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Wednesday

  1. PyTorch BlogSelected

    Google and Meta jointly launch TorchTPU, enabling PyTorch to run natively on TPUs

    Google and Meta's PyTorch teams have collaborated to launch the open-source project TorchTPU, providing a native PyTorch backend for Google TPUs; migration only requires changing model.to("cuda") to model.to("tpu"). The project supports both eager and torch.compile modes, adds a new DeferAndFuse eager mode, covers about 450 Aten operators, and has been verified to run out of the box on 4,917 Hugging Face models, with a Tier 1 pass rate of 98% and Tier 2 numerical consistency relative to GPUs of 97%. According to the official announcement, it has already been used in the inference and training production workloads of some major Google Cloud customers, and is integrated with vLLM, SGLang, TorchTitan, Ray, and TorchRec.

    Google and Meta's PyTorch teams have collaborated to launch the open-source project TorchTPU, providing a native PyTorch backend for Google TPUs; migration only requires changing model.to("cuda") to model.to("tpu"). The project supports both eager and torch.compile modes, adds a new DeferAndFuse eager mode, covers about 450 Aten operators, and has been verified to run out of the box on 4,917 Hugging Face models, with a Tier 1 pass rate of 98% and Tier 2 numerical consistency relative to GPUs of

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Tuesday

  1. 36Kr · AI

    iFlytek's non-recurring net loss in the first three quarters was 763 million yuan, with its book profit turned positive by subsidies and equity gains

    In the first three quarters, iFlytek's revenue was 18.187 billion yuan, and net profit attributable to shareholders was 21.8872 million yuan, but non-recurring net profit showed a loss of 763 million yuan, more than double the 338 million yuan loss in the same period last year. The book turnaround to positive was mainly due to 471 million yuan in government subsidies, 370 million yuan in equity appreciation of invested companies, and 84 million yuan in asset disposal income, totaling about 785 million yuan. The company's R&D expenses in the first three quarters were 3.850 billion yuan, accounting for more than 21% of revenue, and it attributed the widened non-recurring loss to continued investment in the self-controlled large model route; in public domestic large model tenders in the third quarter, iFlytek ranked first in both the number and amount of bids won.

    In the first three quarters, iFlytek's revenue was 18.187 billion yuan, and net profit attributable to shareholders was 21.8872 million yuan, but non-recurring net profit showed a loss of 763 million yuan, more than double the 338 million yuan loss in the same period last year. The book turnaround to positive was mainly due to 471 million yuan in government subsidies, 370 million yuan in equity appreciation of invested companies, and 84 million yuan in asset disposal income, totaling about 785 m

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  2. 36Kr · AI

    MiniMax Releases M3.1 Flash, Scoring 29.6% on Agents' Last Exam to Rank First Among Chinese Models

    MiniMax has officially released M3.1 Flash, the model previously known as Space Bunny (Yutu) that topped the charts anonymously on OpenRouter. It scores 29.6% on Agents' Last Exam, ranking first among Chinese models. The model achieves 73.7% on DeepSWE v1.1, 82.2 points on CyberGym, and 61.7 points on OSWorld V2, with output speeds of up to 200+ TPS and a P50 maintained at 170+ TPS. Pricing is 1 yuan per million input tokens, 4 yuan for output, and 0.1 yuan for cache reads.

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  3. cnBeta

    AI medical consultation meme goes viral across the internet, Baidu unexpectedly caught in the crossfire

    An AI medical consultation meme has gone viral online; its content is said to allude to Baidu, and a German version of the meme has also appeared. The article notes that the earlier claim "20 million people a day see a doctor on Doubao" once trended on social media, showing that many people really are using AI assistants to consult about health issues.

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  4. AI Business

    Smartsheet Takes a "People"-Centered Approach to AI Implementation

    Smartsheet focuses its AI implementation on the people side rather than on the tools themselves, and has established a dedicated role to drive internal AI adoption. Markus McKay-Fleisch, Director of Professional Services Enablement, said that early on they only did simple usage tracking, but later shifted to focusing on what employees gained from the tools. He also noted that while shadow AI brings risks, it is also a clear signal that employees need tools the organization has not yet provided.

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