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Tuesday

  1. Huxiu

    Where the money of the top 100 US VCs and CVCs flowed in the first three quarters of 2026

    In the first three quarters of 2026, global startup funding reached $679 billion, a record high for the same period, of which US companies took about $515.8 billion, up about 44% year over year. Tracking 100 US VC and CVC institutions, the report finds that capital is shifting from picking winners to directly purchasing capacity such as data centers, GPUs, power, and defense contracts, with 27 billion-dollar financings in Q3. Corporate venture capital already accounts for 87.9% of the amount of US AI venture deals; among the 25 VC sample, the top 10 companies by amount took 39.2% of funding, and the average deal size of $137 million is 5.7 times the median of $23.98 million.

    In the first three quarters of 2026, global startup funding reached $679 billion, a record high for the same period, of which US companies took about $515.8 billion, up about 44% year over year. Tracking 100 US VC and CVC institutions, the report finds that capital is shifting from picking winners to directly purchasing capacity such as data centers, GPUs, power, and defense contracts, with 27 billion-dollar financings in Q3. Corporate venture capital already accounts for 87.9% of the amount of

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

    AI FinOps ①: Why Traditional FinOps Can't Control AI Costs

    A Harness.io survey of about 700 global enterprises shows that 67% of enterprises spend at least $250,000 per month on AI, and 73% of AI projects exceed budget because AI workload costs are hard to predict. The article points out four major reasons why traditional cloud FinOps fails in the AI environment: token-based billing, multi-model environments, rapid model iteration, and the acceleration of code generation and agentic workflows. The survey also shows that 57% of surveyed enterprises encourage employees to use AI without restrictions, and Harness.io estimates that 26% of monthly AI budgets are wasted as a result.

    A Harness.io survey of about 700 global enterprises shows that 67% of enterprises spend at least $250,000 per month on AI, and 73% of AI projects exceed budget because AI workload costs are hard to predict. The article points out four major reasons why traditional cloud FinOps fails in the AI environment: token-based billing, multi-model environments, rapid model iteration, and the acceleration of code generation and agentic workflows. The survey also shows that 57% of surveyed enterprises encou

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

Monday

Sunday

  3. 36Kr · AISelected

    Anthropic says Mythos 5 autonomously designed quantum circuits, surpassing human optimal solutions in 53 hours

    Anthropic announced a study in which Mythos 5, given only natural language task descriptions, fully autonomously closed-loop designed 8 basic quantum circuits within 53 hours, all surpassing the best publicly published human designs. In the divsteps task in number theory and cryptography, it autonomously derived a new algebraic identity and completed formalization in Lean, reducing the number of quantum gates by 17 times while increasing qubits by only 12%; in the DQI decoding task, it switched to the Berlekamp-Massey decoding method and precisely calculated storage requirements, reducing gate count by 12 times compared with the original architecture. The research comes from Anthropic's STEM Fellows project, and the text also mentions that FeMoco simulation gate count dropped from the 50 trillion estimated by humans in 2017 to 340 million over 8 years.

    Anthropic announced a study in which Mythos 5, given only natural language task descriptions, fully autonomously closed-loop designed 8 basic quantum circuits within 53 hours, all surpassing the best publicly published human designs. In the divsteps task in number theory and cryptography, it autonomously derived a new algebraic identity and completed formalization in Lean, reducing the number of quantum gates by 17 times while increasing qubits by only 12%; in the DQI decoding task, it switched

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    #hot-signal#Papers/Research#Reasoning#Anthropic

Friday

  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

Saturday

  2. Fortune Tech

    Giorgos Tsetis: No one bears personal responsibility for AI, and this must change

    Giorgos Tsetis, co-founder of Nutrafol and an AI investor, is calling for executives of AI companies to bear personal legal liability, rather than having the company simply pay a fine and be done with it. He noted that an agreement on internal risk controls, independent audits, and board-level safety oversight signed at the White House in late September by leaders of several major AI companies is entirely voluntary, and no one has yet been held personally accountable. Drawing on his own experience running a supplements company, he explained that personal liability prompts companies to proactively identify risks and put safeguards in place in advance, and when necessary to slow down or say no.

    Giorgos Tsetis, co-founder of Nutrafol and an AI investor, is calling for executives of AI companies to bear personal legal liability, rather than having the company simply pay a fine and be done with it. He noted that an agreement on internal risk controls, independent audits, and board-level safety oversight signed at the White House in late September by leaders of several major AI companies is entirely voluntary, and no one has yet been held personally accountable. Drawing on his own experien

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