Uploaded June 2026 | Updated September 2026, 2 weeks ago
In this episode, we have Mark Chen, Chief Research Officer at OpenAI, joining us to make Korean tofu stew and flambé shrimp. From scaling laws and why pre-training is not dead, to the o1 reasoning bet, evals crisis, research taste, long-context learning, and the future of end-to-end AI research, we cover what it takes to push models toward the frontier.
We talk about:
• Why Mark still believes in scaling laws and the exponential
• How OpenAI chooses research bets and allocates compute
• Why reasoning became one of OpenAI’s biggest bets
• How to develop research taste without a traditional ML background
• Why evals are in crisis and benchmarks can be misleading
• What it takes for models to do long-horizon, real-world work
• How AI could change the future of research itself
00:00 – Intro
00:13 – Welcome to Latent Space Cooking
00:28 – The Soup Story: Meta, OpenAI, and Research Recruiting
01:52 – From Trading to AI Research
03:21 – Developing Research Taste
04:26 – AlphaGo, Move 37, and the Rise of Agents
05:23 – RL, Hard-to-Grade Tasks, and Superhuman Evals
08:17 – Cooking Begins on the Impulse Stove
08:53 – Scaling Laws, Pre-Training, and Bear Takes
10:26 – Why Reasoning Became a Core Bet
12:33 – OpenAI’s Research Roadmap and Compute Allocation
15:48 – What Makes a Great Researcher
17:44 – Top Researchers vs. Top Engineers
19:33 – The Evals Crisis and Benchmark-Maxing
21:32 – Building Better Benchmarks
23:40 – Jakub Pachocki, Humor, and “Dumb IOI Gold Medalists”
24:34 – Jagged Intelligence and Why Models Miss Easy Tasks
25:56 – Long Context, Compaction, and Long-Horizon Learning
27:14 – Shrimp Flambé and One-Shot Learning
28:36 – Low-Hanging Fruit vs. New Research Bets
29:39 – Continual Learning and the Road to AGI
31:32 – Multimodal Models and One Architecture
32:36 – Vibe Researching and End-to-End AI Research
34:36 – Failed Bets, Postmortems, and OpenAI’s Alpha
37:07 – Final Seasoning and Taste Test
37:53 – Overrated vs. Underrated AI Research
38:42 – Plating and First Taste
39:15 – External Evals: The Soup Judge
41:00 – ChatGPT Prep and Closing
In this episode, we have Mark Chen, Chief Research Officer at OpenAI, joining us to make Korean tofu stew and flambé shrimp. From scaling laws and why pre-training is not dead, to the o1 reasoning bet, evals crisis, research taste, long-context learning, and the future of end-to-end AI research, we cover what it takes to push models toward the frontier.
We talk about:
• Why Mark still believes in scaling laws and the exponential
• How OpenAI chooses research bets and allocates compute
• Why reasoning became one of OpenAI’s biggest bets
• How to develop research taste without a traditional ML background
• Why evals are in crisis and benchmarks can be misleading
• What it takes for models to do long-horizon, real-world work
• How AI could change the future of research itself
00:00 – Intro
00:13 – Welcome to Latent Space Cooking
00:28 – The Soup Story: Meta, OpenAI, and Research Recruiting
01:52 – From Trading to AI Research
03:21 – Developing Research Taste
04:26 – AlphaGo, Move 37, and the Rise of Agents
05:23 – RL, Hard-to-Grade Tasks, and Superhuman Evals
08:17 – Cooking Begins on the Impulse Stove
08:53 – Scaling Laws, Pre-Training, and Bear Takes
10:26 – Why Reasoning Became a Core Bet
12:33 – OpenAI’s Research Roadmap and Compute Allocation
15:48 – What Makes a Great Researcher
17:44 – Top Researchers vs. Top Engineers
19:33 – The Evals Crisis and Benchmark-Maxing
21:32 – Building Better Benchmarks
23:40 – Jakub Pachocki, Humor, and “Dumb IOI Gold Medalists”
24:34 – Jagged Intelligence and Why Models Miss Easy Tasks
25:56 – Long Context, Compaction, and Long-Horizon Learning
27:14 – Shrimp Flambé and One-Shot Learning
28:36 – Low-Hanging Fruit vs. New Research Bets
29:39 – Continual Learning and the Road to AGI
31:32 – Multimodal Models and One Architecture
32:36 – Vibe Researching and End-to-End AI Research
34:36 – Failed Bets, Postmortems, and OpenAI’s Alpha
37:07 – Final Seasoning and Taste Test
37:53 – Overrated vs. Underrated AI Research
38:42 – Plating and First Taste
39:15 – External Evals: The Soup Judge
41:00 – ChatGPT Prep and Closing
