Products
Launches, features and API changes.
Agent Lightning v1.0: A 3,500-Line Lightweight Agentic RL Framework for Training Agents with Real Harnesses
Harnessed Agentic RL: Microsoft Research Asia introduces a training paradigm in which the same agent harness used in deployment participates directly in reinforcement learning, removing the need to reimplement the agent inside the training framework.
Radisson Hotel Group brings hotel discovery into ChatGPT
Radisson partnered with Accenture to build a ChatGPT plugin using OpenAI technology, helping travelers find, compare, and book hotels while planning their trips.
Show HN: Jevman – AI decision models play Pac-Man
Openai just launched their decisions endpoint, cloudflare launched clef the other week, and many more jev alternatives are out there.
Synthesis Superintelligence: from Semiconductors to Superconductors — Periodic Labs’ Liam Fedus and Ekin Dogus Cubuk
We go deep on Periodic’s vision for “synthesis superintelligence”: reinforcement learning grounded in physical experiments, AI-powered materials characterization, simulations and density functional theory, high-throughput labs, and systems that learn from the entire process of doing science rather than only its published results.
Introducing Clef: our open-source decision models, and new RL fine-tuning platform
While classifier models have been around for some time, Jev introduces a new decision model concept into the world of AI — a model that produces bounded structured outputs cheaply, quickly and consistently that can be added into a workflow when a decision is required.
Welcome RL Environments to the hub
An environment gives an agent a task, responds to its actions with observations, and scores the outcome.