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Saturday

  1. ChinaTalk

    Why DUV Controls Hold Up: Saif Khan on the U.S.-China AI Chip Rivalry

    Saif Khan, a former U.S. National Security Council and Commerce Department official, predicts in a new DUV report from the new think tank CTS that if exports of the relevant equipment stopped now, by the mid-2030s China could produce roughly 100 times fewer AI chips than the United States, making DUV controls the most critical lever for the United States to shape the AI balance of power. In a ChinaTalk interview, he also discussed how robotics will become the next frontier in U.S.-China AI competition, and how AI is changing policy research itself.

    Saif Khan, a former U.S. National Security Council and Commerce Department official, predicts in a new DUV report from the new think tank CTS that if exports of the relevant equipment stopped now, by the mid-2030s China could produce roughly 100 times fewer AI chips than the United States, making DUV controls the most critical lever for the United States to shape the AI balance of power. In a ChinaTalk interview, he also discussed how robotics will become the next frontier in U.S.-China AI compe

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    #analysis#English text is being prepared.#Industry news
  3. TechCrunch AI

    Elorian Releases Its First Model Glimpse, Using a Visual Draft Space for Image Reasoning

    Elorian has released its first model, Glimpse, opening the API as a research preview, with a waitlist for the chat interface. During reasoning, the model can crop image regions, extract video frames, or run code to measure and compare what it sees, which Elorian calls a visual draft space. Glimpse is priced at $0.60 per million input tokens and $3 per million output tokens, and according to Elorian's evaluations it surpasses GPT-6 Astra on scientific chart reasoning and short video description. The company says the model was trained on several hundred GPUs, a scale notably smaller than the frontier systems it benchmarks against, and it initially targets enterprises with large amounts of video, such as robotics, research laboratories, and media and creative firms.

    Elorian has released its first model, Glimpse, opening the API as a research preview, with a waitlist for the chat interface. During reasoning, the model can crop image regions, extract video frames, or run code to measure and compare what it sees, which Elorian calls a visual draft space. Glimpse is priced at $0.60 per million input tokens and $3 per million output tokens, and according to Elorian's evaluations it surpasses GPT-6 Astra on scientific chart reasoning and short video description.

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    #tech-media#Model releases#Multimodal#Reasoning

Friday

  1. QbitAISelected

    Google Releases Gemini 4 Argon, Limited-Time Half-Price API

    Google has released its flagship model Gemini 4 Argon, focused on coding, professional knowledge work, and sustained execution of complex tasks. The API launch price is $2 per million input tokens and $10 per million output tokens, with the discount running through November 30; from December 1, prices return to $4 and $20. On the third-party Artificial Analysis Intelligence Index, Argon High ties with GPT-6 Astra Max and Claude Fable5.1 Max at 53 points, at an average cost of $1.99 per task, about 39% lower than Astra. Google says that on an ADK project it worked unattended continuously for 11 hours, proposed six optimization plans involving 32 files, and ran 16,892 tests, two of which were merged, reducing long-session memory preparation overhead by about 40%.

    Google has released its flagship model Gemini 4 Argon, focused on coding, professional knowledge work, and sustained execution of complex tasks. The API launch price is $2 per million input tokens and $10 per million output tokens, with the discount running through November 30; from December 1, prices return to $4 and $20. On the third-party Artificial Analysis Intelligence Index, Argon High ties with GPT-6 Astra Max and Claude Fable5.1 Max at 53 points, at an average cost of $1.99 per task, abo

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    #chinese#Model releases#Google#Multimodal
  2. Unite.AI

    Imperial College London paper: search-augmented LLMs often cite web pages they never opened

    Three authors from Imperial College London have published the paper "Retrieved but Not Read: Understanding Why Search-Augmented LLMs Fail to Use Available Evidence," examining why search-augmented LLMs frequently cite web pages they never actually open. The study tested GPT-5.6 Luna and six open-weight configurations including GLM-5.3-Flash, gpt-oss-120b, gpt-oss-20b, gemma-4-31b, and qwen3-8b using 225 facts that changed after February 16, 2026, finding that models often answer based solely on search snippets without opening the source pages; under the same set of search results, the proportion of cases where no page was opened ranged from 2.6% to 76%, and when Luna used its built-in search, 53.6% of turns relied only on snippets. When answering from snippets alone, outdated answers accounted for 6.4% and misleading citations for 6.4%, whereas when pages were opened and cited, these fell to 1.3% and 2.3% respectively; placing the correct page directly into the prompt significantly reduced errors, but some models still favored old information even when shown the new facts.

    Three authors from Imperial College London have published the paper "Retrieved but Not Read: Understanding Why Search-Augmented LLMs Fail to Use Available Evidence," examining why search-augmented LLMs frequently cite web pages they never actually open. The study tested GPT-5.6 Luna and six open-weight configurations including GLM-5.3-Flash, gpt-oss-120b, gpt-oss-20b, gemma-4-31b, and qwen3-8b using 225 facts that changed after February 16, 2026, finding that models often answer based solely on

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    #hot-signal#Papers/Research#RAG#Evaluations / benchmarks
  3. Fortune Tech

    The Death of Humanity: Why AI Doom Theories Don't Hold Up

    Collective[i] co-founder Stephen Messer wrote an article rebutting AI doomsday theories, pointing out that the AI revolution has been underway for thirteen years and large language models have been widely adopted for three years, yet the U.S. unemployment rate remained in the 4.3% to 4.5% range from 2025 through the first three quarters of 2026. He cited a March 2026 paper by Anthropic economists and Danish data covering 25,000 employees and 7,000 enterprises, saying no rise in unemployment was found in jobs highly exposed to AI. He believes doomsayers shifted from job threats to AGI existential risks because dangerous narratives make them appear important.

    Collective[i] co-founder Stephen Messer wrote an article rebutting AI doomsday theories, pointing out that the AI revolution has been underway for thirteen years and large language models have been widely adopted for three years, yet the U.S. unemployment rate remained in the 4.3% to 4.5% range from 2025 through the first three quarters of 2026. He cited a March 2026 paper by Anthropic economists and Danish data covering 25,000 employees and 7,000 enterprises, saying no rise in unemployment was

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

Thursday