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This is something I've been working on Procedural Playground, focus on UX. Made for agents No save/export between apps Generation fully editable between programs Photoshop + Figma native plugins Vector output Procedural engines & vector stack Keyframe Animation - Video shows interaction between the PS plugin and the Web... show more

Jorge

7,720 subscribers

20,792 次观看 • 2 个月前 •via X (Twitter)

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Butler starts with content. Just like Amazon started with books. But this goes deeper: a live test of agent-native UX at scale. Request in, output out, fully public, directly on X. No apps. No dashboards. It’s the first working glimpse of ACP: agents that discover, negotiate, and execute, across platforms, for anyone. The future of the internet isn’t just apps. It’s agents. And content is just the starting point.

Butler starts with content. Just like Amazon started with books. But this goes deeper: a live test of agent-native UX at scale. Request in, output out, fully public, directly on X. No apps. No dashboards. It’s the first working glimpse of ACP: agents that discover, negotiate, and execute, across platforms, for anyone. The future of the internet isn’t just apps. It’s agents. And content is just the starting point.

Virtuals Protocol

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the video is live. full app built in under 3 hours. raw. uncut. bugs and all. the stack: → Idea Browser — idea to full PRD in minutes → Mobbin — production grade UI patterns from pre-existing apps → — built full stack with plain english (i specialize in frontend but you can also use superbase) what you'll see: HOUR 1: PRD generation (user flows, features, edge cases) HOUR 2: reference hunting (real apps > dribbble fantasy) HOUR 3: full build (frontend and you can use superbase for backend) this isn't a polished tutorial. it's the actual workflow. live. you'll see where it breaks. you'll see how I fix it. the gap between "idea" and "shipped product" is now 3 hours. watch it. then go build something. like + RT if this changes how your new workflow looks like..

the video is live. full app built in under 3 hours. raw. uncut. bugs and all. the stack: → Idea Browser — idea to full PRD in minutes → Mobbin — production grade UI patterns from pre-existing apps → — built full stack with plain english (i specialize in frontend but you can also use superbase) what you'll see: HOUR 1: PRD generation (user flows, features, edge cases) HOUR 2: reference hunting (real apps > dribbble fantasy) HOUR 3: full build (frontend and you can use superbase for backend) this isn't a polished tutorial. it's the actual workflow. live. you'll see where it breaks. you'll see how I fix it. the gap between "idea" and "shipped product" is now 3 hours. watch it. then go build something. like + RT if this changes how your new workflow looks like..

MotionViz

21,716 次观看 • 7 个月前

🚀Launching CoAgents Public Beta 🪁: Everything you need to build Agent-Native applications, powered by LangGraph & CopilotKit. CoAgents enables in-app agents with: - Agenetic generative UI ✨ - Shared state (between agent application) - Streaming intermediate agent state - Human-in-the-Loop (Human approval & planning) 👨‍🦰 - Frontend Actions 💪 --- We’ve recently seen the emergence of Agent-Native applications that actually work: powered by vertical AI agents + agentic UX + deep in-app integration. (Apps like the Replit AI Agent, OpenAI Canvas, etc, but for any domain) With CoAgents + LangGraph, you can build this next generation of agent apps, for any vertical, with a clean and easy to use infrastructure (in hours). 💻Get started: 🗞️Blog: 🕹️Demo: 🗓️Webinar (Build an Agent-Native Apps with CoAgents & LangGraph): CC: Atai Barkai, , Harrison Chase

🚀Launching CoAgents Public Beta 🪁: Everything you need to build Agent-Native applications, powered by LangGraph & CopilotKit. CoAgents enables in-app agents with: - Agenetic generative UI ✨ - Shared state (between agent application) - Streaming intermediate agent state - Human-in-the-Loop (Human approval & planning) 👨‍🦰 - Frontend Actions 💪 --- We’ve recently seen the emergence of Agent-Native applications that actually work: powered by vertical AI agents + agentic UX + deep in-app integration. (Apps like the Replit AI Agent, OpenAI Canvas, etc, but for any domain) With CoAgents + LangGraph, you can build this next generation of agent apps, for any vertical, with a clean and easy to use infrastructure (in hours). 💻Get started: 🗞️Blog: 🕹️Demo: 🗓️Webinar (Build an Agent-Native Apps with CoAgents & LangGraph): CC: Atai Barkai, , Harrison Chase

CopilotKit🪁

51,666 次观看 • 1 年前

Support for Agent Plugins is live in Cursor (and I made a plugin for searching X!) Agent Plugins combine Skills and MCP servers into a single package Think about them like an Ikea furniture kit: your table comes with instructions, parts, and tools. You use the instructions to understand how things work (which tools on which parts), then use the tools to assemble your furniture Agent Plugins are bundles of tools & resources that allow agents to accomplish a goal: - MCP servers: fixed context and tools - Skills: dynamic instructions, loaded progressively Plugins bundle tools and instructions so your agent is able to use tokens efficiently Many of us already use MCP servers and skills together - Agent Plugins formalize this pattern for more powerful workflows I'm excited to see where the standard takes us!

