Outcome-driven reinforcement learning has advanced reasoning in large language models (LLMs), but prevailing tool-augmented approaches train a single, monolithic policy that interleaves thoughts and tool calls under full context; this scales poorly with long horizons and diverse tools and generalizes weakly to new scenarios. Agentic systems offer a promising alternative by decomposing work across specialized modules, yet most remain training-free or rely on offline training decoupled from the live dynamics of multi-turn interaction. We introduce AgentFlow, a trainable, in-the-flow agentic framework that coordinates four modules (planner, executor, verifier, generator) through an evolving memory and directly optimizes its planner inside the multi-turn loop. To train on-policy in live environments, we propose Flow-based Group Refined Policy Optimization (Flow-GRPO), which tackles long-horizon, sparse-reward credit assignment by converting multi-turn optimization into a sequence of tractable single-turn policy updates. It broadcasts a single, verifiable trajectory-level outcome to every turn to align local planner decisions with global success and stabilizes learning with group-normalized advantages. Across ten benchmarks, AgentFlow with a 7B-scale backbone outperforms top-performing baselines with average accuracy gains of 14.9% on search, 14.0% on agentic, 14.5% on mathematical, and 4.1% on scientific tasks, even surpassing larger proprietary models like GPT-4o. Further analyses confirm the benefits of in-the-flow optimization, showing improved planning, enhanced tool-calling reliability, and positive scaling with model size and reasoning turns.

Hollywood's actors and writers will join forces on the picket line from Friday, after studios failed to reach a deal this week with the Screen Actors Guild – American Federation of Television and Radio Artists (SAG-AFTRA). It is the first time the two unions have been on strike simultaneously since 1960, when actor – and future US president – Ronald Reagan led the protests. Among SAG-AFTRA's 160,000-strong ranks are many of the world's biggest stars. Hollywood's A-listers, from Tom Cruise to Angelina Jolie to Johnny Depp, are card-carrying union members. Stars including Meryl Streep, Ben Stiller and Colin Farrell have come out publicly in favour of the strike.

Lanfrica is an online resource centre that catalogues, archives and links African language resources. These resources include research papers, datasets, projects, software and models that have to do with one or more African languages. The team behind Lanfrica is Chris Emezue, Handel Emezue, and Bonaventure Dossou, with contribution from Daria Yasafova. We caught up with them to find out more about the project, what inspired them to begin, and the potential that Lanfrica offers the AI community and beyond. Chris: The inspiration came while Bona and I were working as undergraduate students.