Australia considers copyright changes for AI training and OpenAI solves over 100 open math problems as Anthropic's Mythos launch triggers global AI confidence crisis.
how this picture was made
Painted by @cf/leonardo/lucid-origin on workers-ai.cloudflare.com, 2026-09-22 00:48Z. Scene directed by @cf/meta/llama-3.3-70b-instruct-fp8-fast.
The scene the art director wrote
A dimly lit conference room with a large wooden table at its center, where a diverse group of people with concerned expressions discuss and gesture, surrounded by empty chairs and faintly visible cityscape outside the window, with a subtle glow of laptop screens and a few scattered papers and notebooks.
Inside the house scaffold (the fixed style + safety clauses), the full prompt the painter received
Sprawling painted editorial illustration for a newspaper front page: A dimly lit conference room with a large wooden table at its center, where a diverse group of people with concerned expressions discuss and gesture, surrounded by empty chairs and faintly visible cityscape outside the window, with a subtle glow of laptop screens and a few scattered papers and notebooks. Rich painterly texture, coherent single scene, cinematic light, extreme wide panoramic banner composition that FILLS THE ENTIRE FRAME edge to edge: the painted scene reaches all four edges, no black bars, no border, no letterboxing, no empty margins. Every person has a natural, fully painted face with real features: never faceless, never blank mannequins, never smooth featureless heads. All people are fictional and resemble no real public figure. Strictly no text anywhere: no letters, no numbers, no typography, no signs, no billboards, no banners, no placards, no storefront lettering, no printed pages, no screen text, no watermark, no logos. No such surface appears in the picture at all: not lettered, and not blank either, because an empty screen or billboard leaves the figures around it reacting to nothing.
The picture's own pin (SHA-256 of the exact bytes served)
26008680a5807c105950b9b0797ffe0935a82fab1e1656d33cb592f95832e5ba
Xiaomi ships open-weight MiMo-V2.6-Pro and MiMo-V2.6-Flash
Xiaomi released MiMo-V2.6-Pro and MiMo-V2.6-Flash as open-weight omnimodal models this week, while separate papers probe where open-weight LLM reasoning and vision still break down.
By Marcus Feld · 2wXiaomi released MiMo-V2.6-Pro and MiMo-V2.6-Flash as open-weight omnimodal AI models, with weights, a technical report, reinforcement-learning environments, and training code in the release.
The week's papers test where open-weight LLMs fall short, though none touches MiMo. One investigation tracked how four open-weight models internally represent cost tradeoffs, and whether their decisions shift as the specified cost direction and magnitude predict. A separate evaluation ran a 140,000-trial product choice benchmark to ask whether LLMs show human-like decision-making.
Two frameworks target reasoning quality. LogicTrack is a neuro-symbolic framework aimed at the gap where LLMs land on correct final answers through logically flawed intermediate chains. Security Reasoning Topology models reasoning through three structures: Linear, Branching, and Graph. On the vision side, frontier vision-language models describe natural images fluently but cannot read scientific images in the VIALS benchmark.
None of these papers evaluates MiMo, and a release is exactly that: a release. The models' behavior is unmeasured until someone runs the evals. Xiaomi published the weights, the RL environments, and the training code, which is the set of materials a team needs to run that measurement itself.
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