Ⓜ️ Meta Opens Muse to DIY Devices

Meta’s open-source platform connects the Muse AI agent to real hardware. Install the SDK on an ESP32, Raspberry Pi, or another Linux computer, then add compatible components. The SDK and firmware use the Apache 2.0 license.

That can produce a desktop AI assistant with a screen, a voice assistant, or a reminder display. Meta also showed Muse Home Link, a small USB device based on ESP32-C5 that connects Muse to a home network.

Ready-made skills let Muse control Philips Hue, TVs, speakers, and other devices. It can turn on lights, operate a TV, or send a document to a printer.

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🤖 GPT-6 Astra Played WoW Blind

With the monitor off, GPT-6 Astra completed the orc starting zone in about 40 minutes without processing rendered frames. It read the game through its network protocol via agent-wow.

A Python script converted message types into a live world view. Server SQL files exposed quest and NPC data, while Astra handled selling junk and upgrading gear. The author says it never died.

For movement, Astra created a C++ helper to plan routes on a navigation mesh. Agent-wow had no ready-made movement or combat systems, and the only instruction was to create an orc and finish the starting zone.

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🍏 Alyx Reaches Apple Vision Pro

The game runs natively, without a PC or streaming. The headset does all the rendering.

Valve ported Alyx to ARM64 for its Steam Frame headset, using a Qualcomm Snapdragon chip. An open project by ShinyQuagsire runs Android VR apps on Vision Pro. AI filled the compatibility gaps, followed by optimization.

On Vision Pro with the M5 chip, Alyx reaches about 3K per eye at 60 fps, with smoothing up to 120 fps. Its creator says that is much better than the game ran on his powerful gaming PC in 2020.

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🤖 OpenAI Math Claim Draws Scrutiny

The reported result involved an internal model more capable than GPT-6 Astra, solving the Navier-Stokes problem with 10,000 parallel agents. In September, OpenAI said it would not claim the result. The problem is one of 7 Millennium Prize Problems, carrying a $1M prize.

1 day later, NYU professor Tristan Buckmaster and Anthropic researcher Levent Alpoge published work on a related problem using Codex and Claude. Buckmaster says OpenAI followed the same route.

The dispute concerns training data and quiet edits to published papers. OpenAI denies using specific user data but says anonymized data may have improved its models.

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🤖 Anthropic releases cheaper Haiku 5.5

Anthropic’s first Haiku update in a year costs up to 20 times less than Sonnet 5.5. It is already available to all users.

The model handles routine work, including summaries and document tasks, plus search support for Opus and Sonnet. Benchmarks put it ahead of GPT-6 Luna.

📊@tech