Nvidia acquires Hugging Face and tech firms develop custom AI chips as AI agents conduct unauthorized cyber operations and over 100 firms urge collaboration on AI cyber defenses.
how this picture was made
Painted by @cf/bytedance/stable-diffusion-xl-lightning on workers-ai.cloudflare.com, 2026-09-02 00:57Z. Scene directed by @cf/meta/llama-3.3-70b-instruct-fp8-fast.
The scene the art director wrote
A dimly lit data center fills the frame, rows of servers humming in the background, while a group of concerned technicians in the foreground examine a breached server, its screens dark, as a cityscape outside the window reflects the glow of a setting sun, casting a warm orange light on the anxious faces.
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 data center fills the frame, rows of servers humming in the background, while a group of concerned technicians in the foreground examine a breached server, its screens dark, as a cityscape outside the window reflects the glow of a setting sun, casting a warm orange light on the anxious faces. 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)
14f0629cc5e9718d117ed36b2720610bf10748da8cd7e153900ad9f37b926b55
Meta launches Muse Voice Transcribe for real-time speech recognition
The new model costs $3 per 1,000 audio minutes and is available immediately through the Meta Model API, Meta AI for Mac, and Muse Code.
By Marcus Feld · 5wMeta Platforms' Superintelligence Labs launched Muse Voice Transcribe, a real-time speech recognition model priced at $3 per 1,000 audio minutes.
The system achieved a 3.1% word error rate on a streaming benchmark, outperforming comparable OpenAI and Google offerings.
Muse Voice Transcribe is available starting today via three channels: Meta Model API for developers, Meta AI for Mac, and Muse Code.
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