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Nov 10

Tuesday
  1. Claude Fable 5.2 and Mythos 5.2 cement Anthropic's AI lead just before its IPO

    Anthropic is releasing Claude Fable 5.2 and Mythos 5.2, its most powerful models to date, in two versions: one freely available and one reserved for verified organizations. The models solve open physics problems, show stronger cybersecurity capabilities, design functioning operating systems, and write more than 90 percent of the changes merged into Anthropic's core code, according to the company.

Nov 9

Monday
  1. Google ships four TPU variants in one year as it ramps up competition with Nvidia

    Google is expanding its TPU 8 family with two specialized variants: the TPU 8tx keeps sensitive data encrypted even during processing, while the TPU 8i Max doubles compute power and memory by placing two chips on a single package. With nearly 100 external customers now on board, Google is increasingly positioning its in-house chips as an alternative to Nvidia's GPUs.

Nov 8

Sunday

Nov 7

Saturday
  1. All the latest updates on AI data centers

    Massive new data centers are the physical foundation for tech companies’ hopes and dreams for AI. But the rush to expand warehouses full of energy-hungry servers has also kicked up fights across the world over their impact on power grids, utility bills, nearby communities, and the environment.

Nov 6

Friday
  1. Google's Gemini Omni 1.2 Flash stretches AI video clips to 15 seconds and cuts pricing by 30 percent

    Google Deepmind is making Gemini Omni 1.2 Flash generally available. The video-generation model now creates clips up to 15 seconds long, can be edited step by step via conversation, and costs just $0.07 per second at 720p, 30 percent less than its predecessor. Users who draft in low resolution and upscale only the final result can save even more.

Nov 5

Thursday
  1. GPT-6 Astra sees the matrix and reprograms other AI models directly through their weights

    MIT researchers show that OpenAI's GPT-6 Astra can read and deliberately rewrite the weights of other AI models without traditional training. In one experiment, Astra boosted a Qwen model's math accuracy from 7.9 to 48.1 percent by changing just 0.016 percent of its weights. The approach could fundamentally simplify AI optimization but still hits clear limits.

Nov 4

Wednesday