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Meta spent the past year looking behind in the AI race. This week it shipped two models that put it back in the conversation. Microsoft showed off a chip meant to cut its Nvidia bill, and drones started hitting data centers in a war. Here is what is solid and what is still a claim.
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TODAY IN AI
3 things that happened while you were busy
1. Meta releases Muse Wonder and Muse Wonder Full. On the Artificial Analysis Intelligence Index, Wonder Full scores 56 and Wonder scores 52, up from 48 for Meta's last model. That puts Wonder Full ahead of GPT-6 Astra at 53 but behind Claude Opus 5.5 at 58. Wonder costs $4 per million input tokens and $20 per million output tokens. Wonder Full is only available through a Muse Code subscription at $50 or $200 a month. See the full benchmark breakdown.
2. Microsoft unveils Maia 300, its third-generation AI chip. Microsoft claims it produces 40% more tokens per megawatt than GPU systems, without naming which GPU or what test. The chip does not arrive yet. The rollout starts in 2027 and is planned at multi-gigawatt scale, after which Microsoft says Maia will be the main hardware for running its own AI products. Read the chip details.
3. Ukrainian drones hit two Yandex data centers in two days. On October 8, an attack shut down a hub in Sasovo that houses two of the three supercomputers Yandex uses to build its AI models. On October 9, another data center near Kaluga was partly knocked out. Yandex says its teams are working to keep services running, and no casualties were reported at the sites. See Al Jazeera's report.
FROM THE FRONTIER
The AI race is now fought over chips, power and buildings
The comeback. Meta's Muse Wonder Full is a clear step up from its predecessor. Meta also says Wonder beats Claude Fable, Opus and Astra on a memory test called MemoryBench, but it has not published the per-benchmark numbers. Treat that as a claim until someone reproduces it. Read the launch summary.
The catch. Artificial Analysis found that Wonder costs $4.52 per task to run the index, against $7.63 for Claude Fable 5.1 and $3.26 for GPT-6 Astra. It also scores lower on general knowledge than Opus 5.5 and Astra, with a hallucination rate of 27% for Wonder and 23% for Wonder Full. Strong at agents and coding, weaker as an encyclopedia. See the cost and accuracy tables.
The silicon. Microsoft is building Maia because running AI is the bill that never stops. A full Maia 300 rack holds 96 accelerators and draws 167 kW, which is a lot of electricity before you count cooling. The efficiency claim is the whole point of the project. See the rack specs.
The targets. Ukraine's strikes came after Russia hit Ukrainian data centers and telecom sites over the past month, and Zelenskyy said Ukraine responds in a mirror-like fashion. When data centers train a country's AI models and run its everyday apps, they stop being neutral buildings. Read the background.
The reframe. The question for the next year is not which model is smartest. It is who can afford to run a good model, power it and keep it standing. Model rankings change in weeks, while chips and data centers take years.
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IN THE KNOW
What people are actually watching and sharing
Bot band. Michael Smith of North Carolina got 18 months in prison for collecting about $8M in music royalties. He used as many as 10,000 bot accounts to stream his AI-generated songs. In April 2023 alone, his bots logged 80.9 million streams on YouTube Music family plans. Read the sentencing story.
Hurricane forecasting by AI. Forecasters at the National Hurricane Center leaned on Google DeepMind's model for Hurricane Isaias from the start, and it called a Category 2 storm before the system had a name. Director Michael Brennan said the AI models have been more consistent from run to run. See how it played out.
A million tokens. Both Muse Wonder models handle text, image, video and audio inputs with a 1M token context window. They reply in text only. Check the spec sheet.
Where Maia is made. The chip's compute chiplets are built by TSMC on its N2P process, with eight HBM4 memory stacks per chip. That keeps Microsoft's independence from Nvidia only partial. Dig into the hardware.
PROMPT STATION
Pick the right AI model for your budget
New models launch every week, and the cheapest one is rarely the smartest. This prompt works in any chatbot with web search on. Tell it your task and monthly volume, and it compares real prices and returns a shortlist you can test this afternoon.
COPY AND PASTE THIS PROMPT
You are a practical advisor for a non-technical business owner. My task is [TASK, e.g. answering customer emails]. I expect about [VOLUME] requests per month and my budget is [MONTHLY BUDGET]. Search the web for current prices and independent benchmarks for the three to five most relevant AI models. Build a comparison with: price per task or per million tokens, strengths, weaknesses, and hallucination risk for my task. Mark any number that comes from the vendor rather than an independent test. Recommend one model to try first and one cheaper fallback, and give me a simple five-question test I can run to check them. Link every source and write UNVERIFIED for anything you cannot confirm.
Tip: Swap [TASK] with writing product descriptions, summarizing meetings or sorting support tickets, and [VOLUME] with a real number like 2,000. For a safer test, add: "Include one model I can run for free."