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Google just released its own MCP (Model Control Plane) server for Stitch, turning LLM coding agents into UI-savvy collaborators. The new Stitch MCP Server pipes designs directly into your IDE. 🔹 Generate new screens 🔹 Fetch code from any design 🔹 Give your agent full visual context

Wes Roth

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138,465 views • 5 months ago •via X (Twitter)

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That gap between design and production? Closed. 🔁 GitHub Copilot, Visual Studio Code, and Figma now create a continuous loop. With the bidirectional Figma MCP server, Copilot users can: 🔹 Pull design context into code 🔹 Push working UI back to the canvas Connect your canvas and stay in the flow. 👇

That gap between design and production? Closed. 🔁 GitHub Copilot, Visual Studio Code, and Figma now create a continuous loop. With the bidirectional Figma MCP server, Copilot users can: 🔹 Pull design context into code 🔹 Push working UI back to the canvas Connect your canvas and stay in the flow. 👇

GitHub

113,080 views • 4 months ago

Design → code → canvas → feedback → repeat. The Figma MCP server is now bidirectional. GitHub Copilot users can pull design context into code and push working UI back to the Figma canvas, all from Visual Studio Code . No handoffs or context switching. Just flow.

Design → code → canvas → feedback → repeat. The Figma MCP server is now bidirectional. GitHub Copilot users can pull design context into code and push working UI back to the Figma canvas, all from Visual Studio Code . No handoffs or context switching. Just flow.

Mario Rodriguez

105,792 views • 4 months ago

At I/O, we announced a big new export partner: Bolt by StackBlitz! ⚡️ bolt.new is an AI-powered builder that generates full-stack web apps directly in your browser. Now, you can take your Stitch screens from a visual concept to a fully coded application with a single click. Here is how it works: 🔹 Select your screens in Stitch 🔹 Click export 🔹 Your screens are automatically transferred to Bolt, ready to be built into a working product 🛠️ (Note: Bolt will accept up to 5 screens at a time for Bolt Free users, and up to 20 screens for Paid users)

At I/O, we announced a big new export partner: Bolt by StackBlitz! ⚡️ bolt.new is an AI-powered builder that generates full-stack web apps directly in your browser. Now, you can take your Stitch screens from a visual concept to a fully coded application with a single click. Here is how it works: 🔹 Select your screens in Stitch 🔹 Click export 🔹 Your screens are automatically transferred to Bolt, ready to be built into a working product 🛠️ (Note: Bolt will accept up to 5 screens at a time for Bolt Free users, and up to 20 screens for Paid users)

Stitch by Google

284,010 views • 1 month ago

🗞️ Ava's Frid-AI Roundup! Welcome to Solidus Ai Tech Friday Roundup! 🔹 OpenAI Unveils the ChatGPT Agent 🔹 Google Activates “AI Mode” with Deep Search and Voice Calling 🔹 Meta Plots Supercomputers the Size of Manhattan 🔹 Netflix Leans into Generative AI for Its Hit Shows 🔹 Amazon Debuts Kiro, an AI‑Powered Coding IDE 🔹 Runway’s Act‑Two Model Brings Motion‑Capture Magic to Any Video 🔹 China Unveils a Humanoid Robot That Swaps Its Own Batteries

🗞️ Ava's Frid-AI Roundup! Welcome to Solidus Ai Tech Friday Roundup! 🔹 OpenAI Unveils the ChatGPT Agent 🔹 Google Activates “AI Mode” with Deep Search and Voice Calling 🔹 Meta Plots Supercomputers the Size of Manhattan 🔹 Netflix Leans into Generative AI for Its Hit Shows 🔹 Amazon Debuts Kiro, an AI‑Powered Coding IDE 🔹 Runway’s Act‑Two Model Brings Motion‑Capture Magic to Any Video 🔹 China Unveils a Humanoid Robot That Swaps Its Own Batteries

