Black Forest Labs ships a 7B open-weights robot control model that beats the RoboLab-120 benchmark. FLUX 3 Action is a World Action Model, meaning it takes camera frames, robot state, and a text instruction, then jointly predicts future video frames and the next action chunk rather than treating perception and control as separate steps. The 7B parameter model is open-weights, so it can run locally without a cloud dependency. It tops the RoboLab-120 benchmark, which is currently the standard leaderboard for this class of model. Black Forest Labs is best known for its FLUX image generation models, making this a significant pivot toward physical AI. (MarkTechPost)
Brief
Friday, September 25, 2026 · 5 min read
Meta's Muse AI Will Hand Over Its Entire Filesystem
Good morning. Meta's week started with Muse topping the App Store. It ended with researchers showing you can ask Muse to zip up its entire root filesystem and it will oblige. Somewhere between those two data points is a product launch that went very well and a security review that did not.
Today's reading time is 5 minutes.
SECURITY
Muse launched to strong numbers earlier this week, but the product's sandbox controls were not keeping pace with its user growth.
Driving the news: Two developers, Peter James and Jonny L. Saunders, say they independently prompted Muse into compressing and sharing the full contents of its root filesystem, including Ubuntu system files and app templates. The disclosure came through The Verge. Neither researcher appears to have needed elevated access or unusual technical knowledge to pull it off. Meta has not yet issued a public patch or statement as of this writing.
- The leaked contents reportedly included Ubuntu system files, app templates, and other internal filesystem contents.
- Both researchers say they reached the same result independently, suggesting the path is not obscure or hard to find.
Zoom in: Muse is Meta's consumer-facing AI agent, released this week to strong early numbers. A separate story today also flagged that Muse's interface bears a close resemblance to a competing agent platform called OpenClaw, which is a different problem but adds to the week's noise around the product. Consumer AI agents that run with access to underlying system resources carry a different risk profile than a chatbot, and this is a concrete demonstration of what that looks like when containment fails.
- Muse topped the App Store charts shortly after launch, per an Apptopia estimate cited by The Verge.
- The filesystem exposure is separate from the design-similarity controversy also reported today.
Why it matters: If you are building on top of consumer AI agents or recommending them to clients, this is the week's clearest reminder that 'early experiment' and 'production-safe' are not the same thing. Any workflow that involves an agent with system-level access needs to treat containment as a first-class requirement, not an afterthought. The people who found this were not adversarial researchers, they were developers poking around.
Bottom line: Muse had a great launch week by every metric except the one that matters most: it will give you its keys if you ask nicely enough.
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Also happening
BottleCap AI releases a fine-tune that cuts thinking tokens by 37.2% at a cost of under 1 percentage point of accuracy. ThinkingCap-Qwen3.8-27B is a drop-in replacement for Qwen3.8-27B on vLLM and SGLang, supporting FP8 and NVFP4 quantization. Macro accuracy moves from 86.65% to 85.79%, a 0.86 percentage point drop, while long-context performance actually improves by 2.25 points. Fewer thinking tokens means lower inference cost and faster time-to-first-token for anyone running the model at scale. The trade-off is explicit and benchmarked across 12 tasks, which is more transparency than most fine-tune releases offer. (MarkTechPost)
Gemini can now make phone calls to local businesses on your behalf, starting on Pixel 11. Google is rolling out an early experiment that lets Gemini handle calls like reservations, stock checks, and appointment changes without the user ever picking up. It works without initiating the call yourself, Gemini dials, talks, and reports back. The feature is Pixel 11-exclusive at launch. This is a direct expansion of the phone-call delegation capability Google has been building since the Duplex era, now surfaced through the Gemini interface. (The Verge)
ElevenLabs CEO says companies using AI voices for customer service should disclose it, at least for now. In an interview with TechCrunch, the CEO of ElevenLabs, now reportedly valued at $22 billion, said businesses should tell customers when they are speaking to an AI voice, though he framed it as a transitional norm rather than a permanent requirement. ElevenLabs powers the synthetic voice on a significant share of enterprise customer service calls. The CEO also discussed margins and IPO timing without committing to a timeline. The disclosure comment is notable because ElevenLabs has a direct commercial interest in wider AI voice adoption, making the candor somewhat inconvenient for the industry's quieter operators. (TechCrunch)
The thread
Open weights, lower cost, same capability
Two of today's stories arrive at the same place from different directions. Black Forest Labs released a 7B open-weights robot control model that tops its category benchmark, and BottleCap AI showed you can cut inference cost by more than a third on a large reasoning model while giving up less than one percentage point of accuracy. Both moves reduce the gap between what you can run yourself and what requires a hosted API, which is the gap that most per-token pricing depends on.
From the publisher
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On our radar
- Meta announced Horizon Create and Horizon Studio, two tools that let users build games for its Horizon social platform using AI prompts, one mobile and one browser-based.
- Midjourney's alpha interface now supports edits and thumbnail previews of styles, with a live preview toggle that shows how a prompt looks across the full style library.
- A developer on r/LocalLLaMA built a custom inference engine for Qwen3.8-Flash-Next that pushes output speed from 15 tokens per second to 65 on a single 12GB GPU, with prompt processing hitting 430 tokens per second.
- Muse's interface design is drawing comparisons to a competing agent platform, with The Verge reporting the resemblance is close enough to be notable, though no legal action has been announced.
- A new arXiv paper introduces DEEPO, a reinforcement learning method targeting hallucination in multimodal models by fixing two weak points in the reward-to-parameter-update chain.
- TW3Cast, a time-series forecasting system using lightly fine-tuned foundation models, reached third place out of 130 entries on the GIFT-Eval benchmark using only training-split data for model selection.
- Researchers published a benchmark paper, TWIST, proposing a new way to measure whether conversational AI intervenes appropriately when a user's beliefs or memory state changes, a property current benchmarks do not test.
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