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Viewing history for 2026年10月30日 周五‹ Previous dayNext day ›AccelerationBack to now

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Launches and updates of AI products, features, apps, tools, APIs and platforms.

10/30Fri
  1. Aravind Srinivas72

    Perplexity Computer can now control Google Chrome from the Perplexity Mac and Windows apps after a one-time extension setup, Aravind Srinivas says. Perplexity’s quoted announcement says Computer can use sites users are already signed into, and the extension is live for all Computer users in those apps. https://chromewebstore.google.com/detail/perplexity/pninphncmkphpjgfffammoenglghcjii https://twitter.com/askperplexity/status/2116183470439620676

    Quoted postComputer@AskPerplexity

    Computer's Mac and Windows apps now work in your own Chrome. The new Perplexity extension links the two, so Computer uses sites you're already signed into. Here, it turns a business's reviews into a prioritized list of fixes and replies. Live now for all Computer users in the Mac and Windows apps. Get it: http://chromewebstore.google.com/detail/perplexity/pninphncmkphpjgfffammoenglghcjii

    Why it matters

    Connecting Computer to an existing Chrome session lets browsing tasks use sites where users are already signed in, reducing setup across those sites.

  2. NVIDIA Blog72

    How Agentic AI Helps Search for Extraterrestrial Signals at the Allen Telescope Array

    Breakthrough Listen and the SETI Institute are using agentic AI at the Allen Telescope Array to steer antennas, correct incoming data and apply AI models through natural language requests. NVIDIA Holoscan and related tools support processing 2.4 terabits per second on NVIDIA RTX PRO 6000 Blackwell GPUs, with inference running on premises. The pipeline has already achieved what the source describes as the first real-time AI detection of a pulsar in the Crab Nebula.

    Why it matters

    The observatory workflow illustrates how agents can coordinate instrument control and live data processing when a shared operational state connects natural language requests to scientific hardware.

  3. Aravind Srinivas68

    Aravind Srinivas promotes /unbroker on Perplexity Computer, quoting @AskPerplexity’s announcement that the UNBROKER skill by @SHL0MS is now in Computer’s skills marketplace. The skill finds a person’s listings on data-broker sites and drafts opt-out requests, each requiring approval before sending. Tasks using /unbroker are free through November 6, up to 5,000 credits per user. https://twitter.com/AskPerplexity/status/2115866344730366393

    Quoted postComputer@AskPerplexity

    The UNBROKER skill by @SHL0MS, now in Computer's skills marketplace, finds a person's listings on data-broker sites and drafts opt-out requests. Each request waits for approval before sending. Tasks that use /unbroker are free through November 6, up to 5,000 credits per user.

    Why it matters

    The approval step gives users control over each outgoing opt-out request while the skill handles finding data-broker listings and drafting the requests.

  4. 宝玉76

    OpenAI is doubling all usage limits for Pro 100/200/500 and Business Premium effective today, according to @thsottiaux, while canceling the planned Pro 200 reduction. Baoyu calculates allowances relative to Plus at 10x for Pro 100, 20x for both existing and newer Pro 200 subscribers, and 50x for Pro 500; no price change was mentioned. Extended limits for dots will continue for now, with dot usage remaining separate from default usage; no extension end date was specified.

    Quoted postTibo@thsottiaux

    Day 25/ We are doubling all usage limits for all Pro 100/200/500 tiers and Business Premium, effective today. We heard your kind feedback and won’t be reducing usage limits for Pro 200, so your Work and Codex usage will stay the same. We’re also going to continue offering extended limits for dots for now, and usage of your dot will still continue to be separate from your default usage. And we'll of course also keep shipping better models and other efficiency improvements that increase your effective usage over time.

    Why it matters

    The breakdown distinguishes increased allowances from a canceled reduction, helping existing and newer Pro 200 subscribers understand why their usage limits converge despite different subscription histories.

