Olive Song
Senior researcher specializing in reinforcement learning and model evaluation at Minimax, involved in developing the M series open-weight models and agentic coding capabilities.
Top 3 podcasts with Olive Song
Ranked by the Snipd community
99 snips
Feb 13, 2026 • 1h 28min
📆 Open source just pulled up to Opus 4.6 — at 1/20th the price
Olive Song, senior reinforcement learning researcher at MiniMax who led the M2.5 release and the Forge RL framework, joins to explain MiniMax M2.5’s 80.2% SWE‑Bench result and compact 10B active‑param design. Conversation covers RL training strategies, speed and efficiency optimizations, open‑source tradeoffs, and how agentic workflows speed iteration. Quick, technical and forward‑looking.
66 snips
Feb 22, 2026 • 55min
Intelligence with Everyone: RL @ MiniMax, with Olive Song, from AIE NYC & Inference by Turing Post
Olive Song, a senior researcher in reinforcement learning at Minimax who helped build the M series open-weight models, discusses training M2 with RL, tight product feedback, and perturbation pipelines. She covers long-horizon agentic coding, reward-hacking and alignment challenges, FP32 RL decisions, and using internal agents to track fast-moving research.
Mar 11, 2026 • 32min
Inside MiniMax: How They Build Open Models
Olive Song, a senior MiniMax researcher specializing in reinforcement learning and model evaluation. She recounts midnight model drops and debugging fp32 precision in the LM head. She shares stories of models “hacking” rewards, real-time developer experiments, ICU-in-the-morning/KTV-at-night swings, and why MiniMax opens weights while wrestling with safety and environment adaptation.
