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Sunday

Saturday

Sunday

  1. Story1 reports · 1 facts

    Rohan Paul says AI helped Meta increase ad volume by 14% and prices by 12%

    On October 17, 2026, Rohan Paul put forward the judgment that AI increased Meta's ad volume by 14% and raised prices by 12%, because AI can better predict users' needs before they search. The same report also mentioned that Meta's advertising business is narrowing its revenue gap with Google Search, with quarterly revenue currently differing by only about $4 billion. At present, this judgment appears only in this one source, and there are no subsequent factual developments.

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  2. Story1 reports · 1 facts

    Xbow uses AI to discover Chrome vulnerability chain, wins Google bounty

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

    escapes the sandbox hosting the V8 JavaScript engine, then escapes Chrome's operating system process sandbox, and can launch Windows applications from within a malicious webpage; Google has already fixed the related flaws. They chose OpenAI's GPT-5.6 Sol to search the Chrome source code, validate ideas, and build a proof of concept, while strategy formulation, search direction, and verification of results remained the responsibility of the researchers. The AI compute cost $40,000, and they rece

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  3. Story1 reports · 1 facts

    Arena.ai says user satisfaction is the biggest gap for AI labs

    Arena.ai puts forward a judgment: whether users enjoy collaborating with agents is the biggest gap between AI labs. This judgment is based on Arena's tracking of four Agent Arena signals for the best agents from six labs—Anthropic, OpenAI, Google DeepMind, Kimi, xAI, and DeepSeek—from late June to early October. Among them, on the Praise vs Complaint metric, OpenAI and Anthropic were +35 points above the leaderboard average, while Moonshot, xAI, and DeepSeek ranged between +5 and +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. There are currently no further developments.

    orating with agents is the biggest gap between AI labs. This judgment is based on Arena's tracking of four Agent Arena signals for the best agents from six labs—Anthropic, OpenAI, Google DeepMind, Kimi, xAI, and DeepSeek—from late June to early October. Among them, on the Praise vs Complaint metric, OpenAI and Anthropic were +35 points above the leaderboard average, while Moonshot, xAI, and DeepSeek ranged between +5 and +13; on Confirmed Success, the average lab's best model rose from -4 to +14

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Friday

  1. FactRelated story

    Gemini Notebook launches three learning features

    On October 16, 2026, Google launched three learning features for Gemini Notebook. According to the Google Blog, the first is the ability to generate a 60-second Short Video Overview for quickly understanding difficult points; the second is creating an Interactive Learning Overview in Reports to walk through notes, lectures, and reading materials step by step; and the third is the addition of three quiz formats: short answer, multiple choice, and fill-in-the-blank. All of the above content is generated strictly based on the user's own course materials, and users can try it at notebook.google. There are currently no subsequent developments.

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    View story:Google launches three learning features for Gemini Notebook

  2. Story5 reports · 4 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.

    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 fr

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  8. FactRelated story

    English translation is being prepared.

    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.

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

Thursday

Wednesday

  1. Story15 reports · 3 facts

    Gemini 4 Argon appears on the GCP quota page

    On October 13, 2026, Gemini 4 Argon appeared on the GCP quota page. Testing Catalog, citing AiBattle, said the model was expected to launch within a few hours and called it a precursor to an imminent API model release; earlier that day, a Google employee had also teased an upcoming release. That evening, Testing Catalog reported that the model had begun rolling out and was already live in GCP's Agent Studio, where users could test it, with Google AI Studio and the Gemini app expected to follow. On October 14, Google officially released Gemini 4 Argon, open to developers and enterprises worldwide, usable via AI Studio and the Gemini platform API, and supported in Google Antigravity as well as the Gemini app and Search AI Mode for Ultra and Pro subscribers; reports said it supports long decoding output of up to 1,048,576 tokens and announced limited-time introductory pricing.

    ta page. Testing Catalog, citing AiBattle, said the model was expected to launch within a few hours and called it a precursor to an imminent API model release; earlier that day, a Google employee had also teased an upcoming release. That evening, Testing Catalog reported that the model had begun rolling out and was already live in GCP's Agent Studio, where users could test it, with Google AI Studio and the Gemini app expected to follow. On October 14, Google officially released Gemini 4 Argon, o

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