←Search results

Search “OpenAI”

By relevance · Total 3714 results Clear search

Sunday

Saturday

  6. OpenAISelected

    GPT-6 Pro upgrade in ChatGPT, supporting multi-agent parallel task processing

    OpenAI announces that GPT-6 Pro in ChatGPT has been upgraded, with faster responses and improved use of plugins and tools. The new capability is that multiple agents can process different parts of the same task in parallel, and users can track each agent's progress and open completed tasks to view their work results. This feature is now available to Pro users in the Chat tab.

    Matched fieldsSummary

    #hot-signal#Product updates#Agents#OpenAI
  9. Arena

    Arena tracks four signals for agents from six major AI labs

    Arena tracked four Agent Arena signals for the best agents from Anthropic, OpenAI, Google DeepMind, Kimi, xAI, and DeepSeek from late June to early October, finding that the largest gap between labs lies in whether users enjoy the experience of using them. On Praise vs Complaint, OpenAI and Anthropic scored +35 points above the leaderboard average, while Moonshot, xAI, and DeepSeek ranged from +5 to +13; on Confirmed Success, the average lab's best model rose from -4 to +14 points within three months, with Anthropic leading at +20 with Claude Opus 5.5 (Max). The Bash Recovery gap narrowed from 34 to 16 points, and Steerability from 19 to 11 points.

    Arena tracked four Agent Arena signals for the best agents from Anthropic, OpenAI, Google DeepMind, Kimi, xAI, and DeepSeek from late June to early October, finding that the largest gap between labs lies in whether users enjoy the experience of using them. On Praise vs Complaint, OpenAI and Anthropic scored +35 points above the leaderboard average, while Moonshot, xAI, and DeepSeek ranged from +5 to +13; on Confirmed Success, the average lab's best model rose from -4 to +14 points within three m

    Matched fieldsSummary、Body

    #editorial#English text is being prepared.#Agents#Evaluations / benchmarks

Friday

  2. 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.

    n 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

    Matched fieldsSummary、Body

    #hot-signal#Safety / alignment#Agents#OpenAI
  4. 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 fieldsSummary、Body

    #ai-vertical#Evaluations / benchmarks#Google#DeepMind