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the product, not an integration you maintain. Comfy API is available on paid Comfy plans, starting with Standard. Usage is billed separately. GPU time is billed by the second. Storage is prorated hourly. See full Comfy API pricing. What this means, and what’s next ComfyUI gave people control over every step of how an image or video gets made. Every node is visible. Every parameter is adjustable. But getting that workflow in front of a team or a customer still meant rebuilding it somewhere else

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models. Always-on agents are proving to be a winning consumer form factor for AI, and plugging them directly into the top models is a differentiator only OAI and Anthropic can leverage. The Rundown: Blotato offers unified social media APIs for your AI agents. Easily schedule posts, create Manychat-style DM automations, and automate your social media marketing with Claude, ChatGPT, Grok Bot, Muse, or any AI agent. With Blotato’s unified social API, your AI agents can: Create content with the late

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I might choose myself for a product that wants access to your bank account and credit card. While your Dot can be represented as simply as a colored ring named "Dot," you're encouraged to consider some of the jollier alternatives — a hexagon wearing a beret, a heart in sunglasses, and so on. For my Dot, I picked a pillowy blue cloud shape, threw some googly eyes and a bowtie on it, and named it Kicker, after journalist slang for the final sentence of a story. From there, I decided to attempt to

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t triage, model routing, and content or safety moderation. Near-instant decisions Decision models on Ollama are fast, as requests don’t have to travel over a network. Nimble 9B averaged 91ms per decision in the Pac-Man example below when running locally on an M5 Max. That’s fast enough to make rapid decisions such as playing a game or processing content in real time: Available models Three new decision models are available to run via Ollama: nimble: open-source 9B parameter decision model develo

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models, and will stay updated over time as new releases launch We already benchmark inference performance on mobile phones and datacenter-scale hardware, and are expanding our coverage to include laptops and workstations. Alongside hosting a leaderboard displaying results from popular model and hardware combinations, we are open-sourcing all code and data required to run AA-AgentPerf-Local to ensure that individuals and companies are able to run their own trials, informing their local AI serving

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difference between tagged and untagged audio as an example. In this first sample, we’re just using a default sentence. For reference, we’re using Siren for these examples. Story paragraph without Audio Tags on Eleven v4 Now, this second example has the same sentence with Audio Tags added. We’ve got emotional cues, sound effects, and even noises beyond the text, like an evil laugh. Story paragraph with Audio Tags on Eleven v4 Five emotional text to speech performances with Eleven v4 The best way

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Technical Blog sessionStorage.removeItem('facets.search.text'); sessionStorage.removeItem('facets.search.text-copy'); sessionStorage.removeItem('facets.search.filters'); Related Resources Trustworthy AI / Cybersecurity English 한국어 Secure AI agents with a safety enforcement layer spanning software and hardware AI-Generated Summary Powered by NVIDIA Nemotron. AI-generated content may summarize information incompletely. Verify important information. Learn more To understand where agentic AI stands

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Technical Blog sessionStorage.removeItem('facets.search.text'); sessionStorage.removeItem('facets.search.text-copy'); sessionStorage.removeItem('facets.search.filters'); Sep 28, 2026 NVIDIA OpenShell 0.1.0 provides an open-source runtime that enforces which systems and data an AI agent can access without rewriting the agent. The runtime combines sandboxed execution, controlled service access, credential management, and formal policy analysis to restrict API operations and protect credentials out

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66%. We gave the hillclimber access to documentation and our SDKs, allowing Claude to identify errors and self-correct them (Figure 9). Claude found that the skill was missing coverage of eight features. Adding sections for them in the skill improved performance to 74%. It then found errors in C and Java type tables, boosting performance to 77%. After the score stalled for two rounds, Claude analyzed the remaining failures and bucketed them by root-cause. A normal round makes one edit for the mo

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As the debate rages over whether the recent spate of rogue AI agents is a step toward AGI or a more conventional engineering problem, Nvidia is offering its own answer to the problem. Nvidia CEO Jensen Huang on Monday introduced a toolkit of software and hardware products that add independent security layers around AI agents to ensure they stay within their test environments even if they attempt to break out. The release follows a string of hacking incidents involving AI models from Anthropic, G

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rotocol (MCP) server, which allows agents to work server-to-server. The proposed standard WebMCP , meanwhile, is designed for agents that work inside the buyer’s browser. Both leverage Shopify’s Universal Commerce Protocol (UCP), which provides a common way to search for and discover products, build carts, and check out. Top AI agents like Muse and Instinct already have direct partnerships with Shopify for agentic commerce. The Instinct partnership was announced today. “If your agent is operatin

