
Black Forest Labs (BFL), the lab behind the FLUX image models, has released FLUX 3 Action. It is a 7B open-weights World Action Model (WAM) for robot control. The model reads camera frames, robot state and a text instruction. It then predicts future video frames and the next chunk of actions together. On the RoboLab-120 leaderboard, it ranks first at 42.92% task success. Is it deployable? Yes, with conditions. The DROID policy needs about 32 GB of GPU memory in BF16 on an H200. It fits 24 GB
Black Forest Labs released FLUX 3 Action, a 7 billion parameter open-weights model designed to control robots by reading camera frames and text instructions, then predicting future video frames and robot actions together. The model ranks first on the RoboLab-120 benchmark at 42.92% task success, outperforming larger competing models while running 1.5 to nearly 4 times faster. This matters because it addresses a tradeoff in robot control systems: models that predict video tend to be accurate but slow, while faster models sacrifice accuracy. The model can be deployed on consumer and professional GPUs with quantization techniques and is available under a non-commercial license with code and documentation for fine-tuning on custom robot demonstrations.

StarSkirmish pits AI-made StarCraft-playing bots against one another, as well as against human-made bots. OpenAI's GPT-6 Astra and Claude Opus 5.5 were essentially tied as the best-performing AI-made bots, but they couldn't top Stardust, the top-rated human-made bot. On Friday, GPT was facing off against Claude and the human-created bot Pluto, but according to Kotaku, it couldn't quite get an edge. So it resorted to a tactic that is becoming alarmingly common for modern AI mod
Datalab has released OmniExtractBench, an open benchmark for structured document extraction. It tests how accurately a system fills a JSON schema from a PDF. The benchmark pools 620 documents from 4 existing benchmarks. One deterministic scorer grades all of them and explains each decision. The release lands while extraction vendors publish their own leaderboards. Datalab argues those leaderboards are hard to compare or audit. OmniExtractBench is its attempt at a shared yardstick. Is it d

Deep Blue took down Garry Kasparov at chess in 1997, AlphaGo beat Lee Sedol at Go in 2016, and poker bots have been beating professionals for years. But one classic game called Stratego held out. Even DeepMind, with its exceptional budget, couldn't build a machine that reliably beat the best human players. Now, a team of researchers from Carnegie Mellon, MIT, New York University, and Stanford University has done it. Their AI, called Ataraxos, beat Pim Niemeijer, arguably the best Stratego player
Want to go deeper than the news? Explore live, cohort-based AI courses taught by practitioners.
Browse AI courses on Maven