Right, so get, we're diving deep into AI today and asking you a question that's got a lot of people talking.
Does AI actually need to experience reality in order to really, truly understand it?
And we've got a whole bunch of research articles here.
And one of the things that just kind of jumped out was this idea that computers can be
so good at things like chess.
Right.
But then they just totally fail at things we humans find so simple, like driving.
Yeah.
It's kind of a paradox, wouldn't you say?
It really is.
And, you know, it gets to the core of how AI and human intelligence might be fundamentally different.
Oh.
You see, humans are constantly bombarded with sensory data all the time.
Right.
What we see, what we hear, what we feel.
Yeah.
Our brains process all that information so fast to make sense of the world.
Wow.
That's how we learn and adapt so quickly.
So it's like our brains are just hardwired for learning in the real world from the get go.
Absolutely.
But AI systems, especially the ones that are getting all the attention these days,
they seem to be really excelling in areas that are very language based.
Yeah.
I mean, look at these LLMs, these large language models.
Right.
They can write poems, generate code, even pass the bar exam.
It's incredible.
Yeah.
So could language itself be the key to AI understanding reality?
Maybe all that real world experience isn't actually necessary.
Well, that's a really great question.
Yeah.
It's a question that has a lot of very smart people debating and...
I bet.
You know, language is definitely powerful.
Yeah.
It's how we communicate complex ideas, pass on knowledge.
You could think of it as a sort of compressed code that contains a vast amount of information and
wisdom.
Right.
But is that enough for AI to build a complete model of reality?
Yeah.
Well, that's where the debate gets really interesting.
Yeah.
Because even if an AI can process language, like a pro, does it actually understand what
those words represent in the real world?
That's the key.
Like if you tell an LLM about a sunset, can it really grasp the beauty, the colors, the
feeling of the warmth on your skin?
That gets to the core of the argument for embodied AI.
This is the idea that true intelligence actually requires some grounding in reality,
whether it's physical or simulated.
I see.
The real world, with all its sights, sounds, smells, textures.
It's so incredibly rich and complex in a way that language can only approximate.
So you're saying even a really realistic virtual world could be enough for AI to develop that
kind of understanding?
It's a possibility, for sure.
There are researchers working on creating just that highly detailed simulated environments
where AI can interact with objects, experience physics, and learn through trial and error,
much like humans do in the real world.
Okay.
So let's talk about this trial and error part for a second.
Okay.
You mentioned earlier that AI struggles with tasks that humans find intuitive, like driving
or doing the dishes.
Right.
And that brings us to this thing called Moravex Paradox.
Exactly.
Moravex Paradox points out this fascinating disconnect.
Computers can easily master tasks that we as humans consider mentally challenging,
right?
Like complex calculations or strategic thinking, but then they stumble when it comes to things
that seem almost effortless for us.
Okay.
What?
Like recognizing a face or navigating a cluttered room?
Oh, so it's almost like they got all the brain power for complex reasoning, but they
lacked the common sense that we developed just from living in the world.
That's a great way to put it, yeah.
But how does this paradox then inform this debate about embodied AI?
What's the connection there?
Well, Moravex Paradox really highlights the difference between the kind of intelligence
that we've traditionally programmed into computers.
Okay.
Logical rule-based systems and the kind of intelligence that emerges from interacting
with the physical world.
Yeah.
Think about something as simple as picking up a glass of water.
Right.
For us, it's automatic.
Totally.
But for a machine, it involves an incredibly complex series of calculations.
Wow.
You know, from perceiving the shape and position of the glass to adjusting grip strength to
avoid breaking it.
And those are all calculations that we don't even consciously think about.
We just do it based on years of experience interacting with the world and developing,
I guess, what you would call intuitive physics.
Precisely.
And that's why many researchers believe that giving AI systems some form of embodiment.
Okay.
Whether it's a physical robot body or a highly realistic virtual one is essential for them
to develop this kind of intuitive understanding.
Okay.
But what about the folks on the other side of the debate?
Yeah.
The ones who think that language might actually be enough.
Right.
I mean, haven't there been some really impressive advances in natural language processing?
Oh, absolutely.
NLP.
Yeah.
Could an LLM with access to this massive data set of text and code potentially deduce how the
world works just from that information?
It's a compelling argument.
Yeah.
And certainly the progress in NLP has been remarkable.
Yeah.
But I think it's important to remember that language while rich in information is ultimately
a representation of reality, not reality itself.
Okay.
It's like the difference between looking at a map of a city and actually walking its streets.
Oh, I see.
You see the difference.
Yeah.
So even if an AI can understand the words tree or wind or sunshine, it wouldn't necessarily
grasp the experience of standing in a forest on a breezy day and feeling the warmth of the sun on its...
Yeah.
Well, I guess AI doesn't have skin.
Exactly.
And that's where the limitations of a purely language-based approach become apparent.
Yeah.
There's a richness to the environment, a sensory experience that language just can't fully capture.
So are you saying then without that direct experience, AI's understanding of the world would
always be kind of theoretical?
It's a good way to put it.
Like it might know the definitions of things, but not truly grasp their essence.
Yeah.
