What matters for RL? Precision! Switching BF16 → FP16
BF16 vs FP16: how switching precision during RL fine-tuning fixes training-inference mismatch, stabilizes GRPO, and why Karpathy applied it to nanochat.
A 4-phase framework for AI adoption in engineering teams — from champion-led experiments to org-wide SDLC integration. Strategies, metrics & real case studies.
Guest Post: The Coding Personalities of Leading LLMs*
GPT-4o, Claude, Llama tested on 4,400+ coding tasks: each LLM has a distinct risk profile. Newer models aren't always safer — data from Sonar's code quality analysis.