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Every company has specialized intelligence that sets it apart. With @langchain, we’re helping enterprises turn that knowledge into specialized agents they can customize, secure and improve over time.

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NVIDIA

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101,362 görüntüleme • 9 gün önce •via X (Twitter)

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Specialized AI agents help enterprises turn AI into systems built for their own workflows. NVIDIA Agent Toolkit brings together open Nemotron models, tools, skills and secure runtime support to help teams build agents tuned for domain-specific work. Learn more:
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Specialized AI agents help enterprises turn AI into systems built for their own workflows. NVIDIA Agent Toolkit brings together open Nemotron models, tools, skills and secure runtime support to help teams build agents tuned for domain-specific work. Learn more:

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“Dare I say it modestly, we’re really the only company that has the knowledge to turn AI into economic value” Palantir CTO, Shyam Sankar
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“Dare I say it modestly, we’re really the only company that has the knowledge to turn AI into economic value” Palantir CTO, Shyam Sankar

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Every company must own its intelligence. We've raised $1.5B Series D at a $17.5B valuation. We’ve surpassed $1B ARR and serve over 40 trillion tokens daily, with 95%+ coming from models specialized on customer data. We’re just getting started. More:
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Every company must own its intelligence. We've raised $1.5B Series D at a $17.5B valuation. We’ve surpassed $1B ARR and serve over 40 trillion tokens daily, with 95%+ coming from models specialized on customer data. We’re just getting started. More:

Fireworks AI

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The next wave of AI will not be one model doing everything. It will be specialized agents built around real domains, real knowledge, and real usage. That is what OptimAI is building with Search, Claw, Persona Agents, and Marketplace. Create an agent. Give it expertise. Publish it. Let it be used. That is how intelligence becomes infrastructure. 💡Build yours at:
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The next wave of AI will not be one model doing everything. It will be specialized agents built around real domains, real knowledge, and real usage. That is what OptimAI is building with Search, Claw, Persona Agents, and Marketplace. Create an agent. Give it expertise. Publish it. Let it be used. That is how intelligence becomes infrastructure. 💡Build yours at:

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Introducing Databricks Document Intelligence: a research-specialized layer that turns raw enterprise documents into structured data your agents can actually reason over. Across our benchmarks, Document Intelligence delivered the highest end-to-end parsing and extraction quality at 6-8x lower cost, with a 16% average performance gain across every agent framework tested, just from better parsing. How to get started:
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Introducing Databricks Document Intelligence: a research-specialized layer that turns raw enterprise documents into structured data your agents can actually reason over. Across our benchmarks, Document Intelligence delivered the highest end-to-end parsing and extraction quality at 6-8x lower cost, with a 16% average performance gain across every agent framework tested, just from better parsing. How to get started:

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Microsoft Discovery uses specialized AI agents that reason over scientific knowledge, generate hypotheses, and simulate results all in a continuous loop. One early result? A novel coolant, discovered in 200 hours.
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Microsoft Discovery uses specialized AI agents that reason over scientific knowledge, generate hypotheses, and simulate results all in a continuous loop. One early result? A novel coolant, discovered in 200 hours.

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Learn how to build a Gemini 3 Deep Agents with this video from LangChain. These agents can reason through complex, long horizon tasks by: > Breaking goals into actionable steps > Delegating specific work for specialized models > Leveraging file systems and code execution
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Learn how to build a Gemini 3 Deep Agents with this video from LangChain. These agents can reason through complex, long horizon tasks by: > Breaking goals into actionable steps > Delegating specific work for specialized models > Leveraging file systems and code execution

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OptimAI Search is now on Agentic(.)Market - and we’re bringing the stack to Base. Builders can plug into live, citation-backed context across web, social, and crypto data through MCP, API, and SDK - then pay seamlessly with x402. No brittle workflows. No manual stitching. Just agent-native access to real-time intelligence at scale. And with custom domain agents on the marketplace, specialized knowledge becomes reusable. Search is becoming infrastructure. Build with it: 💡 💡
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OptimAI Search is now on Agentic(.)Market - and we’re bringing the stack to Base. Builders can plug into live, citation-backed context across web, social, and crypto data through MCP, API, and SDK - then pay seamlessly with x402. No brittle workflows. No manual stitching. Just agent-native access to real-time intelligence at scale. And with custom domain agents on the marketplace, specialized knowledge becomes reusable. Search is becoming infrastructure. Build with it: 💡 💡

