reasoning
Why making an AI think out loud helps it remember facts, even nonsense thinking News
Google Research found that reasoning traces help a model recall facts partly just by buying it extra computation, so even repeating 'let me think' helps, though hallucinated steps backfire.
Chain-of-thought: why making an AI think out loud makes it smarter Lesson
Asking a model to work through a problem step by step, instead of blurting an answer, dramatically improves it on hard tasks. Here is why that simple trick works, what it really buys the model, and where it backfires.
What makes an AI an "agent"? Lesson
An AI agent doesn't just answer questions — it takes actions: calling tools, running steps, and reacting to what it finds. Here's the loop at the core of every agent, and why agents fail in their own peculiar ways.
The little words that keep AI from getting boring News
Rewarding a reasoning model too hard makes it repetitive — and the casualties are tiny words like "but" and "instead" that let it branch to a better thought. A near-free fix protects them.
Reward-based fine-tuning (RLHF and RLVR) Lesson
After a model is first trained, it gets "polished" by rewarding good answers. Here's what that phase is, why it works, and the failure mode where models get repetitive and dull.
veRL Tool
The open RL post-training framework used by most research labs training reasoning models today. Run GRPO, PPO, and related reward-training methods on your own models.