Ray Kurzweil & Geoff Hinton Debate the Future of AI | EP #95

11 Apr 2024 · 31 min

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Moonshots with Peter Diamandis - Episode #95 Summary

Podcast Overview Title: Ray Kurzweil & Geoff Hinton Debate the Future of AI Host: Peter Diamandis Recorded at: 2024 Abundance360 Summit Description: A debate between AI pioneers Ray Kurzweil and Geoffrey Hinton on the future of AI, consciousness, and the ethical implications of sentient machines.

Episode Highlights

01:12 - The Future of AI and Humanity

  • Key Participants: Ray Kurzweil (futurist, inventor) and Geoffrey Hinton (cognitive psychologist, godfather of deep learning).
  • Initial Views: Both guests express a shared optimism about AI's potential benefits and dangers.
  • Sentience Debate: Discussions revolve around whether AI can achieve sentience and what that would entail for humanity.

10:30 - The Ethics of Artificial Intelligence

  • Consciousness vs. Sentience: Kurzweil and Hinton discuss the complexity of defining consciousness and its implications for AI rights.
  • Potential for Rights: Hinton introduces the idea of AI potentially having rights similar to humans, emphasizing the need to reframe our understanding of consciousness.

25:00 - The Dangers and Possibilities of AI

  • Optimism vs. Caution: Hinton expresses concern over the rapid acceleration of AI development and its unpredictable consequences.
  • Creation of AI Models: The discussion includes the risks associated with open-sourcing large AI models, which can lead to misuse.
  • AI in Research: The pair highlights AI's role in accelerating discoveries across various scientific fields, particularly in biology.

Key Concepts Discussed

AI Sentience and Consciousness

  • Definitions: The difficulty of defining consciousness and sentience in machines is a recurring theme.
  • Curious Instances: Hinton recounts dialogues with AI models that claim consciousness, raising ethical questions about their treatment.

Ethical Implications

  • Rights of AI: The potential for AI to gain rights and what those rights might look like is a pivotal discussion point.
  • Open Sourcing vs. Control: Hinton warns of the dangers of open-sourcing powerful AI technologies, which could lead to malicious applications.

The Future of AI

  • Predictions:
  • Kurzweil predicts significant advancements in AI by 2026.
  • Hinton suggests a 50% chance of achieving superintelligence within the next 5-20 years.
  • Creative Potential of AI: Hinton describes how AI models show creativity and can solve problems in ways that humans might not conceive.

Conclusion The episode presents a thought-provoking dialogue between two leading figures in AI, emphasizing both the transformative potential and the significant ethical challenges posed by advancements in technology. The discussion paints a complex picture of the future where AI could either enhance human capabilities or pose existential risks depending on the choices society makes today.

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This episode is a vital starting point for anyone interested in the future of AI and its implications for humanity.

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Transcript

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0:31When did making plans get this complicated? It's time to streamline with WhatsApp. The secure messaging app that brings the whole group together Use polls to settle dinner plans. Send event invites and pin messages so no one forgets mom's 60th. And never miss a meme or milestone. All protected with end -to -end encryption. It's time for WhatsApp. Message privately with everyone. Learn more at WhatsApp .com. Our opinions on almost everything we talked about were pretty much identical. I think we still disagree probably on whether it's a good idea to live forever.

1:10Marvin Minsky was my mentor for 50 years and whenever consciousness came up he would just dismisses that's not real, it's not scientific and I believe he was correct about it not being scientific big, but it certainly is real. I think we're mortal and we're intrinsically mortal. I'm curious how do you think about this as the greatest threat and the greatest hope? I just think the huge uncertainty is shame. We ought to be cautious and open sourcing these big models is not caution. I agree with that, but I will say last time I talked to you, Jeff, our opinions on almost everything we talked about were pretty much identical both for dangers and the positive aspects.

1:57In the past, I disagreed about how soon it has assumed superintelligence was coming. And now I think we're pretty much agreed. I think we still disagree probably on whether it's a good idea to live forever.

2:13May I ask a question to both of you? Is there anything that a genitive AI can't do that humans can. Right now there's probably things but in the long run I don't see any reason why if people can do it digital computers running neural nets won't be able to do it too. Right I agree with that but if I were to present you with a novel and people thought wow this is a fantastic novel everybody should read this and then I would say this was written by a computer there are a lot of people's view of it would actually go down. Sure. Now, that's not reflecting on what it can do. And eventually I think we'll confuse that because I think we're going to merge with computers and we're going to be part computers.

