
36 segments available
Asked Ilya Sutskever (Chief Scientist of OpenAI) about: * time to AGI * leaks and spies * what's after generative models * post AGI futures * working with MSFT and competing with Google * difficulty of aligning superhuman AI Hope you enjoy as much as I did! 𝐄𝐏𝐈𝐒𝐎𝐃𝐄 𝐋𝐈𝐍𝐊𝐒 * Transcript: https://www.dwarkeshpatel.com/p/ilya-sutskever * Apple Podcasts: https://apple.co/42H6c4D * Spotify: https://spoti.fi/3LRqOBd * Follow me on Twitter: https://twitter.com/dwarkesh_sp 𝐓𝐈𝐌𝐄𝐒𝐓𝐀𝐌𝐏𝐒 00:00:00 - Time to AGI 00:05:57 - What’s after generative models? 00:10:57 - Data, models, and research 00:15:27 - Alignment 00:20:53 - Post AGI Future 00:26:56 - New ideas are overrated 00:36:22 - Is progress inevitable? 00:41:27 - Future Breakthroughs
Ilya Sutskever discusses what distinguishes him from other researchers, emphasizing hard work and dedication as key factors in achieving multiple breakthroughs in AI. He reflects on the rarity of scientists who make significant contributions and the importance of relentless effort in the field of artificial intelligence.
"Today I have the pleasure of interviewing Ilya Sutskever, who is the Co-founder and Chief Scientist of OpenAI. Ilya, welcome to The Lunar Society. Thank you, happy to be here. First question a..."
Sutskever addresses concerns about the potential misuse of AI technologies like GPT by foreign governments for propaganda or scams. He speculates on the current state of such activities and the challenges in tracking them, highlighting the technical possibilities and ethical implications of AI deployment.
"Got it. What's the explanation for why there aren't more illicit uses of GPT? Why aren't more foreign governments using it to spread propaganda or scam grandmothers? Maybe they haven't really go..."
In this segment, Sutskever explores the economic value of AI before achieving AGI, suggesting a multi-year window of increasing value. He compares the growth of AI's economic impact to the development of self-driving cars, emphasizing the exponential growth in AI's capabilities and its implications for businesses.
"Would you be able to track it if it was happening? I think large-scale tracking is possible, yes. It requires special operations but it's possible. Now there's some window in which AI is very..."
Sutskever discusses the potential for AI to underperform economically by 2030, attributing this to issues of reliability. He emphasizes the importance of ensuring AI systems are dependable to maximize their economic contributions, while also acknowledging the uncertainty surrounding future developments.
"from now till AGI pretty much. Okay. Because I'm curious if there's a startup that's using your model, at some point if you have AGI there's only one business in the world, it's OpenAI. How mu..."
Ilya Sutskever reflects on the future of AI beyond generative models, suggesting that while the current paradigm is powerful, it may not be the final form leading to AGI. He hints at the need for integrating various ideas from the past to develop the next paradigm in AI research.
"Okay, so let's take the counterfactual where it is a small percentage. Let's say it's 2030 and not that much economic value has been created by these LLMs. As unlikely as you think this might be, ..."
In this thought-provoking segment, Sutskever challenges the notion that next-token prediction can only mimic human performance. He argues that a sufficiently advanced neural network could extrapolate behaviors of hypothetical individuals with superior capabilities, thus potentially surpassing human intelligence.
"to say precisely what the next paradigm will be but it will probably involve integration of all the different ideas that came in the past. Is there some specific one you're referring to? It's h..."
Sutskever discusses the current state of reinforcement learning, noting that most data now comes from AI rather than humans. He envisions a future where AI can improve itself significantly, emphasizing the importance of human-AI collaboration in the learning process.
"This hypothetical, imaginary person with far greater mental ability than the rest of us. When we're doing reinforcement learning on these models, how long before most of the data for the reinfor..."
In this segment, Sutskever addresses concerns about running out of data for training AI models. He reassures that the current data situation remains strong but acknowledges that alternative training methods will be necessary as data sources become exhausted.
"which teaches the next machine. I've had a chance to play around these models and they seem bad at multi-step reasoning. While they have been getting better, what does it take to really surpass..."
Sutskever discusses the potential of multimodal AI as a fruitful direction for future research. He suggests that while text-only models can still achieve significant advancements, integrating multiple modalities could enhance AI capabilities further.
"go. But at some point the data will run out. What is the most valuable source of data? Is it Reddit, Twitter, books? Where would you train many other tokens of other varieties for? Generally sp..."
Sutskever reflects on OpenAI's past decision to step back from robotics due to data limitations. He outlines the current landscape, suggesting that with enough commitment and resources, significant progress in robotics is now possible, emphasizing the need for extensive data collection.
"seems like a very fruitful direction. If you're comfortable talking about this, where is the place where we haven't scraped the tokens yet? Obviously I can't answer that question for us but I'..."
