A new study reveals that top models like DeepSeek-R1 succeed by simulating internal debates. Here is how enterprises can harness this "society of thought" to build more robust, self-correcting agents.

A new technical paper titled “Multi-Agent Reinforcement Learning for Microprocessor Design Space Exploration” was published by researchers at Harvard University and Google research groups.

Google researchers introduce ‘Internal RL,’ a technique that steers an models' hidden activations to solve long-horizon tasks ...

In 2026, enterprises will be expected to automate processes that involve judgment, negotiation, compliance interpretation, ...