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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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  3. 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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Thursday