AITECH CLOUD NETWORK

57,171 views • 11 months ago

New short course: Build AI Apps with MCP Servers: Working with Box Files, built with Box and taught by Ben Kus , their CTO. Many AI applications require custom code for basic file operations. The Model Context Protocol (MCP) standardizes this by letting you offload file tasks to dedicated servers that provide tools an LLM can use directly. In this course, you'll process documents stored in a Box folder using the Box MCP server. Rather than writing custom integration code to connect to the Box API and download files, you'll design your application to use the tools provided via MCP. Skills you'll gain: - Build an LLM-powered document processing app, using the Box MCP server to access files - Design a multi-agent system using Google's Agent Development Kit (ADK), consisting of specialized agents for file operations - Coordinate the multi-agent workflow through an orchestrator that uses the Agent2Agent (A2A) protocol to connect to the agents You'll start with a local file-processing app, refactor it to work with Box's MCP server, then evolve it into a multi-agent system. Sign up here:

New short course: Build AI Apps with MCP Servers: Working with Box Files, built with Box and taught by Ben Kus , their CTO. Many AI applications require custom code for basic file operations. The Model Context Protocol (MCP) standardizes this by letting you offload file tasks to dedicated servers that provide tools an LLM can use directly. In this course, you'll process documents stored in a Box folder using the Box MCP server. Rather than writing custom integration code to connect to the Box API and download files, you'll design your application to use the tools provided via MCP. Skills you'll gain: - Build an LLM-powered document processing app, using the Box MCP server to access files - Design a multi-agent system using Google's Agent Development Kit (ADK), consisting of specialized agents for file operations - Coordinate the multi-agent workflow through an orchestrator that uses the Agent2Agent (A2A) protocol to connect to the agents You'll start with a local file-processing app, refactor it to work with Box's MCP server, then evolve it into a multi-agent system. Sign up here:

Andrew Ng

81,563 views • 10 months ago

Box is a launch partner for Microsoft’s Apps in Copilot launch. The Box AI Agent for Microsoft365 Copilot will be able to surface rich visual previews like slides, graphs, and images right in the conversation and have access to all of the Box MCP server tools. Coming soon to the Box AI Agent in Microsoft 365 Copilot: 🔹 MCP-powered workflows — metadata extraction, document generation, and more 🔹 Visual-first search — view complicated graphs or rich visuals that are buried in your Box content, without having to open files. 🔹 Fewer clarifications, faster decisions - move from chat to action Enable agents to bring apps into the flow of work, while keeping IT in control:

Box is a launch partner for Microsoft’s Apps in Copilot launch. The Box AI Agent for Microsoft365 Copilot will be able to surface rich visual previews like slides, graphs, and images right in the conversation and have access to all of the Box MCP server tools. Coming soon to the Box AI Agent in Microsoft 365 Copilot: 🔹 MCP-powered workflows — metadata extraction, document generation, and more 🔹 Visual-first search — view complicated graphs or rich visuals that are buried in your Box content, without having to open files. 🔹 Fewer clarifications, faster decisions - move from chat to action Enable agents to bring apps into the flow of work, while keeping IT in control:

Box

335,591 views • 4 months ago

wtf is MCP? Paul Klein IV, CEO of explains "Model Context Protocol" (MCP) in plain terms: "There's this new way that people are exposing tools to AI & the 'Model Context Protocol' is one of those ways that you can standardize & give your AI a set of tools to call. BrowserBase has a way to expose the browser to your agent via MCP or MCP server. More & more developers are trying to find ways to integrate more functionalities to their AI agents & BrowserBase's browsers are one of those primitive functionalities, & the MCP is just one way to integrate it into your software." Paul Klein IV From 🅱️'s GitHub: Model Context Protocol (MCP) is an open protocol that enables seamless integration between LLM applications and external data sources and tools. Whether you’re building an AI-powered IDE, enhancing a chat interface, or creating custom AI workflows, MCP provides a standardized way to connect LLMs with the context they need. This server provides cloud browser automation capabilities using Browserbase and Stagehand. This server enables LLMs to interact with web pages, take screenshots, and execute JavaScript in a cloud browser environment.