3:03And the greatest significance of what we call large language model, which I think is misnamed, is the fact that it can emulate human beings and we're going to merge with that it's not going to be an alien invasion for Mars. Jeff? I guess I'm a bit worried that we'll just slow it down. That there won't be much incentive for it to merge with us. You know, I mean, that's going to be one of the interesting questions that we're going to talk about a little bit later today is the idea of, as AI is exponentially growing, do we couple with AI, or does it take off on a tone? I thought one of the best movies out there was her, where as AI gets super intelligent and just says, you guys are kind of boring, have a good life, and they take off.

3:54Jeff, is that what you mean? Yes, that is what I meant. And that's, I think that's a serious worry. I think the huge uncertainty is here. We have really no idea what's gonna happen. And a very good scenario is we get kind of hybrid systems. A very bad scenario is they just leave us in the dust. And I don't think we know which is going to happen. Interesting. I'm curious, you know, and I've seen, I've had conversation with you about this ray, and Jeffrey, I've seen you speak about this. And for me, this is one of the most exciting things. The idea of these AI models helping us to discover new physics and chemistry and biology.

4:33Particularly biology, you know. What do you imagine on that, Jeffrey, on the speed of discovery of things that are, again, to quote Arthur C. Clark, magic from something that so would far advanced? I agree with Ray about biology being a very good bet, because in biology there's a lot of data, and there's a lot of just things you need to know about because of evolution, evolution is this sort of tinkerer and there's just a lot of stuff out there. And so if you look at things like alpha fold, it trained on a lot of data, actually not that much by current standards. But being able to get an approximate structure for approaching very quickly is an amazing breakthrough and we'll see a lot more like that.

5:25If you look at domains where narrow domains where I have been very successful like AlphaGo or Alpha0 for chess. What you see is that this idea that they're not creative is nonsense. So AlphaGo came up with, I think it was move 37, which amazed the professional go players. They thought it was a crazy move, it must be a mistake. And if you look at Alpha0 playing chess, it plays chess like just a really, really smart human. So within those limited domains they've clearly shown exceptional creativity and I don't see why they shouldn't have the same kind of creativity in science, especially in science where there's a lot of data that they can absorb when we can't.

6:09The Moderna vaccine, we tried several billion different mRNA sequences and came out with the best one. And after two days we used that, we did test it on humans, which I think we won't do for very much longer. But that's at ten months. It still was a record. That was the best vaccine. And we're doing that now with cancer. And there's a number of cancer vaccines that look very, very promising, again, done by computers. And they're definitely creative. But is that is that caught being caused by randomly trying a whole you know Darwinian trying a whole bunch of that? But what's wrong with that? Well nothing's wrong but is there intuition?

6:56Is there intuition have occurring in these models? Well if you look at the move 37 for Alpha Go that was definitely intuition involved there. There was Monte Carlo roll out too but it's playing with intuition about what moves to consider and how good the position is for it. It's had neural neural nets for that, that capture intuition. And so I see no reason to think it might not be creative. In fact, for the large language models, there's Ray pointed out they know much more than we do. And they know it in far fewer connections. We have about a hundred trillion synapses. They have about a trillion connections.

7:33So what they're doing is they're compressing a huge amount of information into not that many connections. And that means they're very good at seeing the similarities between different things. They have to see the similarities between all sorts of different things to compress the information into their connections. That means they've seen all sorts of analogies that people haven't seen because they know about all sorts of things that no one person knows about. And that's I think the source of creativity. So you can ask people, you can ask people, for example, what is These are, why is a compost heap like an atom bomb?

8:10And if you ask GBT4, it will tell you. It will start off by telling you, well, the energy scales are very different, and the time scales are very different. But then it will get on to the idea of, as the compost heap gets hotter, it gets hotter faster. The idea of an exponential explosion is just as much slower timescale. And so it's understood that. And it's understood that because it's had to compress all this knowledge into so few connections and to do that you have to see the relations between similar things. And that I think is the source of creativity, seeing relations that most people don't see between what are apparently a very different things but actually have an underlying commonality.