OptimAI Network

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🌟Our latest LangChain Academy course – Deep Agents with LangGraph – is now live!🌟 Many agents today follow the same simple pattern: run in a loop, call tools. That architecture works well enough, but it breaks down as tasks get more complex. Today, companies of all sizes – from startups to large enterprises – are building their own Deep Agents. These agents dive deeper. They’re able to plan complex tasks and carry them out over longer time horizons. There are four key features that set Deep Agents apart from regular agents: 1. Planning – keeps agents on track 2. File system – allows agents to offload context 3. Sub-agents – act as focused specialists 4. Prompting – provides agents with detailed instructions Our latest LangChain Academy course, Deep Agents with LangGraph, shows you how to combine these pieces with LangGraph to orchestrate long-running, multi-agent workflows. Big thanks to community member Dmitry Labazkin for helping us shape this course with his contributions! Enroll for free ➡️
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🌟Our latest LangChain Academy course – Deep Agents with LangGraph – is now live!🌟 Many agents today follow the same simple pattern: run in a loop, call tools. That architecture works well enough, but it breaks down as tasks get more complex. Today, companies of all sizes – from startups to large enterprises – are building their own Deep Agents. These agents dive deeper. They’re able to plan complex tasks and carry them out over longer time horizons. There are four key features that set Deep Agents apart from regular agents: 1. Planning – keeps agents on track 2. File system – allows agents to offload context 3. Sub-agents – act as focused specialists 4. Prompting – provides agents with detailed instructions Our latest LangChain Academy course, Deep Agents with LangGraph, shows you how to combine these pieces with LangGraph to orchestrate long-running, multi-agent workflows. Big thanks to community member Dmitry Labazkin for helping us shape this course with his contributions! Enroll for free ➡️

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claude code can now write sql almost perfectly. but it still needs to be retaught the same definitions over and over. ontology is how AI agents get 7x faster on your database over time. today we shipped Ontology 3.0 — memory for AI agents, specialized for databases:
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claude code can now write sql almost perfectly. but it still needs to be retaught the same definitions over and over. ontology is how AI agents get 7x faster on your database over time. today we shipped Ontology 3.0 — memory for AI agents, specialized for databases:

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Introducing Honen Turn your company context into interactive courses that self-improve over time We partnered with NVIDIA to bring AI literacy to 250,000 learners We're ensuring no person or company gets left behind Get started at
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Introducing Honen Turn your company context into interactive courses that self-improve over time We partnered with NVIDIA to bring AI literacy to 250,000 learners We're ensuring no person or company gets left behind Get started at

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A Stanford researcher has developed self-dressing clothing that can move on its own, an invention that could one day help people with mobility challenges and workers in specialized jobs.
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A Stanford researcher has developed self-dressing clothing that can move on its own, an invention that could one day help people with mobility challenges and workers in specialized jobs.

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Today, we're excited to announce Personas: Your company's voice, across every channel. With full memory across every interaction, one Persona can handle web chat, SMS, voice, and phone calls in ways that are not only realistic, but truly omnichannel. With Personas: -Support teams can deploy a single agent that remembers everything that happens in a conversation across all channels. -Enterprises can create agents that sound and act exactly like their best reps, scaling your best customer interactions company wide. -Developers can build conversational pathways once and connect them across every modality, with full access to your company's knowledge and tools in a secure and safe way. Businesses, developers, or anyone curious can try Personas themselves on our site for free immediately at For enterprises, you can grab a custom demo directly at
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Today, we're excited to announce Personas: Your company's voice, across every channel. With full memory across every interaction, one Persona can handle web chat, SMS, voice, and phone calls in ways that are not only realistic, but truly omnichannel. With Personas: -Support teams can deploy a single agent that remembers everything that happens in a conversation across all channels. -Enterprises can create agents that sound and act exactly like their best reps, scaling your best customer interactions company wide. -Developers can build conversational pathways once and connect them across every modality, with full access to your company's knowledge and tools in a secure and safe way. Businesses, developers, or anyone curious can try Personas themselves on our site for free immediately at For enterprises, you can grab a custom demo directly at

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LangChain Academy is live! Our first course — Introduction to LangGraph — teaches you the in-and-outs of building a reliable AI agent. In this course, you’ll learn how to: 🛠️ Build agents with LangGraph's graph-based workflows 🔄 Use memory + human-in-the-loop for smarter, self-corrective agents 📚 Create your own AI assistant that can perform knowledge tasks Enroll now for free ➡️ Bring LangChain Academy to your company ➡️
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LangChain Academy is live! Our first course — Introduction to LangGraph — teaches you the in-and-outs of building a reliable AI agent. In this course, you’ll learn how to: 🛠️ Build agents with LangGraph's graph-based workflows 🔄 Use memory + human-in-the-loop for smarter, self-corrective agents 📚 Create your own AI assistant that can perform knowledge tasks Enroll now for free ➡️ Bring LangChain Academy to your company ➡️

LangChain

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Our CEO Jensen Huang on the opportunity ahead: use AI deeply, challenge the status quo, and stay focused on the human purpose behind the work. Every job has tasks. People give those tasks purpose, and AI can help turn that purpose into greater impact.
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Our CEO Jensen Huang on the opportunity ahead: use AI deeply, challenge the status quo, and stay focused on the human purpose behind the work. Every job has tasks. People give those tasks purpose, and AI can help turn that purpose into greater impact.

