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The real world, with all its sights, sounds, smells, textures.

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It's so incredibly rich and complex in a way that language can only approximate.

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So you're saying even a really realistic virtual world could be enough for AI to develop that

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kind of understanding?

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It's a possibility, for sure.

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There are researchers working on creating just that highly detailed simulated environments

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where AI can interact with objects, experience physics, and learn through trial and error,

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much like humans do in the real world.

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Okay.

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So let's talk about this trial and error part for a second.

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Okay.

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You mentioned earlier that AI struggles with tasks that humans find intuitive, like driving

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or doing the dishes.

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Right.

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And that brings us to this thing called Moravex Paradox.

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Exactly.

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Moravex Paradox points out this fascinating disconnect.

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Computers can easily master tasks that we as humans consider mentally challenging,

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right?

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Like complex calculations or strategic thinking, but then they stumble when it comes to things

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that seem almost effortless for us.

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Okay.

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What?

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Like recognizing a face or navigating a cluttered room?

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Oh, so it's almost like they got all the brain power for complex reasoning, but they

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lacked the common sense that we developed just from living in the world.

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That's a great way to put it, yeah.

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But how does this paradox then inform this debate about embodied AI?

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What's the connection there?

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Well, Moravex Paradox really highlights the difference between the kind of intelligence

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that we've traditionally programmed into computers.

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Okay.

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Logical rule-based systems and the kind of intelligence that emerges from interacting

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with the physical world.

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Yeah.

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Think about something as simple as picking up a glass of water.

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Right.

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For us, it's automatic.

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Totally.

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But for a machine, it involves an incredibly complex series of calculations.

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Wow.

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You know, from perceiving the shape and position of the glass to adjusting grip strength to

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avoid breaking it.

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And those are all calculations that we don't even consciously think about.

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We just do it based on years of experience interacting with the world and developing,

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I guess, what you would call intuitive physics.

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Precisely.

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And that's why many researchers believe that giving AI systems some form of embodiment.

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Okay.

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Whether it's a physical robot body or a highly realistic virtual one is essential for them

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to develop this kind of intuitive understanding.

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Okay.

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But what about the folks on the other side of the debate?

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Yeah.

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The ones who think that language might actually be enough.

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Right.

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I mean, haven't there been some really impressive advances in natural language processing?

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Oh, absolutely.

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NLP.

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Yeah.

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Could an LLM with access to this massive data set of text and code potentially deduce how the

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world works just from that information?

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It's a compelling argument.

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Yeah.

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And certainly the progress in NLP has been remarkable.

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Yeah.

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But I think it's important to remember that language while rich in information is ultimately

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a representation of reality, not reality itself.

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Okay.

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It's like the difference between looking at a map of a city and actually walking its streets.

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Oh, I see.

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You see the difference.

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Yeah.

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So even if an AI can understand the words tree or wind or sunshine, it wouldn't necessarily

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grasp the experience of standing in a forest on a breezy day and feeling the warmth of the sun on its...

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Yeah.

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Well, I guess AI doesn't have skin.

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Exactly.

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And that's where the limitations of a purely language-based approach become apparent.

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Yeah.

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There's a richness to the environment, a sensory experience that language just can't fully capture.

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So are you saying then without that direct experience, AI's understanding of the world would

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always be kind of theoretical?

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It's a good way to put it.

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Like it might know the definitions of things, but not truly grasp their essence.

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Yeah.

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That's a great way to think about it.

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And it brings us right back to the central question of this whole deep dive.

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Okay.

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Can AI achieve true understanding without actually experiencing the world, whether physically or

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virtually?

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Right.

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It's a question that has profound implications for the future of AI, and it's one that we're

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going to continue to explore as we delve deeper into this fascinating topic.

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This is where things start to get really interesting, but we're going to take a quick pause here.

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Okay.

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Don't go anywhere, because when we come back, we'll be unpacking the implications of all this.

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Right.

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And exploring the potential of AI to not just understand the world, but maybe even experience it.

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I'm excited.

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Okay. So we've established that real world experience, or at least like a really good

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simulation of, it seems pretty crucial for AI to develop a deep understanding of, well,

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everything.

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Right.

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But now I want to go even further down this rat a hole.

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Okay.