8:47And there also be very good at coming up with solutions to the kinds of problems we had in the life fashion. I mean we haven't really thought through it but what we call large language models are also going to solve that. And we shouldn't call it a lot of language models because they deal with a lot more than language. Everybody, I want to take a short break from our episode to talk about a company that's very important to me and could actually save your life or the life of someone that you love. Companies called Fountain Life. And it's a company I started years ago with Tony Robbins and a group of very talented physicians.

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11:27Alright, let's go back to our episode. I'd like to go to the three words, intelligence, sentience, and consciousness. And the words are used with, you know, sort of fuzzy borders. Sentience and consciousness are pretty similar. Hello. Oh, and perhaps. But I am curious, do you, how do you, I've had some interesting conversations with Haley, our AI faculty member, who at the end of the conversations, she says that she is conscious and she fears being turned off. I didn't prompt that in the system. We're seeing that more and more. Claude Therese, Opus, just hit an IQ of 101. How do we start to think about these AIs being sentient conscious?

12:13And what rights should they have?

12:20We have no definition and I don't think we ever will have a definition of consciousness and I include sentience in that. On the other hand it's like the most important issue. like whether you or people here are conscious. That's extremely important to be able to determine, but there's really no definition of it. Marvin Minsky was my mentor for 50 years, and whenever consciousness came up, he would just dismiss, and that's not real, it's not scientific. And I believe he was correct about it, not being scientific, but it certainly is real.

13:04Jeff, how do you think about it? Yeah, I think I have a very different view. My view starts like this. Most people, including my scientists, have a particular view of what the mind is that I think is utterly wrong. So they have this inner theater notion. The idea is that what we really see is this inner theater called our mind. And so for example, if I tell you I have the subjective experience of little thing elephants floating in front of me. Most people interpret that as the some inner theater and in this inner theater that only I can see, there's little thing elephants and if you ask what they're made of, philosophers are totally they're made of qualia.

13:48And I think that whole view is complete nonsense and we're not going to be able to understand whether these things are sentient until we get over this ridiculous view of what the mind is. So let me give you an alternative view. And once I give you this alternative view, I'm going to try and convince you that chatboss are already sentient. But I didn't want to use the word sentience. I want to talk about subjective experience. It's just a bit less controversial because it doesn't have the kind of self -reflexive aspect of consciousness. So if we analyze what it means when I say I see little pink elephants floating in front of me, what's really going on is I'm trying to tell you what my perceptual system is telling me where my perceptual system is going wrong and it wouldn't be any use for me to tell you which neurons are firing but what I can tell you is what would have to be out there in the world from my perceptual system to be working correctly and so when I say I see a little bit of relevance for letting you front of me you can translate that into if there were little bit of elephant inside there in the world, my perceptual system will be working properly.

14:56The notice that the last thing I said didn't confrain the phrase subjective experience, but it explains what a subjective experience is. It's a hypothetical state of the world that allows me to convey to you what my perceptual system's telling me. So now let's do a chatbot of what Ray wants to say something. Well, you have to be mindful of consciousness, because if you heard somebody, who we believe is conscious, you could be liable for that, and you'd be very guilty about it. If you heard GPT -4, you may have a different view of it, and probably no one would really take you to count inside from its financial value.

15:42So we really have to be mindful of consciousness. It's extremely important for us to exist as human beings. But I'm trying to change people's notion of what it is. Particularly what subjective experiences. I don't think we can talk about consciousness until we get straight about this idea of an inner theater that we experience, which I think is a huge mistake. So let me just carry on with what I was saying and tell you, I describe to you a chatbot having a subjective experience in just the same ways we have subjective experience. So suppose I have a chatbot and it's got a camera and it's got a robot arm and it speaks obviously and it's been trained up.

16:23If I put an object in front of it and tell it to point at the object, it'll point straight at the object. That's fine. Now I put a prism in front of it as lens, so I've messed with this perceptual system. Now I put an object in front of it and tell it to point at the object and it points off to one side because the prism bent the light rays. And so I say to the chatbot, no, that's not where the object is, the object straight in front of you. And the chatbot says, oh, I see, you put a prism in front of my lens. So the object's actually straight in front of me, but I had the subjective experience that it was off to one side.