wtf is MCP? Paul Klein IV, CEO of explains "Model Context Protocol" (MCP) in plain terms: "There's this new way that people are exposing tools to AI & the 'Model Context Protocol' is one of those ways that you can standardize & give your AI a set of tools to call. BrowserBase has a way to expose the browser to your agent via MCP or MCP server. More & more developers are trying to find ways to integrate more functionalities to their AI agents & BrowserBase's browsers are one of those primitive functionalities, & the MCP is just one way to integrate it into your software." Paul Klein IV From 🅱️'s GitHub: Model Context Protocol (MCP) is an open protocol that enables seamless integration between LLM applications and external data sources and tools. Whether you’re building an AI-powered IDE, enhancing a chat interface, or creating custom AI workflows, MCP provides a standardized way to connect LLMs with the context they need. This server provides cloud browser automation capabilities using Browserbase and Stagehand. This server enables LLMs to interact with web pages, take screenshots, and execute JavaScript in a cloud browser environment.

Molly O’Shea

20,408 views • 1 year ago

New course: MCP: Build Rich-Context AI Apps with Anthropic. Learn to build AI apps that access tools, data, and prompts using the Model Context Protocol in this short course, created in partnership with Anthropic Anthropic and taught by Elie Schoppik Elie Schoppik, its Head of Technical Education. Connecting AI applications to external systems that bring rich context to LLM-based applications has often meant writing custom integrations for each use case. MCP is an open protocol that standardizes how LLMs access tools, data, and prompts from external sources, and simplifies how you provide context to your LLM-based applications. For example, you can provide context via third-party tools that let your LLM make API calls to search the web, access data from local docs, retrieve code from a GitHub repo, and so on. MCP, developed by Anthropic, is based on a client-server architecture that defines the communication details between an MCP client, hosted inside the AI application, and an MCP server that exposes tools, resources, and prompt templates. The server can be a subprocess launched by the client that runs locally or an independent process running remotely. In this hands-on course, you'll learn the core architecture behind MCP. You’ll create an MCP-compatible chatbot, build and deploy an MCP server, and connect the chatbot to your MCP server and other open-source servers. Here’s what you’ll do: - Understand why MCP makes AI development less fragmented and standardizes connections between AI applications and external data sources - Learn the core components of the client-server architecture of MCP and the underlying communication mechanism - Build a chatbot with custom tools for searching academic papers, and transform it into an MCP-compatible application - Build a local MCP server that exposes tools, resources, and prompt templates using FastMCP, and test it using MCP Inspector - Create an MCP client inside your chatbot to dynamically connect to your server - Connect your chatbot to reference servers built by Anthropic’s MCP team, such as filesystem, which implements filesystem operations, and fetch, which extracts contents from the web as markdown - Configure Claude Desktop to connect to your server and others, and explore how it abstracts away the low-level logic of MCP clients - Deploy your MCP server remotely and test it with the Inspector or other MCP-compatible applications - Learn about the roadmap for future MCP development, such as multi-agent architecture, MCP registry API, server discovery, authorization, and authentication MCP is an exciting and important technology that lets you build rich-context AI applications that connect to a growing ecosystem of MCP servers, with minimal integration work. Please sign up here!