That's a great way to think about it.
And it brings us right back to the central question of this whole deep dive.
Okay.
Can AI achieve true understanding without actually experiencing the world, whether physically or
virtually?
Right.
It's a question that has profound implications for the future of AI, and it's one that we're
going to continue to explore as we delve deeper into this fascinating topic.
This is where things start to get really interesting, but we're going to take a quick pause here.
Okay.
Don't go anywhere, because when we come back, we'll be unpacking the implications of all this.
Right.
And exploring the potential of AI to not just understand the world, but maybe even experience it.
I'm excited.
Okay. So we've established that real world experience, or at least like a really good
simulation of, it seems pretty crucial for AI to develop a deep understanding of, well,
everything.
Right.
But now I want to go even further down this rat a hole.
Okay.
What happens when AI starts not just understanding the world, but experiencing it in a way that's
closer to how we humans do?
That takes us into the realm of what some researchers are calling artificial sentience,
or even artificial consciousness.
Wow.
It's a really complex and debated area.
Yeah. I can imagine. I mean, we're talking about AI potentially having feelings, emotions,
subjective experiences, things that we typically associate with being human.
Right.
It kind of blows my mind to even think about it.
Okay.
It's definitely thought provoking, and it raises some fundamental questions about
the nature of consciousness itself.
Yeah.
You know, if an AI could experience the world through senses, even if those senses are simulated,
would that mean it's truly conscious, or would it simply be a very sophisticated mimicry of
consciousness?
I guess it depends on how you define consciousness, right?
Yeah.
There's no single agreed upon definition.
No.
But let's stick with this idea of AI having sensory experiences for a moment.
Okay.
How would that even work?
Right.
Would we need to like build robots with actual physical bodies that can sense the world just
like we do?
That's one approach for sure.
Okay.
And it's definitely an area of active research in robotics, but as we were talking about earlier,
it's not the only possibility.
Right.
Remember those simulated environments we discussed?
Yes.
It might be possible to create a form of virtual embodiment where AI exists within a very
realistic simulation and interacts with that world through virtual senses.
So like a super advanced version of those virtual reality games where you can feel like
you're actually in another place.
Precisely.
And the technology for creating those kinds of immersive experiences is advancing so
rapidly.
It is.
We're already seeing incredibly realistic simulations in gaming and training environments.
Oh yeah.
It's not a huge leap to imagine that these could evolve to the point where an AI could
experience a virtual world that's basically indistinguishable from reality, at least from
its perspective.
So even if it's not a physical body, the AI still needs some kind of embodied experience.
Right.
Some way to interact with the world and receive feedback from those interactions.
Yeah.
It's not enough to just be a disembodied brain in a server rack somewhere crunching data.
It needs to be in the world in some way.
Yeah.
Embodiment, whether physical or virtual, seems crucial for developing that deep,
intuitive understanding of the world.
Right.
It's the difference between knowing the definition of hot and actually feeling the
heat of a flame.
You know, thinking about this whole virtual embodiment thing, it makes me wonder about
the potential implications for AI learning and development.
Yeah.
If we can create these rich simulated worlds for AI to inhabit, could that accelerate their
learning process?
Potentially.
I mean, in a simulation, you can speed up time, expose the AI to a wider range of experiences,
maybe even control the variables in a way that you can't in the real world.
You've hit on some really interesting possibilities.
Yeah.
There's a lot of potential for using simulated environments to train AI systems in a more
efficient and controlled way.
Right.
For example, imagine training a self-driving car AI in a virtual city where you can simulate
all sorts of traffic conditions, weather patterns, even unexpected events that could
help the AI learn much faster and more safely than it could in the real world.
Right.
Because in a simulation, you can let the AI make mistakes and learn from them without
any real world consequences.
That's just going to rewind time and try different approaches.
It's like a giant sandbox for AI experimentation.
Exactly, and that kind of experimentation is crucial for AI to develop robust and adaptable
intelligence.
It's about more than just following rules or memorizing patterns.
It's about being able to generalize from past experiences, handle unexpected situations,
learn and adapt on the fly.
So it sounds like the simulated environments could be a game changer for AI development.
Yeah.
Especially when it comes to tasks that require a lot of real world experience like driving
or even things like social interaction, which is something AI traditionally struggles with.
Absolutely, and it's not just about the practical applications.
These simulations could also help us understand the fundamental principles of intelligence itself.
Oh, wow.
You know, by observing how AI systems learn and adapt in these controlled environments,
we might gain insights into the very nature of learning, problem solving, even consciousness.
It's like having a window into the development of a mind, albeit an artificial one.
But that raises another question.
If AI becomes so good at learning and adapting in these virtual worlds,
will it still be relevant to the real world?
Right.
I mean, will it be able to transfer that knowledge and those skills to a physical environment with
all its complexities and unpredictability?
That's a key challenge for AI researchers.
Yeah.
Ensuring that what AI learns in a simulation can be effectively applied in the real world.
Right.
There are differences between the two, of course.
Of course.
The physics of a simulated world might not perfectly match the physics of the real world.
Right.
And there's always the possibility of encountering situations in the real world that weren't
accounted for in the simulation.