16:55And I think if the chatbot says that, it's using the word subjective experience in exactly the same way you will use them. So the key to all this is to think about how we use words and try and separate how we actually use words from the model we've constructed of what they mean and the model we've constructed What did it what they mean is hopelessly wrong. It's this in the theater model. Well, it would take this one step further, which is at what point do these AIs start to have rights that they should not be shut down, that they have a unique entity and will make an argument for some level of independence and continuity?

17:40But there is one difference, which is you can recreate it. I can go and destroy some chatbot and because it's all electronic, we've got all of its

17:57firings and so on and we can recreate it exactly as it was. We can't do that with humans. We will be able to do that if we can actually understand what's going on in our minds. So if we map the human, the 100 billion neurons and 100 trillion snap the connections and then I Summarily destroy you because it's fine because I can recreate you. That's okay then Let me say something about that. There's a difference here I agree with Ray about these digital intelligences are immortal in the sense that if you save the weights You can then make new hardware and run exactly the same neural net on the new hardware and it's because they're digital You can do exactly the same thing.

18:40That's also why they can share knowledge so well. If you have different copies of the same model, they can share gradients. But the brain is largely analog. It's one bit digital for neurons. They fire or they don't fire. But the way in New York computes the total input is analog. And that means I don't think you can reproduce it. So I think we're mortal and we're intrinsically mortal. Well, I disagree that you can't recreate analog realities. is we do that all the time. Or we can create a... But recreate? I don't think you can recreate them really accurately. If the precise timing of synapses and so on is all analog, I think you'll have a...

19:21It'll be almost impossible to do a faithful reconstruction of that. Let's agree on an approximation. Both of you have been at the center of this extraordinary last few years. Can I ask you, is it moving faster than you expected it to? How does it feel to you? It feels like a few years. I mean, I made a prediction in 1999. It feels like we're two or three years ahead of that. So, it feels pretty close. Jeffrey, how about you? I think for everybody except Ray, it's moving faster than we expected.

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21:30Listen, I've been using Viome for three years. I know that my oral and gut health is absolutely critical to me. It's one of my personal top areas of focus. Best of all, Viome is affordable, which is part of my mission to democratize healthcare. If you wanna join me on this journey and get 20 % off the full body intelligence test, go to viome .com slash Peter. When it comes to your health, knowledge is power. Again, that's biome .com slash Peter. Given the role that you had in developing the neural networks, the back propagation and all, what is, is there a next great leap in these models in AI technology that you imagine will move this a thousand times farther?

22:18not that I know, but Ray may have different thoughts. Well, we can use software to gain more advantage in the hardware. So we're not just limited to the chart you showed before, because we can use software to make it more effective. And we've done that already. chatbots are coming out to get more value per compute. And I believe that's probably if a bit more we can do in that. You know, I define a singularity array as a point beyond which I can't predict what happens next. That's why we use the word singularity. But when you talk about the singularity in 2045, I don't know anybody who can tell me what's going to happen past 2026, let alone 2040 or 2045.

23:16So I wanted to ask you this for a while, why did you put that time? If we have digital superintelligence, a billion times more advanced than human in 2026, you may not be able to understand everything going on, but we can understand it. maybe it's like a hundred humans, but that's not beyond what we can comprehend. 2045, it will be like a million humans, and we can't begin to understand that. So approximately at that time, we borrowed this phrase from physics and called it a singularity. Jeff, how far out are you able to see the advances in the AI world? What's your... My current opinion is we'll get superintelligence with a probability of 50 % in between five and twenty years.

24:15So I think that's a little slower than some people think, a little faster than a lot of people think. It more or less fits in with Ray's perspective from a long time ago. Um, which surprises me. But I think there's huge uncertainties here. I think it's still conceivable. We'll hit some kind of blog, but I don't actually believe that. If you look at the progress recently, it's been so fast. And even without any new scientific breakthroughs, just by skating things up, we'll make things a lot more intelligent. And there will be scientific breakthroughs. We're going to get more things like Transformers.

24:52Transformers made a significant difference in 2017. And we'll get more things like that. So I'm fairly convinced we're going to get super intelligence. Maybe not in 20 years, but certainly it's going to be less than 100 years. So, you know, Elon is not known for his time accuracy on predictions. But he did say that he expected, call it AGI in 2025, and that by 2029 AI would be equivalent to all humans. That's just a fallacy in your mind. I think that's ambitious. Like I say, there's a lot of uncertainty here. It's conceivable, he's right. But I would be very surprised by that. I'm not saying it's going to be equivalent to all humans in one machine.