In this segment, Sutskever discusses the complexities of defining alignment in AI. He suggests that rather than a single mathematical definition, multiple perspectives will be necessary to ensure AI systems behave as intended, particularly as they approach AGI capabilities.
"I think one could make progress in robotics today, with enough motivation. What ideas are you excited to try but you can't because they don't work well on current hardware? I don't think current..."
Sutskever shares his thoughts on the most promising approaches to AI alignment, advocating for a combination of methods. He emphasizes the need for adversarial testing and internal analysis of neural networks to reduce the risk of misalignment as AI capabilities grow.
"Alright, so let's say it's something that's almost AGI. Where is AGI? Depends on what your AGI can do. Keep in mind that AGI is an ambiguous term. Your average college undergrad is an AGI, righ..."
Discussing the future of AI research, Sutskever reflects on the current understanding of models and the need for deeper insights. He envisions a scenario where smaller, well-understood neural networks help analyze larger, complex models to ensure their safe deployment.
"And you also want to be in a world where your degree of alignment keeps increasing faster than the capability of the models. Do you think that the approaches we’ve taken to understand the model..."
Sutskever speculates on the future role of AI in research, suggesting that advanced AI could assist humans by generating fruitful ideas. He discusses the potential for AI to enhance human creativity and problem-solving capabilities, rather than replacing them.
"Today when you use Copilot, how do you divide it up? So I expect at some point you ask your descendant of ChatGPT, you say — Hey, I'm thinking about this and this. Can you suggest fruitful ideas..."
In this segment, Sutskever contemplates the criteria for a billion-dollar prize in alignment research. He suggests a retrospective evaluation approach, where significant progress is recognized after a set period, rather than immediate judgment.
"So rather than say that there is a prize committee that decides right away, you wait for five years and then award it retroactively. But there's no concrete thing we can identify as you solve t..."
Sutskever discusses the implications of achieving AGI and the existential questions it raises about human purpose and meaning. He envisions a future where AI aids in personal enlightenment and societal problem-solving, while also acknowledging the challenges of adapting to rapid changes.
"sensible extrapolations of anything. Maybe that would be one answer. You need to have data, you can’t come up with those things out of thin air because otherwise, your error bars are going to be..."
Exploring the concept of merging human capabilities with AI, Sutskever reflects on the potential for individuals to enhance their understanding and problem-solving abilities through integration with AI technologies. He expresses intrigue about the future of human evolution alongside AI.
"What are you personally doing after AGI comes? The question of what I'll be doing or what people will be doing after AGI comes is a very tricky question. Where will people find meaning? But I t..."
Sutskever addresses the uncertainty of future developments, particularly in the year 3000. He emphasizes that change is constant and that the evolution of society will continue beyond AGI, advocating for a world where individuals retain the freedom to learn and grow.
"Are you going to become part AI? It is very tempting. Do you think there'll be physically embodied humans in the year 3000? 3000? How do I know what’s gonna happen in 3000? Like what does i..."
In this reflective segment, Sutskever shares his thoughts on the progress of AI since 2015, acknowledging both the advancements and the areas where expectations have not been met. He discusses the importance of deep learning and the unpredictable nature of technological growth.
"morally and progress forward on their own, with the AGI providing more like a base safety net. How much time do you spend thinking about these kinds of things versus just doing the research? I d..."
Sutskever compares TPUs and GPUs, revealing that they are fundamentally similar in function despite initial perceptions of their differences. He discusses the implications of hardware costs and performance on AI development, emphasizing the importance of cost efficiency.
"Well, no in 2015, I did have all these best with people in 2016, maybe 2017, that things will go really far. But specifics. So it's like, it's both, it's both the case that it surprised me and I..."
Sutskever elaborates on the balance between generating new ideas and understanding existing AI models. He highlights the complexity of neural networks and the critical need for researchers to comprehend results and underlying phenomena to drive future advancements.
"and you have a lot of memory and there is a bottleneck between those two. And the problem that both the TPU and the GPU are trying to solve is that the amount of time it takes you to move one fl..."
Ilya Sutskever shares his positive experiences with Microsoft Azure as a platform for machine learning. He praises Microsoft's support in optimizing Azure for AI workloads, indicating the importance of strong partnerships in the tech industry. This segment underscores the collaborative nature of AI development.
"part is where the real action takes place. Does that describe your entire career? If you think back on something like ImageNet, was that more new idea or was that more understanding? Well, that..."
Sutskever addresses potential vulnerabilities in the AI ecosystem, particularly concerning geopolitical events like natural disasters in Taiwan. He discusses the implications of such setbacks on AI compute resources and the resilience of the industry. This segment raises awareness about the fragility of AI infrastructure.
"and we’re super happy with it. How vulnerable is the whole AI ecosystem to something that might happen in Taiwan? So let's say there's a tsunami in Taiwan or something, what happens to AI in ge..."
In this segment, Sutskever explores the relationship between the cost of inference for AI models and their utility. He argues that as long as the output of a model is valuable, higher costs can be justified. This discussion highlights the economic considerations in deploying AI technologies.
