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Friday

  1. Computerworld

    Xbow used $40,000 of AI compute to find a Chrome exploit chain, earning a $250,000 bounty from Google

    Researchers at Xbow USA spent six days developing a Chrome exploit chain that first escaped the sandbox hosting the V8 JavaScript engine, then escaped Chrome's operating system process sandbox, allowing a Windows application to be launched from within a malicious webpage; Google has fixed the relevant flaws. They chose OpenAI's GPT-5.6 Sol to search Chrome source code, validate ideas, and build a proof of concept, while strategy formulation, search direction, and result verification remained the responsibility of the researchers. The AI compute cost $40,000, and they received a $250,000 bug bounty from Google, the first under the new 2026 rules.

    he sandbox hosting the V8 JavaScript engine, then escaped Chrome's operating system process sandbox, allowing a Windows application to be launched from within a malicious webpage; Google has fixed the relevant flaws. They chose OpenAI's GPT-5.6 Sol to search Chrome source code, validate ideas, and build a proof of concept, while strategy formulation, search direction, and result verification remained the responsibility of the researchers. The AI compute cost $40,000, and they received a $250,000

    Matched fieldsTitle、Summary、Body

    #hot-signal#Safety / alignment#Agents#OpenAI
  2. The Decoder

    Google Gemini 4 Argon scores 97.5% on ARC-AGI-3, but drops to 49.8% when the test environment is changed

    Google DeepMind's new frontier model Gemini 4 Argon scored 97.5% on ARC-AGI-3 in the Provider Adapter Harness test environment at a cost of $4,800, becoming the second lab after OpenAI to cross 95%, second only to GPT-6 Astra's 99.9%. Under the Standard Harness, which allows only simple notes, the low-reasoning setting's score dropped to 49.8%, and due to API issues it was unable to complete all 55 games. On Epoch AI's ECI index, Argon scored 165, on par with Fable 5.1, but ranked eighth on the math ECI and sixth on the software engineering index.

    Google DeepMind's new frontier model Gemini 4 Argon scored 97.5% on ARC-AGI-3 in the Provider Adapter Harness test environment at a cost of $4,800, becoming the second lab after OpenAI to cross 95%, second only to GPT-6 Astra's 99.9%. Under the Standard Harness, which allows only simple notes, the low-reasoning setting's score dropped to 49.8%, and due to API issues it was unable to complete all 55 games. On Epoch AI's ECI index, Argon scored 165, on par with Fable 5.1, but ranked eighth on the

    Matched fieldsTitle、Summary、Body

    #ai-vertical#Evaluations / benchmarks#Google#DeepMind
  6. François CholletSelected

    Chollet: Gemini 4 Argon performs comparably to Astra on ARC-AGI-3, Google returns to the frontier

    François Chollet stated that Gemini 4 Argon's performance on ARC-AGI-3 is close to Astra's, and Google has returned to the frontier. Data cited by ARC Prize shows that Google DeepMind's Gemini 4 Argon achieved 97.5% (provider adapter harness, $4.8K) and 49.8% (standard harness, $5.8K) on ARC-AGI-3, 91.3% at $0.32/task on ARC-AGI-2, and 98.5% at $0.16/task on ARC-AGI-1, making it the second frontier AI lab to exceed 95% on ARC-AGI-3.

    Matched fieldsTitle、Summary

    #hot-signal#Evaluations / benchmarks#Google#DeepMind

Thursday