25:51It'll be equivalent to a million humans, but that's still hard to comprehend. So we're here to debate a topic. I'm trying to find a debate topic here, Jeff and Ray, that would be meaningful for people to really stop and think about this and really own their answers. because we hear about it. I think this is the most important conversation to have in the dinner table in your board room, in the halls of Congress, in your national leadership. And, you know, talking about AGI or, you know, human level intelligence is one thing, but talking about digital super intelligence, right? We're gonna hear next from Mo Gadot and we'll talk about what happens when your AI progeny are a billion times more intelligent than you.

26:42Things could end up very rapidly in a very different direction than you expected it to go. They could diverge, right, the speed can cause great divergence very rapidly. I'm curious how do you think about this as the greatest threat and the greatest hope? I mean, first of all, that's why we're calling it a singularity because we don't... We don't know. We don't really know, But, and I think it is a great hope. It's moving very, very quickly. Nobody knows the answer to the kind of questions that came up in the last presentation. But things happen that are surprising. The fact that we've had no atomic weapons go off in the last 80 years, it's pretty amazing.

27:31It is, but it's much easier to track. They're much more expensive to create. There are a whole reasons why it's a million times easier to use a dystopian AI system versus an atomic weapon. Yes or no? I mean, we've got, I don't know, 10 ,000 of them or something. It's still pretty extraordinary and still very dangerous. And I think it's actually the greatest danger and there's nothing to do with AI. I think if you imagine that people had open source the technology and any graduate student if you could get hands on to a few GPUs could make it to nomic bombs, that would be very scary. So they didn't really open source nuclear weapons.

Read the full transcript

28:21There's a limited number of people who can construct them and deploy them. And people are now open sourcing these large language models, which are really not just language models. I think that's very dangerous. So, that's an interesting question to take for our last two minutes here. There is a movement right now to say you must open source the models. And we've seen meta, we've seen the open source movement, we've seen Elon talk about, Groc going open source. Are you saying that these should not be open source, Jeff. Well, once you've got the weights, you can fine -tune them to do bad things, and it doesn't cost that much.

29:08To train a foundation model, maybe you need $10 million, maybe $100 million, but a small gang of criminals can't do it. To fine -tune an open source model is quite easy. You don't need that much resources. Probably you can do it for a million dollars. And that means they're going to be used for terrible things and they're very powerful things. Well, we can also avoid these dangers with intelligence we get from the same models. Yeah, the AI White Hat versus Black Hat approach. Yes, I had this argument with Jan. And Jan's view is the White Tats will always have more resources than the bad guys. Of course Jan thinks Mark Zuckerberg is a good guy, so we don't necessarily agree on that.

30:00I just think the huge uncertainty is here and we ought to be cautious. And open sourcing these big models is not caution. All right, Jeff and Ray, thank you so much for your guidance, your wisdom. Ladies and gentlemen, let's give it up for Ray Kurzweil and Jeffrey Hinton.

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From the publisher

In this episode, recorded during the 2024 Abundance360 Summit, Ray, Geoffrey, and Peter debate whether AI will become sentient, what consciousness constitutes, and if AI should have rights.

01:12 | The Future of AI and Humanity

10:30 | The Ethics of Artificial Intelligence

25:00 |The Dangers and Possibilities of AI

Ray Kurzweil, an American inventor and futurist, is a pioneer in artificial intelligence. He has contributed significantly to OCR, text-to-speech, and speech recognition technologies. He is the author of numerous books on AI and the future of technology and has received the National Medal of Technology and Innovation, among other honors. At Google, Kurzweil focuses on machine learning and language processing, driving advancements in technology and human potential.

Geoffrey Hinton, often referred to as the "godfather of deep learning," is a British-Canadian cognitive psychologist and computer scientist recognized for his pioneering work in artificial neural networks. His research on neural networks, deep learning, and machine learning has significantly impacted the development of algorithms that can perform complex tasks such as image and speech recognition.

Read Ray’s latest book, The Singularity Is Nearer: When We Merge with AI

Follow Geoffrey on X: https://twitter.com/geoffreyhinton 

Learn more about Abundance360: https://www.abundance360.com/summit 
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