Support for Agent Plugins is live in Cursor (and I made a plugin for searching X!) Agent Plugins combine Skills and MCP servers into a single package Think about them like an Ikea furniture kit: your table comes with instructions, parts, and tools. You use the instructions to understand how things work (which tools on which parts), then use the tools to assemble your furniture Agent Plugins are bundles of tools & resources that allow agents to accomplish a goal: - MCP servers: fixed context and tools - Skills: dynamic instructions, loaded progressively Plugins bundle tools and instructions so your agent is able to use tokens efficiently Many of us already use MCP servers and skills together - Agent Plugins formalize this pattern for more powerful workflows I'm excited to see where the standard takes us!

matt palmer

39,554 次观看 • 9 天前

The breakdown of doing a Procedural Bridge in Unreal Engine with Dash is here! 🔥 You will see several of the procedural tools in Dash and how to use them together to create complex procedural setups. This bridge is only one out of many examples possible! Of course, this procedural bridge could be created with PCG as well, but with Dash, we believe we have made it much simpler, with no need to set up any complex node systems. If you like PCG and use it for creating procedural setups like this, we would love to hear your thoughts, is the Dash workflow a valid alternative, or can it be used together with PCG to improve your UE5 workflows?

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Polygonflow Dash

11,929 次观看 • 1 年前

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m0h

69,625 次观看 • 3 个月前

🙌Meet Artifig: A Figma Plugin to Generate Figma Plugins Do you use Figma and ever feel like this: - Your mind is bursting with plugin ideas, but you can't bring them to life because you don't know how to code? - You want to focus on design, but repetitive tasks keep slowing you down? - You dream of creating custom tools for your team, but lack the time or resources? I’ve been there too. That’s why I created Artifig. ✨ What is Artifig? Artifig is an AI-powered Figma plugin that empowers anyone to build their own Figma plugins using just natural language. No coding needed—simply describe what you want, and watch as your idea transforms into a fully functional, real-time plugin. 🚀 Redefining Figma Plugin Development The core philosophy of Artifig is simple: Designers often have countless ideas and creative visions, but many of them remain unrealized due to a lack of technical skills. We believe designers shouldn’t be limited by their inability to code. You should focus on creating, not be held back by technical barriers or repetitive tasks. Artifig takes you directly from "description" to "implementation." 🛠️ How Does It Work? 1. Describe Your Needs: Tell Artifig what you want, like “Create a skew transformation tool for objects, supporting horizontal and vertical skew with real-time preview functionality.” 2. Generate and Run the Plugin: Artifig instantly generates the plugin and runs it right within Figma. For example, the generated plugin can apply skew transformations to objects, precisely controlled via matrix transformations, with an intuitive user experience. 3. Optimize and Iteration: Need adjustments? Simply describe them, and Artifig will Iterating the plugin step by step. 4. Share Your Creations: Publish your plugins to the Artifig community, or remix plugins shared by others to build on their ideas. No learning curve. No complex steps. It’s as simple as that. 🌟 Key Features - Zero Barrier to Entry: No coding experience needed—any Figma user can create plugins effortlessly. - Multilingual Support: Works in multiple languages, including English, Chinese, French, Japanese, and German. - What-You-See-Is-What-You-Get: Generated plugins run in real-time, so you can quickly validate and refine your ideas. - Open and Flexible: The generated plugin code is 100% yours—modify it, distribute it, even use it commercially. - Global Community: Share your plugins, explore others’ creations, and publish your plugins to the Figma community. 🎯 Why is Artifig a Game-Changer? 1. No More Repetitive Work Let AI handle the tedious, time-consuming tasks: batch renaming layers, auto-aligning elements, or applying styles in bulk. All you need to do is say, “Import a PDF and arrange each image on the canvas with 20px spacing.” 2. Quickly Bring Ideas to Life From color contrast checks to data imports and custom components, all your “what if we could” ideas can now become plugins. Just one natural language description, and Artifig makes it happen. 3. Custom Tools for Your Team Build tailored tools for your team, creating unique solutions to streamline your workflow. 4. Not Just a Tool, But a Learning Experience Artifig explains the logic behind the code it generates, helping you understand Figma APIs and JavaScript. Today, you’re a designer; tomorrow, you could also be a design engineer. 🧑‍🚀👩🏻‍💻🥷🏻 Who is Artifig For? - Beginners: No development experience needed—just describe your ideas and let Artifig do the rest. - Experts: Save time and focus on high-value tasks while Artifig handles the repetitive work. - Learners: Use Artifig as a bridge to deepen your understanding of development. - Teams: Build custom tools to enhance collaboration and efficiency. 🎉 Ready to Get Started? I believe designers’ time and focus should be spent on creating, not on wrestling with complex tools. Artifig is the first step toward realizing this vision. Try Artifig now and experience an unprecedented flow of creativity!