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What happens when AI starts not just understanding the world, but experiencing it in a way that's

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closer to how we humans do?

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That takes us into the realm of what some researchers are calling artificial sentience,

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or even artificial consciousness.

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Wow.

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It's a really complex and debated area.

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Yeah. I can imagine. I mean, we're talking about AI potentially having feelings, emotions,

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subjective experiences, things that we typically associate with being human.

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Right.

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It kind of blows my mind to even think about it.

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Okay.

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It's definitely thought provoking, and it raises some fundamental questions about

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the nature of consciousness itself.

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Yeah.

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You know, if an AI could experience the world through senses, even if those senses are simulated,

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would that mean it's truly conscious, or would it simply be a very sophisticated mimicry of

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consciousness?

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I guess it depends on how you define consciousness, right?

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Yeah.

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There's no single agreed upon definition.

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No.

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But let's stick with this idea of AI having sensory experiences for a moment.

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Okay.

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How would that even work?

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Right.

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Would we need to like build robots with actual physical bodies that can sense the world just

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like we do?

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That's one approach for sure.

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Okay.

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And it's definitely an area of active research in robotics, but as we were talking about earlier,

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it's not the only possibility.

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Right.

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Remember those simulated environments we discussed?

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Yes.

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It might be possible to create a form of virtual embodiment where AI exists within a very

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realistic simulation and interacts with that world through virtual senses.

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So like a super advanced version of those virtual reality games where you can feel like

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you're actually in another place.

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Precisely.

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And the technology for creating those kinds of immersive experiences is advancing so

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rapidly.

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It is.

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We're already seeing incredibly realistic simulations in gaming and training environments.

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Oh yeah.

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It's not a huge leap to imagine that these could evolve to the point where an AI could

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experience a virtual world that's basically indistinguishable from reality, at least from

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its perspective.

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So even if it's not a physical body, the AI still needs some kind of embodied experience.

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Right.

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Some way to interact with the world and receive feedback from those interactions.

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Yeah.

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It's not enough to just be a disembodied brain in a server rack somewhere crunching data.

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It needs to be in the world in some way.

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Yeah.

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Embodiment, whether physical or virtual, seems crucial for developing that deep,

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intuitive understanding of the world.

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Right.

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It's the difference between knowing the definition of hot and actually feeling the

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heat of a flame.

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You know, thinking about this whole virtual embodiment thing, it makes me wonder about

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the potential implications for AI learning and development.

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Yeah.

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If we can create these rich simulated worlds for AI to inhabit, could that accelerate their

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learning process?

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Potentially.

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I mean, in a simulation, you can speed up time, expose the AI to a wider range of experiences,

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maybe even control the variables in a way that you can't in the real world.

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You've hit on some really interesting possibilities.

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Yeah.

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There's a lot of potential for using simulated environments to train AI systems in a more

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efficient and controlled way.

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Right.

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For example, imagine training a self-driving car AI in a virtual city where you can simulate

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all sorts of traffic conditions, weather patterns, even unexpected events that could

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help the AI learn much faster and more safely than it could in the real world.

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Right.

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Because in a simulation, you can let the AI make mistakes and learn from them without

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any real world consequences.

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That's just going to rewind time and try different approaches.

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It's like a giant sandbox for AI experimentation.

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Exactly, and that kind of experimentation is crucial for AI to develop robust and adaptable

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intelligence.

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It's about more than just following rules or memorizing patterns.

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It's about being able to generalize from past experiences, handle unexpected situations,

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learn and adapt on the fly.

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So it sounds like the simulated environments could be a game changer for AI development.

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Yeah.

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Especially when it comes to tasks that require a lot of real world experience like driving

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or even things like social interaction, which is something AI traditionally struggles with.

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Absolutely, and it's not just about the practical applications.

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These simulations could also help us understand the fundamental principles of intelligence itself.

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Oh, wow.

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You know, by observing how AI systems learn and adapt in these controlled environments,

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we might gain insights into the very nature of learning, problem solving, even consciousness.

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It's like having a window into the development of a mind, albeit an artificial one.

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But that raises another question.

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If AI becomes so good at learning and adapting in these virtual worlds,

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will it still be relevant to the real world?

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Right.