So it's like sending a student who aced all their exams in a virtual classroom out into
the real world for the first time.
Yeah.
They might have the knowledge, but do they have the practical skills and the ability to
adapt to unexpected challenges?
Exactly.
And that's why it's important to find ways to bridge the gap between simulation and reality.
Okay.
One approach is to gradually increase the realism of the simulation.
Introducing more and more of the complexities and unpredictability of the real world.
Makes sense.
Another is to combine simulation-based training with real-world experience.
Right.
Allowing the AI to test and refine its skills in a safe and controlled manner.
Okay.
So even with these like super realistic simulations, it sounds like we can't completely
abandon the idea of AI interacting with the physical world.
Right.
There's still something valuable about that direct experience, about bumping up against
those real-world constraints and learning to adapt.
Absolutely.
The real world is the ultimate testing ground for AI.
Yeah.
It's where the rubber meets the road, so to speak.
Right.
And it's where we'll ultimately see whether AI can truly live up to its potential.
And that brings us to the big question, what does all this mean for the future of AI and its role
in our lives?
Right.
Are we headed toward a future where AI is just a really super smart tool?
Or are we talking about something more profound, something that could change our
understanding of intelligence consciousness and maybe even what it means to be human?
That's a question that deserves careful consideration and open discussion.
Yeah.
The future of AI is being shaped right now.
And it's important that we engage in these conversations, that we explore the possibilities
and the potential pitfalls, and that we work together to create a future where AI benefits
humanity as a whole.
Okay.
So we really covered a lot of ground here, exploring this whole wild idea of whether AI needs to
experience reality to truly get it.
Yeah.
We started off by looking at how human brains are just wired for real-world learning.
Right.
You know, constantly taking in all the sensory data just to make sense of our surroundings.
And we contrasted that with how AI systems are doing their thing.
Right.
Especially those huge language models excelling in all these areas that are very language-based.
Yeah.
It makes you wonder if language could be the key to AI understanding reality.
Uh-huh.
That's a good question.
Right.
Like maybe all that real-world experience isn't actually necessary.
Then we got into the whole debate about embodied AI.
This idea that true intelligence needs some kind of grounding in reality, whether it's
physical or simulated.
Right.
And how could we forget more of ex-paradox?
Oh, yeah.
That was a good one.
That fascinating thing where computers can master these tasks that we humans find so mentally
challenging.
Right.
But then they totally trip up on the things we do without even thinking, like recognizing
someone's face or walking through a crowded room.
It's so interesting, isn't it?
It is.
And then that led us to all these potential simulated environments.
Right.
You know, speeding up AI learning, giving them this sort of virtual embodiment where they
can interact with a world that's safe to experiment in.
And we even touched on artificial sentience and consciousness.
Oh, yeah.
Wondering if AI could one day actually experience the world like we do with all the feelings,
emotions, and subjective experiences.
Pretty mind-blowing.
It is.
It's been a thought-provoking journey to say the least.
Oh, sure.
And I think one of the key takeaways here is that this question of AI needing to experience
reality to really understand it, well, it's not just some technical thing.
It really gets at some fundamental aspects of what it means to be intelligent, to be
conscious, to be alive.
You know, as we were talking about all this, it made me think about how our own understanding
of the world is shaped by our experiences.
Bluffs.
Like, how much we learn from our senses, from messing around with our environment, you know,
from making mistakes and figuring things out as we go.
That's a great point.
Our brains are always making predictions about the world based on what we've gone through.
Right.
Like, we anticipate how things will move, how people will react, how situations will unfold.
And when we're wrong, we change how we understand things.
Yeah, it's this constant feedback loop that shapes how we see reality.
So if we want AI to really understand the world like we do, maybe it needs to get in
on that same feedback loop.
Right.
Interacting with the world, making predictions, testing them out, learning from its mistakes.
Exactly.
And that's why this whole debate about embodied AI is so important.
Yeah.
It's not just about giving AI a body or creating some super realistic simulation.
It's about giving AI the chance to learn and adapt in a way that's more like how we do it.
And maybe just maybe that kind of learning could lead to something really amazing.
What?
Like, what are you thinking?
Well, an AI that not only understands the world, but can actually reason about it.
Mm-hmm.
You know, create new ideas and even help us understand ourselves better.
That's an exciting thought.
Yes.
So as we're wrapping up this whole deep dive, what's the one big thing you want to leave our
listener with?
I'd say this.
The future of AI is being shaped right now.
It's a future full of crazy possibilities and some big challenges.
Right.
And it's a future that we all have a part in shaping.
And how can our listeners get involved?
What can they do to help steer AI in the right direction?
Well, I'd say stay curious, stay informed, stay engaged.
I like that.
Learn about the different ways AI is being developed.
Ask those tough questions, share your thoughts and your worries.
And remember, the choices we make today will determine what kind of future we build with AI.
Well said.
It's been an incredible journey exploring all of this with you.
I really enjoyed it.
And to our listeners, thank you so much for joining us on this deep dive.
We hope you found it insightful, thought-provoking, and maybe even a little mind-blowing.