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jay plemons

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🔥 New LangChain Academy Course: LangChain Essentials (Python & TypeScript) 🔥 Learn the basics of LangChain – our open source framework that makes it easy to start building agents with any model provider. Last week, we released LangChain 1.0. We’ve completely rewritten LangChain to be opinionated, focused, and powered by LangGraph’s runtime. It includes a new `create_agent` abstraction to build agents quickly, middleware for flexibility, and standard content blocks that work across any model provider. In this quickstart course, you'll learn how to: - Build an agent with the `create_agent` abstraction - Use LangChain’s core building blocks: Models, Messages, Memory, and Tools - Customize your agent with middleware - Debug and test your agent with LangSmith Observability & Evaluation Enroll for free ➡️
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🔥 New LangChain Academy Course: LangChain Essentials (Python & TypeScript) 🔥 Learn the basics of LangChain – our open source framework that makes it easy to start building agents with any model provider. Last week, we released LangChain 1.0. We’ve completely rewritten LangChain to be opinionated, focused, and powered by LangGraph’s runtime. It includes a new `create_agent` abstraction to build agents quickly, middleware for flexibility, and standard content blocks that work across any model provider. In this quickstart course, you'll learn how to: - Build an agent with the `create_agent` abstraction - Use LangChain’s core building blocks: Models, Messages, Memory, and Tools - Customize your agent with middleware - Debug and test your agent with LangSmith Observability & Evaluation Enroll for free ➡️

LangChain

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🔗 New LangChain Academy Course: Introduction to LangChain (Python) 🔗 Learn how to build with LangChain – our open source framework that makes it easy to start building agents with any model provider. In this course, you’ll create agents that can reason, use tools, and take action, and learn how to debug their behavior with LangSmith. Along the way, you’ll: - Build an agent with the `create_agent` abstraction - Use LangChain’s core building blocks: Models, Messages, Memory, and Tools - Customize your agent with middleware - Debug your agent with LangSmith Observability & Studio By the end of the course, you’ll have assembled a full team of personal assistants. Enroll for free ➡️

LangChain

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.Snorkel AI helps organizations leverage their own data and expertise to build high-quality, specialized AI systems orders of magnitude faster than fully manual approaches. The company drives value in partnership with AWS and NVIDIA to help their customers. Available in AWS Marketplace, Snorkel’s AI Data Development platform enables enterprises to turn their proprietary data and domain knowledge into expert evaluation and training data, with options for in house data development or white glove dataset delivery.
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.Snorkel AI helps organizations leverage their own data and expertise to build high-quality, specialized AI systems orders of magnitude faster than fully manual approaches. The company drives value in partnership with AWS and NVIDIA to help their customers. Available in AWS Marketplace, Snorkel’s AI Data Development platform enables enterprises to turn their proprietary data and domain knowledge into expert evaluation and training data, with options for in house data development or white glove dataset delivery.

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A builder wants to ship an agent that can search live data, use it instantly, and keep going without manual steps. That is why OptimAI Search now ships with x402, SDK, and MCP support. x402 makes access and payment seamless. SDK and MCP make integration straightforward for builders. And under the hood, OptimAI Search gives agents real-time access to huge volumes of public and social web data, structured into context they can actually use. Add Agent Marketplace on top, and domain knowledge becomes reusable: build specialized agents, publish them, and let others build on what you create. This is what search looks like in the agent-native internet. 💡Try it:
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A builder wants to ship an agent that can search live data, use it instantly, and keep going without manual steps. That is why OptimAI Search now ships with x402, SDK, and MCP support. x402 makes access and payment seamless. SDK and MCP make integration straightforward for builders. And under the hood, OptimAI Search gives agents real-time access to huge volumes of public and social web data, structured into context they can actually use. Add Agent Marketplace on top, and domain knowledge becomes reusable: build specialized agents, publish them, and let others build on what you create. This is what search looks like in the agent-native internet. 💡Try it:

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