  5. Aravind Srinivas67

    Aravind Srinivas announces that /teardown by @jakubkrehel is now available as a skill in Perplexity Computer for interactively exploring objects in 3D, with 5000 trial credits per user. https://t.co/RM1HUQq4Jz https://t.co/w0fOEYaDq1 @AskPerplexity says the skill creates labeled exploded views or cutaways, exports to SVG, PNG or PDF, and offers free /teardown tasks through November 6, up to 5,000 credits per user. https://t.co/z6DYCF6Z6V

    Quoted postComputer@AskPerplexity

    The Teardown skill by @jakubkrehel, now in Computer's skills marketplace, draws an exploded view or cutaway of an object, parts labeled. Drawings are interactive and export to SVG, PNG or PDF. Tasks that use /teardown are free through November 6, up to 5,000 credits per user. https://t.co/z6DYCF6Z6V

    Why it matters

    Interactive labeled views and exports to SVG, PNG or PDF give users ways to inspect an object's parts and reuse the resulting drawings outside Computer.

  6. Google Gemini69

    You can now generate, preview, and edit documents, PDFs, presentations, spreadsheets, and more directly in Gemini. Turn handwritten notes into a PDF study guide, manually tweak content, highlight sections for Gemini to edit text or visuals, and ask follow-up questions.

    Why it matters

    Generating files and making targeted edits within Gemini could reduce the need to switch tools when turning handwritten notes into study materials.

10/29Thu
  1. vLLM78

    vLLM announces day-0 support for MistralAI's Mistral Large 4, a trillion-parameter multimodal MoE with 1M context for advanced coding, reasoning, and cybersecurity-related tasks. FP8 and NVFP4 checkpoints, with a built-in DSpark drafter. https://twitter.com/1667249535519805451/status/2115811242556137820

    Quoted postMistral AI@MistralAI

    Today, we release the weights of a new and improved Le Chonk, advancing the open frontier for agentic coding and cybersecurity. 💻 Built to build: Le Chonk ranks #1 on @cognition’s FrontierCode among open models, and sets a new benchmark for Pareto efficiency on @artificialanalysis. 🛡 Built to defend: State-of-the-art in cyberdefense, put through the paces by the world's leading cyber vendors, including @CrowdStrike, @cloudflare, @rubrik, @zscaler, and others. Built for sovereignty: Make it yours. Download the weights on @huggingface , customize it with Mistral Forge, and deploy it wherever you need it. Read more from our team and customers 👇:

    Why it matters

    The checkpoint formats and built-in DSpark drafter provide concrete deployment context for developers considering serving Mistral Large 4 with vLLM.

  2. NVIDIA AI81

    NVIDIA congratulates @MistralAI on the next generation of Le Chonk, a 1T-parameter MoE multimodal model trained from scratch on 3,800 NVIDIA Grace Blackwell GPUs. In the quoted announcement, Mistral releases its weights for agentic coding and cybersecurity. NVIDIA’s day 0 support includes NVFP4 weights on @huggingface → https://huggingface.co/mistralai/Mistral-Large-4-1T-A52B-NVFP4 Performance-optimized Dynamo for distributed inference → https://docs.nvidia.com/dynamo/recipes/mistral-large-4

    Quoted postMistral AI@MistralAI

    Today, we release the weights of a new and improved Le Chonk, advancing the open frontier for agentic coding and cybersecurity. 💻 Built to build: Le Chonk ranks #1 on @cognition’s FrontierCode among open models, and sets a new benchmark for Pareto efficiency on @artificialanalysis. 🛡 Built to defend: State-of-the-art in cyberdefense, put through the paces by the world's leading cyber vendors, including @CrowdStrike, @cloudflare, @rubrik, @zscaler, and others. Built for sovereignty: Make it yours. Download the weights on @huggingface , customize it with Mistral Forge, and deploy it wherever you need it. Read more from our team and customers 👇:

    Why it matters

    The post connects the released model weights with NVFP4 availability and a Dynamo inference recipe, providing concrete deployment context for teams considering running the model themselves.