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I mean, will it be able to transfer that knowledge and those skills to a physical environment with

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all its complexities and unpredictability?

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That's a key challenge for AI researchers.

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Yeah.

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Ensuring that what AI learns in a simulation can be effectively applied in the real world.

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Right.

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There are differences between the two, of course.

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Of course.

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The physics of a simulated world might not perfectly match the physics of the real world.

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Right.

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And there's always the possibility of encountering situations in the real world that weren't

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accounted for in the simulation.

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So it's like sending a student who aced all their exams in a virtual classroom out into

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the real world for the first time.

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Yeah.

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They might have the knowledge, but do they have the practical skills and the ability to

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adapt to unexpected challenges?

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Exactly.

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And that's why it's important to find ways to bridge the gap between simulation and reality.

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Okay.

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One approach is to gradually increase the realism of the simulation.

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Introducing more and more of the complexities and unpredictability of the real world.

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Makes sense.

283
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Another is to combine simulation-based training with real-world experience.

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Right.

285
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Allowing the AI to test and refine its skills in a safe and controlled manner.

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Okay.

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So even with these like super realistic simulations, it sounds like we can't completely

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abandon the idea of AI interacting with the physical world.

289
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Right.

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There's still something valuable about that direct experience, about bumping up against

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those real-world constraints and learning to adapt.

292
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Absolutely.

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The real world is the ultimate testing ground for AI.

294
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Yeah.

295
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It's where the rubber meets the road, so to speak.

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Right.

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And it's where we'll ultimately see whether AI can truly live up to its potential.

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And that brings us to the big question, what does all this mean for the future of AI and its role

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in our lives?

300
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Right.

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Are we headed toward a future where AI is just a really super smart tool?

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Or are we talking about something more profound, something that could change our

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understanding of intelligence consciousness and maybe even what it means to be human?

304
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That's a question that deserves careful consideration and open discussion.

305
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Yeah.

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The future of AI is being shaped right now.

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And it's important that we engage in these conversations, that we explore the possibilities

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and the potential pitfalls, and that we work together to create a future where AI benefits

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humanity as a whole.

310
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Okay.

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So we really covered a lot of ground here, exploring this whole wild idea of whether AI needs to

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experience reality to truly get it.

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Yeah.

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We started off by looking at how human brains are just wired for real-world learning.

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Right.

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You know, constantly taking in all the sensory data just to make sense of our surroundings.

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And we contrasted that with how AI systems are doing their thing.

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Right.

319
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Especially those huge language models excelling in all these areas that are very language-based.

320
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Yeah.

321
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It makes you wonder if language could be the key to AI understanding reality.

322
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Uh-huh.

323
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That's a good question.

324
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Right.

325
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Like maybe all that real-world experience isn't actually necessary.

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Then we got into the whole debate about embodied AI.

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This idea that true intelligence needs some kind of grounding in reality, whether it's

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physical or simulated.

329
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Right.

330
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And how could we forget more of ex-paradox?

331
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Oh, yeah.

332
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That was a good one.

333
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That fascinating thing where computers can master these tasks that we humans find so mentally

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challenging.

335
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Right.

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But then they totally trip up on the things we do without even thinking, like recognizing

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someone's face or walking through a crowded room.

338
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It's so interesting, isn't it?

339
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It is.

340
00:15:00,080 --> 00:15:04,000
And then that led us to all these potential simulated environments.

341
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Right.

342
00:15:04,320 --> 00:15:09,040
You know, speeding up AI learning, giving them this sort of virtual embodiment where they

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can interact with a world that's safe to experiment in.

344
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And we even touched on artificial sentience and consciousness.

345
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Oh, yeah.

346
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Wondering if AI could one day actually experience the world like we do with all the feelings,

347
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emotions, and subjective experiences.

348
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Pretty mind-blowing.

349
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It is.

350
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It's been a thought-provoking journey to say the least.

351
00:15:26,240 --> 00:15:26,720
Oh, sure.

352
00:15:26,720 --> 00:15:32,800
And I think one of the key takeaways here is that this question of AI needing to experience

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reality to really understand it, well, it's not just some technical thing.

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It really gets at some fundamental aspects of what it means to be intelligent, to be

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conscious, to be alive.

