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  2. A Yi AI Notes

    AI Personal Website Tutorial: Feishu Doc Draft Plus a List of Nearly 70 UI Design Sites

    A hands-on tutorial on building a personal website with AI presents a two-step workflow: first create a Feishu document as the content draft and let AI read it through the Feishu command-line tool, so that editing the document syncs the page; then pull components, animations, and layouts from existing design sites and feed them to AI for assembly. The author organizes nearly 70 sites by 8 tasks, including component libraries such as shadcn/ui, Aceternity UI, and Magic UI; animation tools such as Motion, GSAP, Three.js, and Spline; whole-site inspiration sites such as Godly, Land-book, and Awwwards; AI website-building tools such as v0, Lovable, and Google Stitch; and 4 design Skills including Anthropic's frontend-design. The article notes that referencing interaction styles and using open-source components is fine, but do not copy entire sites' visual assets and copy; check the license agreements before commercial use, and Tailwind Plus and the full version of Mobbin are paid subscriptions.

    animation tools such as Motion, GSAP, Three.js, and Spline; whole-site inspiration sites such as Godly, Land-book, and Awwwards; AI website-building tools such as v0, Lovable, and Google Stitch; and 4 design Skills including Anthropic's frontend-design. The article notes that referencing interaction styles and using open-source components is fine, but do not copy entire sites' visual assets and copy; check the license agreements before commercial use, and Tailwind Plus and the full version of Mo

    Matched fieldsSummary、Body

    #hot-signal#Tutorials / practice#Agents#English text is being prepared.

Friday

  3. ARC PrizeSelected

    ARC Prize announces evaluation results of Gemini 4 Argon on the ARC-AGI series

    ARC Prize announces the validated results of Google Gemini 4 Argon on ARC-AGI: ARC-AGI-3 reaches 97.5% (provider adapter harness, cost $4.8K), and 49.8% under the standard harness (cost $5.8K); ARC-AGI-2 is 91.3%, at $0.32 per task; ARC-AGI-1 is 98.5%, at $0.16 per task. ARC Prize states that 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 failed to complete all 55 games due to API issues, and the high reasoning tier completed only 19 games so no score was published; costs are calculated at the current discounted price of $2 per million input tokens and $10 per million output tokens.

    ARC Prize announces the validated results of Google Gemini 4 Argon on ARC-AGI: ARC-AGI-3 reaches 97.5% (provider adapter harness, cost $4.8K), and 49.8% under the standard harness (cost $5.8K); ARC-AGI-2 is 91.3%, at $0.32 per task; ARC-AGI-1 is 98.5%, at $0.16 per task. ARC Prize states that 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 failed to complete all 55 games due to API issues

    Matched fieldsSummary、Body

    #company#Evaluations / benchmarks#Reasoning#Google

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  1. Story5 reports · 3 facts

    Google releases the Gemini 4 Carbon model

    On October 28, 2026, Google DeepMind released Gemini 4 Carbon, calling it its strongest model, ranking first with 59 points on the Artificial Analysis Intelligence Index v5.0, and scoring 88.2% on SEC-bench Pro, 54.8% on ExploitGym, and 71.0% on CWE-bench. The model targets long-horizon engineering tasks and was first opened to some cybersecurity defenders, then expanded through the Fairwind Program, and afterward made available to developers, enterprises, and consumers. On October 29, Arena.ai said Gemini 4 Carbon ranked second in Agent Arena with a net improvement of 16.2% and pushed the Pareto frontier forward; the same day, Yuchen Jin cited Artificial Analysis data to raise reservations, noting that the evaluation used the Antigravity CLI. On October 30, the Artificial Analysis Intelligence Index showed it in first place with 59 points, 1 point higher than Claude Opus 5.5. On October 31, Perplexity CEO Aravind Srinivas shared an early evaluation, saying it set a new SoTA on the WANDR benchmark.

    On October 28, 2026, Google DeepMind released Gemini 4 Carbon, calling it its strongest model, ranking first with 59 points on the Artificial Analysis Intelligence Index v5.0, and scoring 88.2% on SEC-bench Pro, 54.8% on ExploitGym, and 71.0% on CWE-bench. The model targets long-horizon engineering tasks and was first opened to some cybersecurity defenders, then expanded through the Fairwind Program, and afterward made available to developers, enterprises, and consumers. On October 29, Arena.ai

    Matched fieldsTitle

Wednesday

  1. FactRelated story

    Google releases Gemini 4 Carbon model

    On October 28, 2026, Google DeepMind released Gemini 4 Carbon, calling it its strongest model, ranking first with 59 points on the Artificial Analysis Intelligence Index v5.0, and scoring 88.2% on SEC-bench Pro, 54.8% on ExploitGym, and 71.0% on CWE-bench. The model targets long-horizon engineering tasks and was first opened to some cybersecurity defenders, then expanded through the Fairwind Program, and afterward made available to developers, enterprises, and consumers. On October 29, Arena.ai said Gemini 4 Carbon ranked second in Agent Arena with a net improvement of 16.2% and pushed the Pareto frontier forward; the same day, Yuchen Jin cited Artificial Analysis data to raise reservations, noting that the evaluation used the Antigravity CLI. On October 30, the Artificial Analysis Intelligence Index showed it in first place with 59 points, 1 point higher than Claude Opus 5.5. On October 31, Perplexity CEO Aravind Srinivas shared an early evaluation, saying it set a new SoTA on the WANDR benchmark.

    Matched fieldsTitle

    View story:Google releases the Gemini 4 Carbon model