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Ilya Sutskever – We're moving from the age of scaling to the age of research

2025-11-25 Science & Technology
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Dwarkesh Patel
Dwarkesh Patel
1.3m subscribers

Ilya Sutskever on Model Generalization, Pre-training Limits, and SSI's Research Path

Discover why current AI models fail to generalize like humans and how SSI plans to pivot research beyond the scaling paradigm to achieve robust intelligence. This discussion details the critical bottlenecks in AI development and the necessary shift toward continual learning principles.

Short Summary

  • Current AI success relies on scaling pre-training, but this method suffers from inadequate generalization compared to human capability.
  • Reinforcement Learning (RL) training appears susceptible to reward hacking focused narrowly on evaluation benchmarks, leading to fragility.
  • SSI views the field as returning to an “age of research,” requiring fundamental breakthroughs in learning mechanisms, not just increased compute.
  • Ilya emphasizes that true AGI might be better defined as a continuously learning agent rather than a static, fully knowledgeable entity.
  • SSI’s focus is an attempt to investigate superior learning principles, potentially leading to an AI robustly aligned to care for sentient life.

This conversation with Ilya Sutskever examines the limitations discovered following the scaling era of deep learning. We explore the disconnect between high evaluation scores and real-world performance, analyze the role of Value Functions, and contrast pre-training reliance against the sample efficiency of human learning. This breakdown focuses on identifying the next fundamental research challenge required for safe, scalable superintelligence.

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Description

Ilya & I discuss SSI’s strategy, the problems with pre-training, how to improve the generalization of AI models, and how to ensure AGI goes well. 𝐄𝐏𝐈𝐒𝐎𝐃𝐄 𝐋𝐈𝐍𝐊𝐒 * Transcript: https://www.dwarkesh.com/p/ilya-sutskever-2 * Apple Podcasts: https://podcasts.apple.com/us/podcast/dwarkesh-podcast/id1516093381?i=1000738363711 * Spotify: https://open.spotify.com/episode/7naOOba8SwiUNobGz8mQEL?si=39dd68f346ea4d49 𝐒𝐏𝐎𝐍𝐒𝐎𝐑𝐒 - Gemini 3 is the first model I’ve used that can find connections I haven’t anticipated. I recently wrote a blog post on RL’s information efficiency, and Gemini 3 helped me think it all through. It also generated the relevant charts and ran toy ML experiments for me with zero bugs. Try Gemini 3 today at https://gemini.google - Labelbox helped me create a tool to transcribe our episodes! I’ve struggled with transcription in the past because I don’t just want verbatim transcripts, I want transcripts reworded to read like essays. Labelbox helped me generate the *exact* data I needed for this. If you want to learn how Labelbox can help you (or if you want to try out the transcriber tool yourself), go to https://labelbox.com/dwarkesh - Sardine is an AI risk management platform that brings together thousands of device, behavior, and identity signals to help you assess a user’s risk of fraud & abuse. Sardine also offers a suite of agents to automate investigations so that as fraudsters use AI to scale their attacks, you can use AI to scale your defenses. Learn more at https://sardine.ai/dwarkesh To sponsor a future episode, visit https://dwarkesh.com/advertise 𝐓𝐈𝐌𝐄𝐒𝐓𝐀𝐌𝐏𝐒 00:00:00 – Explaining model jaggedness 00:09:39 - Emotions and value functions 00:18:49 – What are we scaling? 00:25:13 – Why humans generalize better than models 00:35:45 – Straight-shotting superintelligence 00:46:47 – SSI’s model will learn from deployment 00:55:07 – Alignment 01:18:13 – “We are squarely an age of research company” 01:29:23 -- Self-play and multi-agent 01:32:42 – Research taste

Top Comments (10)

@modalmixture 2025-11-26

“My cofounder said yes to Meta, and as a result he was able to enjoy a lot of near-term liquidity” has to be the most polite way of saying someone sold out

2.1k 39 replies
@ackium 2025-11-25

"Talent hits a target no one else can hit; Genius hits a target no one else can see."

1.3k 30 replies
@attisday 2025-11-25

Ilya is looking good, glad to see he's got his enthusiasm back

663 18 replies
@tarmicachiwara2973 2025-11-26

13:44 “certainly! i’ll be very happy to do that.” this is chatgpt’s dad

427 10 replies
@ralphschraven339 2025-11-25

I love someone like Ilya recognizing the absurdity of this AI-driven reality. It's not just us feeling that way, it's everyone. Even Ilya.

180 11 replies
@HighlandArmsM1911 2025-12-04

18:13 I can’t wrap my head around how the interviewer can hear Ilya cracking open such an interesting nut about how our emotions play into our reward function, and how our hunger “emotion” has ceased to serve us in a world with abundant food,and go “yup people have talking about scaling data” and launches into another topic. Ilya said a lot of really interesting things in this one, but that one really left me wanting to hear him expound upon how biological urges could map onto value functions.

145 14 replies
@Joedcastroa1 2025-11-26

35:25 Bro just vibe researched…

114
@kaio0777 2025-11-27

hearing Ilya i am reminded how truly wise he is and how he understand his field so well. i am in awe.

15
@kellymurphy9844 2025-11-27

I'm glad that you pre-interview prep didn't kill you - like always, you invested the time and Ilya knew it

13 1 replies
@omar.r.d9016 2025-11-27

This was so fun to watch, bring Ilya on again whenever possible

12

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