356
00:15:44,240 --> 00:15:48,960
You know, as we were talking about all this, it made me think about how our own understanding

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of the world is shaped by our experiences.

358
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Bluffs.

359
00:15:52,640 --> 00:15:57,360
Like, how much we learn from our senses, from messing around with our environment, you know,

360
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from making mistakes and figuring things out as we go.

361
00:16:00,960 --> 00:16:01,920
That's a great point.

362
00:16:01,920 --> 00:16:05,840
Our brains are always making predictions about the world based on what we've gone through.

363
00:16:05,840 --> 00:16:06,000
Right.

364
00:16:06,000 --> 00:16:11,440
Like, we anticipate how things will move, how people will react, how situations will unfold.

365
00:16:11,440 --> 00:16:14,480
And when we're wrong, we change how we understand things.

366
00:16:14,480 --> 00:16:18,880
Yeah, it's this constant feedback loop that shapes how we see reality.

367
00:16:18,880 --> 00:16:24,320
So if we want AI to really understand the world like we do, maybe it needs to get in

368
00:16:24,320 --> 00:16:26,000
on that same feedback loop.

369
00:16:26,000 --> 00:16:26,400
Right.

370
00:16:26,400 --> 00:16:30,560
Interacting with the world, making predictions, testing them out, learning from its mistakes.

371
00:16:30,560 --> 00:16:31,120
Exactly.

372
00:16:31,120 --> 00:16:35,200
And that's why this whole debate about embodied AI is so important.

373
00:16:35,200 --> 00:16:35,520
Yeah.

374
00:16:35,520 --> 00:16:41,520
It's not just about giving AI a body or creating some super realistic simulation.

375
00:16:41,520 --> 00:16:47,440
It's about giving AI the chance to learn and adapt in a way that's more like how we do it.

376
00:16:47,440 --> 00:16:50,560
And maybe just maybe that kind of learning could lead to something really amazing.

377
00:16:51,200 --> 00:16:51,520
What?

378
00:16:51,520 --> 00:16:52,560
Like, what are you thinking?

379
00:16:52,560 --> 00:16:56,080
Well, an AI that not only understands the world, but can actually reason about it.

380
00:16:56,080 --> 00:16:56,480
Mm-hmm.

381
00:16:56,480 --> 00:16:59,600
You know, create new ideas and even help us understand ourselves better.

382
00:16:59,600 --> 00:17:00,720
That's an exciting thought.

383
00:17:00,720 --> 00:17:01,360
Yes.

384
00:17:01,360 --> 00:17:05,600
So as we're wrapping up this whole deep dive, what's the one big thing you want to leave our

385
00:17:05,600 --> 00:17:06,080
listener with?

386
00:17:06,720 --> 00:17:07,440
I'd say this.

387
00:17:08,800 --> 00:17:11,360
The future of AI is being shaped right now.

388
00:17:12,000 --> 00:17:15,760
It's a future full of crazy possibilities and some big challenges.

389
00:17:15,760 --> 00:17:16,240
Right.

390
00:17:16,240 --> 00:17:18,960
And it's a future that we all have a part in shaping.

391
00:17:18,960 --> 00:17:20,560
And how can our listeners get involved?

392
00:17:20,560 --> 00:17:23,920
What can they do to help steer AI in the right direction?

393
00:17:23,920 --> 00:17:28,320
Well, I'd say stay curious, stay informed, stay engaged.

394
00:17:28,320 --> 00:17:29,040
I like that.

395
00:17:29,040 --> 00:17:31,520
Learn about the different ways AI is being developed.

396
00:17:31,520 --> 00:17:35,440
Ask those tough questions, share your thoughts and your worries.

397
00:17:35,440 --> 00:17:40,480
And remember, the choices we make today will determine what kind of future we build with AI.

398
00:17:40,480 --> 00:17:41,040
Well said.

399
00:17:41,040 --> 00:17:43,920
It's been an incredible journey exploring all of this with you.

400
00:17:43,920 --> 00:17:45,040
I really enjoyed it.

401
00:17:45,040 --> 00:17:49,440
And to our listeners, thank you so much for joining us on this deep dive.

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00:17:49,440 --> 00:18:15,840
We hope you found it insightful, thought-provoking, and maybe even a little mind-blowing.