"is. If it is more useful than it is expensive then it is not prohibitive. To give you an analogy, suppose you want to talk to a lawyer. You have some case or need some advice or something, you're..."
Sutskever discusses the risk of AI models becoming commoditized and the strategies to prevent this. He emphasizes the need for continuous improvement and innovation in AI to maintain value and trustworthiness. This segment delves into the competitive dynamics of the AI market.
"and more reliable, more trustworthy, so you can trust their answers. All those things. Yeah. But let's say it's 2025 and somebody is offering the model from 2024 at cost. And it's still pretty g..."
Ilya Sutskever shares his insights on the trends of convergence and divergence in AI research directions among companies. He predicts a cycle of convergence on immediate goals followed by divergence into long-term explorations. This segment provides a strategic perspective on the future of AI development.
"behavior, where there is a lot of convergence on the near term work, there's going to be some divergence on the longer term work. But then once the longer term work starts to fruit, there will b..."
Sutskever addresses the security challenges faced by AI companies, particularly regarding the protection of model weights from espionage. He reassures that OpenAI has robust security measures in place, highlighting the importance of safeguarding intellectual property in the AI landscape.
"Yeah. We talked about this a little bit at the beginning. But as foreign governments learn about how capable these models are, are you worried about spies or some sort of attack to get your weig..."
In this segment, Sutskever discusses the potential emergent properties of large AI models, focusing on reliability and controllability. He expresses excitement about the possibilities these properties could unlock for AI applications. This segment emphasizes the importance of understanding model behavior at scale.
"What will happen in this parameter count, what will happen in that parameter count? I think it's possible to make some predictions about specific capabilities though it's definitely not simple a..."
Sutskever reflects on the inevitability of progress in AI, considering the historical context of technological advancements. He speculates on how the deep learning revolution might have unfolded differently without key pioneers. This segment provides a philosophical perspective on the trajectory of AI development.
"force behind the fact that the data exists, that the GPUs exist, and that the transformers exist? The data exists because computers became better and cheaper, we've got smaller and smaller trans..."
Ilya Sutskever shares his thoughts on the challenges of aligning superhuman AI models with human values. He acknowledges the current understanding of alignment but warns of the complexities involved as AI capabilities advance. This segment highlights the critical importance of alignment research in the future of AI.
"one. You don't need to optimize your code as much. When the ImageNet data set came out, it was huge and it was very, very difficult to use. Now imagine you wait for a few years, and it becomes v..."
Sutskever addresses the relationship between digital models and the physical world, arguing that there is no clear distinction between the world of bits and atoms. He illustrates this by discussing how neural networks can influence real-world actions, such as rearranging one's living space based on AI suggestions, thus demonstrating their tangible impact.
"very meaningful contributions. Other than that, do you think academia will come up with important insights about actual capabilities or is that going to be just the companies at this point? ..."
Ilya Sutskever reflects on the potential for future breakthroughs in AI, questioning whether they will be as significant as the Transformer model. He suggests that many advancements may seem obvious in hindsight, yet they will still represent crucial steps forward in understanding and implementing AI capabilities.
"I don't think that there is a clean distinction between the world of bits and the world of atoms. Suppose the neural net tells you — hey here's something that you should do, and it's going to im..."
In this segment, Sutskever discusses the nature of deep learning breakthroughs, emphasizing that many significant insights may have been overlooked in the past. He explains how the understanding of neural networks and backpropagation has evolved, leading to a recognition of their capabilities that was not initially apparent.
"obvious that such and such a thing can work. The reason the Transformer has been brought up as a specific advance is because it's the kind of thing that was not obvious for almost anyone. So peop..."
Sutskever evaluates a new algorithm proposed by his former advisor, which aims to train neural networks without backpropagation. He discusses its relevance to neuroscience and the challenges of replicating brain-like learning processes, while also affirming the effectiveness of backpropagation in engineering robust AI systems.
"What is your opinion of your former advisor’s new forward forward algorithm? I think that it's an attempt to train a neural network without backpropagation. And that this is especially interesti..."
Ilya Sutskever shares his perspective on the role of human intelligence in guiding AI research. He emphasizes the importance of being inspired by human cognition while cautioning against fixating on non-essential qualities. Sutskever advocates for focusing on fundamental principles that can lead to meaningful advancements in AI.
"It's the only algorithm. I guess I've heard you in different contexts talk about using humans as the existing example case that AGI exists. At what point do you take the metaphor less seriousl..."
In the closing segment, Sutskever reflects on his journey in AI research, attributing his success to perseverance and a continuous effort to explore new ideas. He acknowledges the complexity of achieving breakthroughs and the necessity of having the right mindset and approach in the field of artificial intelligence.
"we just need to focus on getting our own basics right. One can and should be inspired by human intelligence with care. Final question. Why is there, in your case, such a strong correlation betw..."