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Sunday

  1. FactRelated story

    Four Gemini 4 Argon agents complete Minecraft without human intervention

    The Google DeepMind team had four AI agents running on Gemini 4 Argon autonomously complete Minecraft in a randomly generated world, killing the Ender Dragon with no human input throughout. The team did not assign them roles, strategies, or game-specific tools; the four agents divided the work among themselves, warned each other of threats, recovered items from fallen teammates, and recorded mistakes in a shared memory. The entire run took 27 hours and 14 minutes, during which they wrote a total of 2,783 JavaScript programs, exchanged 229 chat messages, and died 605 times, costing $1,620 at the standard Gemini 4 Argon pricing that takes effect in 2027.

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    View story:Four Gemini 4 Argon agents complete Minecraft without human intervention

Friday

  1. Story1 reports · 1 facts

    Chollet says Argon performs similarly to Astra on ARC-AGI-3

    François Chollet commented that Gemini 4 Argon performs similarly to Astra on ARC-AGI-3, with Google returning to the frontier. On the same day, ARC Prize published the verified results for Gemini 4 Argon on the ARC-AGI series: ARC-AGI-3 scored 97.5% under the provider adapter harness at a cost of $4.8K; under the standard harness it scored 49.8% at a cost of $5.8K. ARC-AGI-2 scored 91.3% at $0.32 per task; ARC-AGI-1 scored 98.5% at $0.16 per task. ARC Prize said Google DeepMind is the second frontier AI lab to exceed 95% on ARC-AGI-3, and Argon's 97.5% is second only to GPT-6 Astra's 99.9%. The standard harness test could not complete all 55 games due to API issues; the high-reasoning setting completed only 19 games, so no score was published.

    er the provider adapter harness at a cost of $4.8K; under the standard harness it scored 49.8% at a cost of $5.8K. ARC-AGI-2 scored 91.3% at $0.32 per task; ARC-AGI-1 scored 98.5% at $0.16 per task. ARC Prize said Google DeepMind is the second frontier AI lab to exceed 95% on ARC-AGI-3, and Argon's 97.5% is second only to GPT-6 Astra's 99.9%. The standard harness test could not complete all 55 games due to API issues; the high-reasoning setting completed only 19 games, so no score was published.

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  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

Sunday

Tuesday

Thursday

Tuesday

Thursday

Thursday

  1. Google Blog

    Google releases Gemini education research results in the UK and Italy

    Google announced the results of its Gemini classroom research in the UK and Italy: a 10-week randomized controlled trial in the UK covering more than 1,100 students aged 12 to 15 found that AI tutoring performed similarly to human tutoring on platform tasks and quizzes, but showed no improvement on the STAR standardized test. A study of 31 schools and 1,600 teachers in Italy showed that after teachers used Gemini to co-design lessons, traditional lecturing decreased by 38%, student-led collaborative learning nearly tripled, and student engagement rose from 77% to 84%.

    A teacher crouching next to a student seated at a desk as they talk. In front of the student are papers and a laptop.

    Google announced the results of its Gemini classroom research in the UK and Italy: a 10-week randomized controlled trial in the UK covering more than 1,100 students aged 12 to 15 found that AI tutoring performed similarly to human tutoring on platform tasks and quizzes, but showed no improvement on the STAR standardized test. A study of 31 schools and 1,600 teachers in Italy showed that after teachers used Gemini to co-design lessons, traditional lecturing decreased by 38%, student-led collabora

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    #lab#Papers/Research#Google#English text is being prepared.

Tuesday

Tuesday

  3. Huxiu

    Carnegie Report: China Overtakes the US for the First Time as the Top Destination for Leading AI Talent, but Talent Still Nets Outflow

    A global AI talent report released by Carnegie China on September 23 shows that in 2025, 41% of the world's top AI researchers work in China and 34% in the US, compared with 27% versus 46% three years ago. Tracking the résumés of 10,280 authors from NeurIPS 2025, the report notes a net outflow of 1,729 people from China and a net inflow of 2,145 into the US; 98% of top researchers working in China did their undergraduate studies in China, versus only about 30% in the US. Among institutions, Peking University rose to first place, with Tsinghua second and Shanghai Jiao Tong University fourth. The report also acknowledges that its sample skews toward academia and underestimates industry.

    A global AI talent report released by Carnegie China on September 23 shows that in 2025, 41% of the world's top AI researchers work in China and 34% in the US, compared with 27% versus 46% three years ago. Tracking the résumés of 10,280 authors from NeurIPS 2025, the report notes a net outflow of 1,729 people from China and a net inflow of 2,145 into the US; 98% of top researchers working in China did their undergraduate studies in China, versus only about 30% in the US. Among institutions, Peki

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

Saturday

Thursday