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Tuesday

Monday

  1. MarkTechPost

    The Evolution of Qwen: From 7B to 2.4T, a Full Retrospective of Alibaba's AI Model Series

    Alibaba Cloud's Qwen series began with Tongyi Qianwen in April 2023, open-sourced Qwen-7B in August 2023, launched the first Qwen3-Max-Preview with over 1 trillion parameters in September 2025, and ultimately evolved to an open-weight model with 2.4 trillion parameters. In 2024, three generations—Qwen1.5, Qwen2, and Qwen2.5—were released in succession; Qwen2.5's pre-training data grew from 7 trillion to 18 trillion tokens, and model downloads exceeded 40 million. In 2025, Qwen3 adopted a hybrid thinking mode, covering 119 languages, and Qwen3-Next-80B-A3B claims training costs of only 10% of Qwen3-32B and 10x higher inference throughput above 32K tokens.

    Alibaba Cloud's Qwen series began with Tongyi Qianwen in April 2023, open-sourced Qwen-7B in August 2023, launched the first Qwen3-Max-Preview with over 1 trillion parameters in September 2025, and ultimately evolved to an open-weight model with 2.4 trillion parameters. In 2024, three generations—Qwen1.5, Qwen2, and Qwen2.5—were released in succession; Qwen2.5's pre-training data grew from 7 trillion to 18 trillion tokens, and model downloads exceeded 40 million. In 2025, Qwen3 adopted a hybrid

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    #ai-vertical#Industry news#Open-source ecosystem#English text is being prepared.
  5. Huxiu

    Profit Is Not in the Tool: Why AI Applications Don't Make Money, and Why Profit Lies in To B Workflow Capture

    The root cause of AI applications not making money lies on the supply side: for single-point capabilities such as writing code, creating images, and translation, supply is abundant and switching costs are zero, so profits are bound to trend toward zero. The path that can actually collect money is to B workflow capture, that is, taking over a company's complete business processes and tying to the ROI of its real P&L—helping a client earn an extra 500,000 per month can justify charging 300,000. The best testing ground is labor-intensive cognitive labor industries such as e-commerce, livestreaming, game guilds, and insurance sales.

    The root cause of AI applications not making money lies on the supply side: for single-point capabilities such as writing code, creating images, and translation, supply is abundant and switching costs are zero, so profits are bound to trend toward zero. The path that can actually collect money is to B workflow capture, that is, taking over a company's complete business processes and tying to the ROI of its real P&L—helping a client earn an extra 500,000 per month can justify charging 300,000. Th

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    #hot-signal#English text is being prepared.#Industry news

Sunday

  4. TechCrunch AI

    AWS CEO responds to data center controversy: no longer using NDAs

    Amazon Web Services CEO Matt Garman said in a blog post that the company no longer uses non-disclosure agreements (NDAs) when partnering with government agencies to build data centers. He also rebutted four claims about data centers—that they consume too much water, drive up electricity prices, cause serious pollution, and bring no benefit to communities—saying that direct water use by data centers accounts for only 0.5% of U.S. industrial water use, that backup generators sit idle 99.9% of the time, and that over the past three years Amazon has invested more than $1 billion in U.S. communities where it has data centers.

    Amazon Web Services CEO Matt Garman said in a blog post that the company no longer uses non-disclosure agreements (NDAs) when partnering with government agencies to build data centers. He also rebutted four claims about data centers—that they consume too much water, drive up electricity prices, cause serious pollution, and bring no benefit to communities—saying that direct water use by data centers accounts for only 0.5% of U.S. industrial water use, that backup generators sit idle 99.9% of the

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    #tech-media#Industry news#OpenAI#Anthropic

Saturday

Friday