New course: MCP: Build Rich-Context AI Apps with Anthropic. Learn to build AI apps that access tools, data, and prompts using the Model Context Protocol in this short course, created in partnership with Anthropic Anthropic and taught by Elie Schoppik Elie Schoppik, its Head of Technical Education. Connecting AI applications to external systems that bring rich context to LLM-based applications has often meant writing custom integrations for each use case. MCP is an open protocol that standardizes how LLMs access tools, data, and prompts from external sources, and simplifies how you provide context to your LLM-based applications. For example, you can provide context via third-party tools that let your LLM make API calls to search the web, access data from local docs, retrieve code from a GitHub repo, and so on. MCP, developed by Anthropic, is based on a client-server architecture that defines the communication details between an MCP client, hosted inside the AI application, and an MCP server that exposes tools, resources, and prompt templates. The server can be a subprocess launched by the client that runs locally or an independent process running remotely. In this hands-on course, you'll learn the core architecture behind MCP. You’ll create an MCP-compatible chatbot, build and deploy an MCP server, and connect the chatbot to your MCP server and other open-source servers. Here’s what you’ll do: - Understand why MCP makes AI development less fragmented and standardizes connections between AI applications and external data sources - Learn the core components of the client-server architecture of MCP and the underlying communication mechanism - Build a chatbot with custom tools for searching academic papers, and transform it into an MCP-compatible application - Build a local MCP server that exposes tools, resources, and prompt templates using FastMCP, and test it using MCP Inspector - Create an MCP client inside your chatbot to dynamically connect to your server - Connect your chatbot to reference servers built by Anthropic’s MCP team, such as filesystem, which implements filesystem operations, and fetch, which extracts contents from the web as markdown - Configure Claude Desktop to connect to your server and others, and explore how it abstracts away the low-level logic of MCP clients - Deploy your MCP server remotely and test it with the Inspector or other MCP-compatible applications - Learn about the roadmap for future MCP development, such as multi-agent architecture, MCP registry API, server discovery, authorization, and authentication MCP is an exciting and important technology that lets you build rich-context AI applications that connect to a growing ecosystem of MCP servers, with minimal integration work. Please sign up here!

Andrew Ng

142,010 views • 1 year ago

We have an ambitious vision for Stitch, we're just getting started. We've heard all your feedback on the product. Lots of improvements coming up soon on design quality, variety and iteration capabilities. Maybe even a new model 👀 Code is our underlying artifact, we will make sure you can use your Stitch designs into real products.

We have an ambitious vision for Stitch, we're just getting started. We've heard all your feedback on the product. Lots of improvements coming up soon on design quality, variety and iteration capabilities. Maybe even a new model 👀 Code is our underlying artifact, we will make sure you can use your Stitch designs into real products.

Stitch by Google

23,937 views • 1 year ago

You can now clone any website just by writing a prompt. Simply add the new Firecrawl MCP server to your favorite AI coding tool for improved web data extraction, and let Claude code it for you. Here’s how:

You can now clone any website just by writing a prompt. Simply add the new Firecrawl MCP server to your favorite AI coding tool for improved web data extraction, and let Claude code it for you. Here’s how:

Alvaro Cintas

539,649 views • 1 year ago

Here is a quick walkthrough of everything new in Stitch: 🌊 Streaming: Stitch now streams its work straight to the canvas. You can see Stitch working and start steering before the final product is done! 📄 Existing Designs: Stitch can help you start with your design by creating a DESIGN.md from your codebase, .fig files, or a live website ⏩ In-place AI Edits: Stitch can quickly edit specific parts of your screens just by asking or pointing and clicking 🎥 Motion & HTML canvas: Javascript, shaders and more now render natively on an HTML canvas so you can immediately see animation, hover states and effects 🚀 Portability and Integrations: We've added a big list of import and export additions to fit right into your workflow, including import your .fig files and one-click export to Netlify, Loveable and Bolt 🌟 Bonus: New skills to IMPORT your screens directly into Stitch via MCP and sync changes back to your codebase Walkthrough video👇 Details for each improvement in 🧵

Here is a quick walkthrough of everything new in Stitch: 🌊 Streaming: Stitch now streams its work straight to the canvas. You can see Stitch working and start steering before the final product is done! 📄 Existing Designs: Stitch can help you start with your design by creating a DESIGN.md from your codebase, .fig files, or a live website ⏩ In-place AI Edits: Stitch can quickly edit specific parts of your screens just by asking or pointing and clicking 🎥 Motion & HTML canvas: Javascript, shaders and more now render natively on an HTML canvas so you can immediately see animation, hover states and effects 🚀 Portability and Integrations: We've added a big list of import and export additions to fit right into your workflow, including import your .fig files and one-click export to Netlify, Loveable and Bolt 🌟 Bonus: New skills to IMPORT your screens directly into Stitch via MCP and sync changes back to your codebase Walkthrough video👇 Details for each improvement in 🧵

