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Scaling and the Road to Human-Level AI | Anthropic Co-founder Jared Kaplan
14 segments available
Jared Kaplan on June 16th, 2025 at AI Startup School in San Francisco. Jared Kaplan started out as a theoretical physicist chasing questions about the universe. Then he helped uncover one of AI’s most surprising truths: that intelligence scales in a predictable, almost physical way. That insight became foundational to the modern era of large language models—and led him to co-found Anthropic. In this talk, he walks through how that discovery reshaped the path to human-level AI, what it means for future models like Claude, and why even the dumbest questions can lead to the biggest breakthroughs. He reflects on memory, oversight, and what’s left to solve as models grow smarter—and longer-horizon tasks come within reach. Apply to Y Combinator: https://ycombinator.com/apply Chapters: 00:17 - From Physics to AI 01:41 - Initial Skepticism and Shift to AI 02:12 - AI Training Phases 02:32 - Pre-Training 03:16 - Reinforcement Learning 04:19 - Scaling Laws in Training 08:19 - Unlocking AI Capabilities 11:27 - Organizational Knowledge and Memory 12:19 - Oversight and Nuanced Tasks 13:38 - Preparing for the Future 15:48 - Claude 4 and Beyond 21:18 - Human-AI Collaboration 29:50 - Scaling Laws and Compute Efficiency 35:26 - Audience Q&A
Segments Timeline
From Physics to AI Journey
Jared Kaplan shares his transition from a theoretical physicist to working in AI and the motivations behind it.
"Hey everyone. Um, I'm Jared Kaplan. I'm going to talk briefly about scaling and the road to human level AI, but my guess is for this audience, a lot of these ideas are pretty familiar, so I'll keep it..."
The Two Phases of AI Training
Exploring the essential phases of pre-training and reinforcement learning in contemporary AI models.
"when I was in school. But I got convinced that that maybe AI would be an exciting field to work on. Um, and I I got very lucky to know the right people and the rest is history. So uh I'm going to talk..."
Predictable Scaling Trends in AI Training
This segment explores the surprising precision of scaling laws in AI training and their implications for future advancements.
"that are chosen to be helpful, honest, and harmless. And we discourage the behaviors that are bad. So really all there is to training these models is learning to predict the next word and then doing r..."
Scaling Laws in Reinforcement Learning
This segment discusses the emergence and significance of scaling laws in reinforcement learning, particularly through the example of AlphaGo and the game Hex.
"underlies uh uh improvements in in AI. The other is actually also something that started to appear quite a long time ago although it's become really really impactful uh in the last couple of years is ..."
Unlocking AI Capabilities Systematically
This segment discusses how advancements in AI are defined by systematic improvements in its capabilities across various tasks.
"researchers are really smart or they suddenly got smart. It's that we found a very very simple way of making AI better systematically and and we're we're turning that crank. So what kinds of capabilit..."
Future AI: Organizational Knowledge and Memory
This segment explores the future capabilities of AI models, emphasizing the importance of organizational knowledge and memory to achieve human-level performance.
"tasks that the AI models uh can can do, including longer and longer horizon tasks. And so you can sort of speculate about where this is heading. And in AI 2027 folks did. And this kind of picture sugg..."
Mastering Nuanced AI Oversight
This segment discusses the importance of nuanced oversight in AI development to solve complex tasks beyond simple, clear-cut problems.
"think will become increasingly important. A third ingredient that I think that we need to get better at and and we're making progress on is oversight. the ability of AI models to understand sort of fi..."
Harnessing AI to Transform Integration
Exploring how AI can facilitate its own integration into various fields and the potential rapid adoption in new areas.
"that there'll be a Claude 5 coming that will make that make that product work and deliver a lot of value. So I think that's that's something that I always recommend is sort of experiment on the bounda..."
The Rise of AI Collaboration
Exploring the evolution of AI as a capable collaborator in longer tasks and the implications for human involvement.
"unlocking longer and longer horizon tasks. I think that like as as time goes on we're going to see Claude as a collaborator that can sort of take on larger and larger chunks of work. This is to your p..."
Unlocking Insights Across Disciplines
This segment explores how AI's extensive knowledge can unearth insights by integrating information from various fields, particularly in science, finance, and law.
"trying to prove one theorem for a decade like the threemon hypothesis or firmat's last theorem. Um I think that's that's sort of solving one very specific very hard problem. I think there's a lot of a..."
Precision in Understanding AI Trends
This segment emphasizes the importance of clarifying macro trends in AI to enhance understanding and drive innovation.
"I think the thing that was useful from a physics point of view is looking for the biggest picture, most macro trends and then trying to make them as precise as possible. So I remember meeting like kin..."
Rethinking AI Scaling Laws
This segment explores potential failures in scaling laws within AI training and the implications of reduced compute power and precision in advancing AI capabilities.
"very interesting to examine where it's failing. But I think that my first inclination is to think if scaling laws are failing, it's because we've screwed up AI training in some way. Maybe we got uh we..."
Navigating the Future of AI Careers
This segment explores essential skills and strategies for staying relevant in an evolving AI landscape.
"to sort of orchestrate a much dumber model to break the task down into very very small slices and put them together. So, I do kind of expect that a lot of the value is going to come from the most capa..."
Optimizing Long-Horizon AI Training
This segment discusses the complexities and strategies in training AI models for long-term, complex tasks, emphasizing the role of both AI and human input in task development.
"very kind of operationally intensive path where you just sort of build more and more different tasks for AI models to do that are more and more complex, more and more long horizon and you just sort of..."