  3. Hugging Face Blog71

    Introducing AnySpeechRecognizer and AnyDecisionModel for Speech and Decisions on Apple Platforms

    The authors announce two Swift packages for Apple platforms, AnySpeechRecognizer and AnyDecisionModel. AnySpeechRecognizer mirrors Apple's speech APIs while adding local Parakeet and Qwen3-ASR engines and speaker diarization for up to four speakers; AnyDecisionModel returns typed answers and probabilities for yes-or-no, multiple-choice, and rating-scale questions through local or hosted backends. Both support downloading open models from the Hugging Face Hub, and the reported speech evaluations cover macOS only, with no iPhone testing yet.

    Why it matters

    The explanation of probability calibration and option order bias offers a practical method for evaluating model-based decisions before using confidence values as application thresholds.

  4. The Decoder81

    Google opens Android development to third-party AI agents and unveils new Gemini APIs

    Google introduced Android Studio Rabbit 2 with support for more than 40 coding agents through the open Agent Client Protocol, including Claude, Codex, and Google Antigravity. Android CLI updates add Compose previews and memory leak analysis for agents. Google also announced an alpha Agentic API powered by Gemini Nano 4, a beta AppFunctions API for shared tool calling, and a Connected Apps Platform preview linking apps to Google Search and Gemini.

    Why it matters

    Direct IDE access for third-party coding agents and shared app functions illustrate how Google is extending agent integration across Android development workflows and on-device app interactions.

10/28Wed
  1. NVIDIA Blog74

    NVIDIA RTX Spark Laptops Gain Nemotron 3.5 Transcribe, Agent Controls and Gaming Updates

    NVIDIA introduced Nemotron 3.5 Transcribe alongside model support, agent resource controls and gaming updates for RTX Spark laptops. The open weight speech model handles transcription, speaker attribution, translation and audio questions, supports 40 languages and is available today on Hugging Face, with quantized versions coming soon. NVIDIA App now lets users allocate GPU resources between foreground applications and background agents, while Liquid AI’s LFM3 models support local execution through llama.cpp and vLLM.

    Why it matters

    Combining speech processing updates with GPU resource controls provides context for how local models and background agents share laptop hardware with everyday applications.

  2. vLLM71

    vLLM announces day-0 serving for NVIDIA Nemotron 3.5 Transcribe through vLLM + NeMo Speech. 40 languages. Recordings up to an hour. Promptable transcripts, speaker labels and audio Q&A. Open weights in BF16, FP8 and NVFP4. https://t.co/WhcqKqd1jf

    Quoted postNVIDIA AI@NVIDIAAI

    Meet NVIDIA Nemotron 3.5 Transcribe 🎙️ An open-weight, promptable 30B MoE model with ~4B active parameters that brings transcription in 40 languages, speaker attribution, translation, contextual prompting and audio understanding into one checkpoint. Watch it keep track of who https://t.co/PEH1PeURIv

    Why it matters

    Day-0 serving through vLLM and NeMo Speech gives deployment context for the release, alongside open weights available in BF16, FP8 and NVFP4 formats.

  3. AWS Machine Learning Blog76

    AWS announces SOCI-indexed images for faster SageMaker AI jobs

    AWS announced SOCI indexing for Amazon SageMaker AI training and processing jobs across all AWS Regions, enabling container images to load lazily. In AWS benchmarks, container readiness took 3–11 seconds, and training jobs finished 1–6 minutes sooner despite a first-epoch penalty of 3–16 seconds. Users can select pre-indexed Deep Learning Containers or index custom images; lazy loading requires Amazon ECR private repositories.

    Why it matters

    The benchmarks distinguish image download savings from first-epoch overhead, providing a concrete basis for assessing workloads whose startup code accesses different portions of a container image.