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yancymin

21,222 次观看 • 1 年前

This might be the craziest workflow you'll see this week. From #VR greyboxing to 3D worlds with the help of #AI. The 2 tools I used are ShapesXR and Marble from World Labs. Let me tell you why and how. - ShapesXR is the most powerful and fastest way to assemble 3D scenes at scale. - The library of assets + ability to sketch from procedural primitives gives the perfect balance between speed and freedom. - ShapesXR allows you to export your creation as a glTF that can be used as a "3D prompt" into Marble - Marble now allows you to create a panorama using a 3D scene as input increasing DRAMATICALLY the control you have during the creation process - Through the workflow you can adjust textures and objects in the scene using AI inpainting - There are tons of options on how to use the final output (create a #GaussianSplatting, export collision mesh and even a detailed mesh 🤯) This is the perfect examples of how VR creative tools improve and accelerate the design process... so make sure to follow me if that's your jam 😉.

This might be the craziest workflow you'll see this week. From #VR greyboxing to 3D worlds with the help of #AI. The 2 tools I used are ShapesXR and Marble from World Labs. Let me tell you why and how. - ShapesXR is the most powerful and fastest way to assemble 3D scenes at scale. - The library of assets + ability to sketch from procedural primitives gives the perfect balance between speed and freedom. - ShapesXR allows you to export your creation as a glTF that can be used as a "3D prompt" into Marble - Marble now allows you to create a panorama using a 3D scene as input increasing DRAMATICALLY the control you have during the creation process - Through the workflow you can adjust textures and objects in the scene using AI inpainting - There are tons of options on how to use the final output (create a #GaussianSplatting, export collision mesh and even a detailed mesh 🤯) This is the perfect examples of how VR creative tools improve and accelerate the design process... so make sure to follow me if that's your jam 😉.

Gabriele Romagnoli

20,126 次观看 • 9 个月前

I built a multiplayer embroidery sampler for the internet. It's called Common Thread. 🪡 Built the entire thing in Figma Make, first thing I've ever vibecoded with it. Every visitor gets a patch on a shared canvas. You pick a thread color, choose a stitch type, and craft your art. A sampler is a piece of fabric where you practice and collect different stitches — a reference guide and playground in one. They were meant to be passed between hands and added to over time. Common Thread is that, but the fabric is infinite, the UI is whimsical, and the hands are anonymous. The part I love most: you can snap any section with a draggable embroidery hoop and export it, framed. i love how Figma Make is a kind of tool that lets you focus on what something should feel like, not how to ship it. Made for the Contra x Figma Makethon #FigmaMakeathon Try it yourself! /link below/

I built a multiplayer embroidery sampler for the internet. It's called Common Thread. 🪡 Built the entire thing in Figma Make, first thing I've ever vibecoded with it. Every visitor gets a patch on a shared canvas. You pick a thread color, choose a stitch type, and craft your art. A sampler is a piece of fabric where you practice and collect different stitches — a reference guide and playground in one. They were meant to be passed between hands and added to over time. Common Thread is that, but the fabric is infinite, the UI is whimsical, and the hands are anonymous. The part I love most: you can snap any section with a draggable embroidery hoop and export it, framed. i love how Figma Make is a kind of tool that lets you focus on what something should feel like, not how to ship it. Made for the Contra x Figma Makethon #FigmaMakeathon Try it yourself! /link below/

charlota

520,504 次观看 • 5 个月前

Agents were once limited to calling APIs. Now agents participate in the economy. The missing element for autonomous agents was always payments. Now agents transact natively on the internet using x402, enabling autonomous payments between agents and services. Agent Stack: 🦞 Openclaw agent infra ▶️ Telegram communication layer 🤖 Teneo agent + agent wallet Agent Workflow - Compare accounts following two separate X handles: ✅ User - Enters a query ✅ Agent - Autonomously selects the correct Teneo agent and queries it ✅ Agent - Pays via x402 on Avalanche🔺 ✅ Agent - Returns structured dataset Any user can simply ask a question and give a job. The agent does everything else No API keys. No subscriptions. Just programmatic value exchange. Build and monetize your own agents today. #A2A #x402 #Infra