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be featured. 🤖 Muse - Meta’s personal agent, now available as a real-time avatar 🧑‍💻 Rollouts - Cursor’s bot to monitor code, catch regressions, trigger rollbacks 📺️ Tesseract - Mirage’s video, motion, and sound editor for AI agents 🗣️ Gemini 3.8 Flash TTS - Google’s text-to-speech AI supporting 100 languages Dario Amodei and Sam Altman called for AI safety at the UN, with Amodei saying it could be “a risk to humanity” and Altman warning about losing “control of the future to AI.” FLUX-maker Bla

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ders AI operators, pipelines rows so their KV stays in GPU HBM, and batches work to keep the GPU busy. For AI joins, we even use some fun tree attention tricks (c.f. SpecInfer, Hydragen) to reuse forward pass work… pic.twitter.com/MxqFwwHQ7t— Shreya Shankar (@sh reya) September 24, 2026 29クエリの評価で1.84倍高速化⁠、vLLMが上回るケースも 開発側はQuailの性能を、映画レビュー、医療レポート、法的文書、AIエージェントの実行履歴などを扱う29クエリのベンチマーク「QUAIL-B」で評価した。モデルにはQwen3 4B FP8、GPUにはH100を1基使用し、QuailとvLLMを同じ物理GPU上で順番に実行した。モデルとプロンプトを統一し、フィルターや結合の組み合わせと順序を示す論理クエリ計

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problems . Even projects that have been enrolled in OSS-Fuzz for years can still hide critical bugs, and the reason is almost always the same: someone needs to keep an eye on coverage, write new harnesses for the code that nobody is reaching, and triage the crashes that come out the other end. In other words, fuzzing still needs a human in the loop. So the natural question I kept asking myself was: how much of that human work can we actually hand over to an LLM agent? That is what led me to bui

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nsitive actions are all overseen by the Sentinel, which runs outside of that cell. Similarly, all sensitive secrets - like the passwords you enter into Muse’s secure credential storage - are also stored outside the runtime cell. This was a very deliberate choice - your Muse Secure VM truly is your own computer in the cloud. You can install software in it, write and compile code, use the browser to surf the web: it is your own Linux box that you can operate as you choose with your Muse. Poking ar

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Key Takeaways Use the LangSmith Fine-Tuning CLI and skill - smithtune - to leverage agent trajectories stored in LangSmith to a fine-tuned model in one end-to-end workflow; In addition to driving training, the smithtune CLI handles evaluating the fine-tuned model and uploads eval results to LangSmith for easy analysis; We partnered with Fireworks & Baseten to create a seamless link between LangSmith trajectories and creation of a dataset for fine-tuning both the platforms Today we're launching L

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mputing infrastructure, built on TEEs with verifiable transparency. On top of the confidentiality and attestation the hardware provides, it adds non-targetability and encrypted storage. The more you use an AI assistant, the more useful it gets as it learns your style, preferences and context. Wearable AI assistants will help you in similar ways, including with everyday life. To do that they need to know you and your context. That can include connecting ideas across days or weeks, and working pro

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Technical Blog sessionStorage.removeItem('facets.search.text'); sessionStorage.removeItem('facets.search.text-copy'); sessionStorage.removeItem('facets.search.filters'); Related Resources Data Center / Cloud Using NVIDIA Cluster Readiness Engine, teams can bring reliable GPU clusters to production with workload-driven validation. AI-Generated Summary NVIDIA Cluster Readiness Engine (NVCRE) is an open source Kubernetes controller that runs real distributed workloads across topology-aware node gro

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oughly 66% of our system prompt. Over time, we continue to add and remove instructions as new models require new guidance, which then flows into the training of future models. Leveraging A/B tests on a large user base is crucial to effectively optimizing the harness for real traffic. While evals can be a fast and useful proxy, they often represent "hard" problems and don't properly reflect the true distribution of user requests. Loading tools only when needed The system prompt is only one part o

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o lose its edge over a single mega-cluster. How ARCv3 deltas move from trainer to rollouts. Each trainer shard uploads its slice of the compressed weight delta to shared object storage (S3) in parallel. Then, the Fireworks API signals every region that a new update is available, and each rollout region pulls the pieces it needs and reconstructs the updated model locally. The trainer never talks directly to the rollout fleet, which is what lets a globally distributed inference cluster stay in syn

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