Intelligence with Everyone: RL @ MiniMax, with Olive Song, from AIE NYC & Inference by Turing Post

Описание: Olive Song from MiniMax shares how her team trains the M series frontier open-weight models using reinforcement learning, tight product feedback loops, and systematic environment perturbations. This crossover episode weaves together her AI Engineer Conference talk and an in-depth interview from the Inference podcast. Listeners will learn about interleaved thinking for long-horizon agentic tasks, fighting reward hacking, and why they moved RL training to FP32 precision. Olive also offers a candid look at debugging real-world LLM failures and how MiniMax uses AI agents to track the fast-moving AI landscape.

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SPONSORS:
Claude: Claude is the AI collaborator that understands your entire workflow, from drafting and research to coding and complex problem-solving. Start tackling bigger problems with Claude and unlock Claude Pro’s full capabilities at https://claude.ai/tcr

Tasklet: Tasklet is an AI agent that automates your work 24/7; just describe what you want in plain English and it gets the job done. Try it for free and use code COGREV for 50% off your first month at https://tasklet.ai

CHAPTERS:
(00:00) About the Episode
(04:15) Minimax M2 presentation (Part 1)
(17:59) Sponsors: Claude | Tasklet
(21:22) Minimax M2 presentation (Part 2)
(21:26) Research life and culture
(26:27) Alignment, safety and feedback
(32:01) Long-horizon coding agents
(35:57) Open models and evaluation
(43:29) M2.2 and researcher goals
(48:16) Continual learning and AGI
(52:58) Closing musical summary
(55:49) Outro

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