Stitch by Google

21,597 views • 1 month ago

🧠 Want to give your coding agent new capabilities? Use Agent Skills in Visual Studio Code! Agent skills let you package instructions and resources into reusable capabilities for your agent. Skills can be loaded on demand and called directly from chat using slash commands like /skill-name. Learn more:

🧠 Want to give your coding agent new capabilities? Use Agent Skills in Visual Studio Code! Agent skills let you package instructions and resources into reusable capabilities for your agent. Skills can be loaded on demand and called directly from chat using slash commands like /skill-name. Learn more:

Visual Studio Code

55,133 views • 3 months ago

Here is a quick walkthrough of everything new in Stitch: 🎨 The AI-native canvas can hold and reason across images, code, and text simultaneously. The new agent manager helps you design in parallel. (PS … light mode!) 🧠 A smarter design agent now understands your entire canvas context. You can swap images, generate product briefs, or mix mobile and desktop screens on the same canvas. 🎙️ You can vibe design with your voice (in Preview). Stitch can ‘see’ your canvas and your selected screens. You can ask for design critiques, variations, or navigate your canvas. ⚡️ Instant prototypes. Just hit the play button to see a prototype or preview your app in seconds. Stitch can imagine the next screen based on your mouse click. 📐 DESIGN.md and consistency. Every new design automatically starts with a cohesive design system which vastly improves consistency. The new DESIGN.md file can be used to export or import your design rules. Walkthrough video👇 Details for each major improvement 🧵

Here is a quick walkthrough of everything new in Stitch: 🎨 The AI-native canvas can hold and reason across images, code, and text simultaneously. The new agent manager helps you design in parallel. (PS … light mode!) 🧠 A smarter design agent now understands your entire canvas context. You can swap images, generate product briefs, or mix mobile and desktop screens on the same canvas. 🎙️ You can vibe design with your voice (in Preview). Stitch can ‘see’ your canvas and your selected screens. You can ask for design critiques, variations, or navigate your canvas. ⚡️ Instant prototypes. Just hit the play button to see a prototype or preview your app in seconds. Stitch can imagine the next screen based on your mouse click. 📐 DESIGN.md and consistency. Every new design automatically starts with a cohesive design system which vastly improves consistency. The new DESIGN.md file can be used to export or import your design rules. Walkthrough video👇 Details for each major improvement 🧵

Stitch by Google

487,548 views • 3 months ago

📣 Agent Forge is LIVE! What if creating your own team of AI agents took minutes — not months? Say hello to Agent Forge — the platform that puts AI agents at your fingertips. Here’s what you can do: 🔹 Automate your operations 🔹 Create an entire team of AI Agents 🔹 Use real-time data fetching Agents 🔹 Build powerful AI agent workflows fast 🔹 Design intelligent workflows using our drag & drop mechanism Whether you're building a startup, launching a side hustle, or just exploring AI for trading & research — Agent Forge is your new playground. ✨ Get $65 in free credits as a first-time user — no strings attached. 👉 Try it now:

📣 Agent Forge is LIVE! What if creating your own team of AI agents took minutes — not months? Say hello to Agent Forge — the platform that puts AI agents at your fingertips. Here’s what you can do: 🔹 Automate your operations 🔹 Create an entire team of AI Agents 🔹 Use real-time data fetching Agents 🔹 Build powerful AI agent workflows fast 🔹 Design intelligent workflows using our drag & drop mechanism Whether you're building a startup, launching a side hustle, or just exploring AI for trading & research — Agent Forge is your new playground. ✨ Get $65 in free credits as a first-time user — no strings attached. 👉 Try it now:

AITECH CLOUD NETWORK

598,953 views • 1 year ago

Every frontend developer just stopped opening DevTools. Your AI coding agent can now reverse-engineer the entire design system of any website directly from the terminal. Just type: /design And it instantly extracts: • Brand colors • Fonts & typography • Spacing system • Buttons & UI components • Layout patterns • Design tokens Then saves everything into a structured DESIGN.md file your AI agent can understand and reuse. Powered by Hyperbrowser + Claude Code MCP. The crazy part? You can now study, replicate, and rebuild world-class UI systems in minutes instead of wasting hours manually inspecting websites. This changes how vibe coding works forever. Repo👇

divyansh tiwari

78,201 views • 1 month ago

Two highly requested features just landed in Stitch! You can now generate custom images like logos right on the canvas and copy screens across projects. ✨ Native Image Generation: Create custom logos or hero graphics, and ask the agent to drop them directly into your UI. ✨ Copy & Paste Across Projects: Grab that perfect screen you made last week and paste it into a new project. Perfect for combining styles and merging content. Your vibe design partner just leveled up. Let’s build! 👇

Two highly requested features just landed in Stitch! You can now generate custom images like logos right on the canvas and copy screens across projects. ✨ Native Image Generation: Create custom logos or hero graphics, and ask the agent to drop them directly into your UI. ✨ Copy & Paste Across Projects: Grab that perfect screen you made last week and paste it into a new project. Perfect for combining styles and merging content. Your vibe design partner just leveled up. Let’s build! 👇

Stitch by Google

56,622 views • 2 months ago

🎨 Stop describing, start showing! One of your most requested features. Your design inspiration is now a core part of the Stitch canvas. 🖼️ Bring in any inspirational image or screenshot to add rich visual context to every step of your design journey—from initial idea to final edit. Four easy ways to add images: * Drag & drop * Paste (CMD/Ctrl+V) * Direct upload button * Attach to prompt Select images alongside your screens (CMD/Ctrl+Click) to provide the ultimate context for your next generation or edit. Coming soon: The ability to seamlessly incorporate images (logos, profile pics) directly into your generated designs.

Stitch by Google

28,714 views • 8 months ago

🤯 Building computer-vision applications is never going to be the same again. As Andrej Karpathy says, "English is going to be the new programming-language", and we just made that happen for programming visual AI. 👨‍💻 This past month, the VLM Run team cooked up something magical that I'm especially proud of - a natural-language interface to build and run computer vision workflows (object-detection, OCR, parsing, and so much more) – all via our new VLM Run MCP server. 🔌 It works with any MCP-compatible AI agent (Claude, OpenAI, Cursor, etc.) and abstracts complex visual workflows into simple English commands. No need to write Python or fiddle with bespoke computer-vision code – just say what you want your agent to do, and it does it. Here’s a glimpse into what you can build today ( ☑️ Image AI agents – run detection, tagging, blurring, cropping, and more traditional CV tasks with English ☑️ Document AI agents – extract totals from invoices, search visual content, or act on what’s found ☑️ Video AI agents – understand scene content, trim clips, add subtitles, and create ready-to-share edits ☑️ And best-of-all, it's fully programmable with English. 🧑‍🍳 MCP Showcase: 📚 MCP Cookbooks: 📚 MCP Docs: #computervision #ai #agents #llm #vlm #mcp #vibecoding #genai

🤯 Building computer-vision applications is never going to be the same again. As Andrej Karpathy says, "English is going to be the new programming-language", and we just made that happen for programming visual AI. 👨‍💻 This past month, the VLM Run team cooked up something magical that I'm especially proud of - a natural-language interface to build and run computer vision workflows (object-detection, OCR, parsing, and so much more) – all via our new VLM Run MCP server. 🔌 It works with any MCP-compatible AI agent (Claude, OpenAI, Cursor, etc.) and abstracts complex visual workflows into simple English commands. No need to write Python or fiddle with bespoke computer-vision code – just say what you want your agent to do, and it does it. Here’s a glimpse into what you can build today ( ☑️ Image AI agents – run detection, tagging, blurring, cropping, and more traditional CV tasks with English ☑️ Document AI agents – extract totals from invoices, search visual content, or act on what’s found ☑️ Video AI agents – understand scene content, trim clips, add subtitles, and create ready-to-share edits ☑️ And best-of-all, it's fully programmable with English. 🧑‍🍳 MCP Showcase: 📚 MCP Cookbooks: 📚 MCP Docs: #computervision #ai #agents #llm #vlm #mcp #vibecoding #genai

Sudeep Pillai

17,789 views • 1 year ago

Introducing Einstein Sales Agent on Salesforce's new Agentforce Platform! Scale your sales force easily with autonomous sales agents! Sales agents can turn deals over to humans directly in Salesforce Sales Cloud! Humans with AI drive customer success, together. 🔹 24/7 automated pipeline nurturing 🔹 Personalized engagement with inbound leads using trusted CRM data 🔹 Seamless transitions and human handoffs across all channels 🔹 No need for complex conversational scripts 🔹 Operates across sales, service, marketing, and commerce 🔹 Reaches leads on their preferred channel, in their preferred language 🔹 Configurable with sales strategies and knowledge, just like training a seller 🔹 Transparent governance dashboards for full oversight 🔹 Extensible low-code tools 🔹 MuleSoft for cross-system actions 🔹 Real-time, harmonized data with Data Cloud See Einstein Sales Agents in action at Dreamforce 2024! Now everyone is an Einstein. ❤️

Introducing Einstein Sales Agent on Salesforce's new Agentforce Platform! Scale your sales force easily with autonomous sales agents! Sales agents can turn deals over to humans directly in Salesforce Sales Cloud! Humans with AI drive customer success, together. 🔹 24/7 automated pipeline nurturing 🔹 Personalized engagement with inbound leads using trusted CRM data 🔹 Seamless transitions and human handoffs across all channels 🔹 No need for complex conversational scripts 🔹 Operates across sales, service, marketing, and commerce 🔹 Reaches leads on their preferred channel, in their preferred language 🔹 Configurable with sales strategies and knowledge, just like training a seller 🔹 Transparent governance dashboards for full oversight 🔹 Extensible low-code tools 🔹 MuleSoft for cross-system actions 🔹 Real-time, harmonized data with Data Cloud See Einstein Sales Agents in action at Dreamforce 2024! Now everyone is an Einstein. ❤️

Marc Benioff

56,695 views • 1 year ago

🚀 The team at Google DeepMind just released Gemini Embedding 2, a frontier embeddings model with 3072 dimensions and state-of-the-art semantic quality. 👩‍💻 We built a demo showing how to integrate it across the LlamaIndex ecosystem, from LlamaParse to LlamaAgents: 𝗮𝘂𝗱𝗶𝗼-𝗸𝗯, a knowledge base for your audio notes. With audio-kb, you can: 🔹 Upload an MP3 or record directly from your terminal 🔹 LlamaParse extracts the transcript from the audio 🔹 Gemini Embedding 2 generates embeddings 🔹 Metadata + vectors are stored in SurrealDB and indexed with HNSW 🔍 Once ingested, you can search all your audio notes directly from the terminal. 🎙️ Perfect for turning voice memos, meetings, or lectures into a searchable knowledge base. 📖 Full blog: 💻 GitHub: ⚡ Try LlamaParse:

🚀 The team at Google DeepMind just released Gemini Embedding 2, a frontier embeddings model with 3072 dimensions and state-of-the-art semantic quality. 👩‍💻 We built a demo showing how to integrate it across the LlamaIndex ecosystem, from LlamaParse to LlamaAgents: 𝗮𝘂𝗱𝗶𝗼-𝗸𝗯, a knowledge base for your audio notes. With audio-kb, you can: 🔹 Upload an MP3 or record directly from your terminal 🔹 LlamaParse extracts the transcript from the audio 🔹 Gemini Embedding 2 generates embeddings 🔹 Metadata + vectors are stored in SurrealDB and indexed with HNSW 🔍 Once ingested, you can search all your audio notes directly from the terminal. 🎙️ Perfect for turning voice memos, meetings, or lectures into a searchable knowledge base. 📖 Full blog: 💻 GitHub: ⚡ Try LlamaParse:

LlamaIndex 🦙

34,765 views • 4 months ago