Agents were once limited to calling APIs. Now agents participate in the economy. The missing element for autonomous agents was always payments. Now agents transact natively on the internet using x402, enabling autonomous payments between agents and services. Agent Stack: 🦞 Openclaw agent infra ▶️ Telegram communication layer 🤖 Teneo agent + agent wallet Agent Workflow - Compare accounts following two separate X handles: ✅ User - Enters a query ✅ Agent - Autonomously selects the correct Teneo agent and queries it ✅ Agent - Pays via x402 on Avalanche🔺 ✅ Agent - Returns structured dataset Any user can simply ask a question and give a job. The agent does everything else No API keys. No subscriptions. Just programmatic value exchange. Build and monetize your own agents today. #A2A #x402 #Infra

Teneo Protocol

41,730 次观看 • 4 个月前

GeoLibre v1.1 is out! GeoLibre is a free and open-source, lightweight, cloud-native GIS platform for visualizing, exploring, and analyzing geospatial data. One application that runs everywhere: in your web browser, as a native desktop app, on your phone, and inside a Jupyter notebook. No account, no server, no cost. Everything runs locally and your data stays private. This release builds on the v1.0 foundation with features that make day-to-day mapping smoother: - Attribute table management — rename, delete, hide/show, and reorder fields right in the table, with the layout saved to your project. - Data-driven symbology for Add Vector Layer — single, categorized, graduated, and expression-based styling now applies to maplibre-gl-vector layers. - Atmosphere Effects plugin — a deep-space backdrop, parallax starfield, comets, and a glowing globe halo at low zoom (toggle it from the Controls menu). - Layer panel upgrades — rename layers, open the attribute table, and export straight from the layer actions menu. - Auto Refresh extended to Add Vector Layer URL layers. - In-browser GeoPandas via Pyodide — run the vector tools with no Python sidecar, same results. - Plugin API — external plugins can now render on the host's shared instance via app.getDeckGL(). Try the live demo: Star it on GitHub: Docs and roadmap: Release notes: #GIS #OpenSource #Geospatial #MapLibre #WebGIS #DuckDB #GeoLibre

GeoLibre v1.1 is out! GeoLibre is a free and open-source, lightweight, cloud-native GIS platform for visualizing, exploring, and analyzing geospatial data. One application that runs everywhere: in your web browser, as a native desktop app, on your phone, and inside a Jupyter notebook. No account, no server, no cost. Everything runs locally and your data stays private. This release builds on the v1.0 foundation with features that make day-to-day mapping smoother: - Attribute table management — rename, delete, hide/show, and reorder fields right in the table, with the layout saved to your project. - Data-driven symbology for Add Vector Layer — single, categorized, graduated, and expression-based styling now applies to maplibre-gl-vector layers. - Atmosphere Effects plugin — a deep-space backdrop, parallax starfield, comets, and a glowing globe halo at low zoom (toggle it from the Controls menu). - Layer panel upgrades — rename layers, open the attribute table, and export straight from the layer actions menu. - Auto Refresh extended to Add Vector Layer URL layers. - In-browser GeoPandas via Pyodide — run the vector tools with no Python sidecar, same results. - Plugin API — external plugins can now render on the host's shared instance via app.getDeckGL(). Try the live demo: Star it on GitHub: Docs and roadmap: Release notes: #GIS #OpenSource #Geospatial #MapLibre #WebGIS #DuckDB #GeoLibre

Qiusheng Wu

20,833 次观看 • 2 个月前

Don’t know how to use Remotion with Claude Code? We got you. This video is fully made with Video Agent. Avatar, script, motion graphics, and the final edits all with one prompt. Try Video Agent for free on HeyGen

Joshua Xu

172,749 次观看 • 6 个月前

GeoLibre v1.9.0 is here! GeoLibre is a free and open-source, lightweight, cloud-native GIS platform for visualizing, exploring, and analyzing geospatial data. It runs everywhere you do, in the web browser, on the desktop, on mobile, and inside Jupyter notebooks, all while keeping your data local and private. This release brings CAD drawing import, smarter WMS and WFS service discovery, and a docked SQL workspace with autocomplete. What's new in v1.9.0 - CAD import: Add CAD drawings (DXF/DWG) as a layer, with a picker for choosing which drawing layers to load and a CRS selector for placing them correctly on the map. - Smarter service discovery: WMS and WFS panels now read the service's GetCapabilities, so you pick available layers and feature types from a populated dropdown instead of typing names by hand. - Docked SQL Workspace: The SQL Workspace now docks as a resizable panel beside the map, with editor autocomplete for tables, columns, and SQL keywords. - Generic Vector to Vector conversion: Convert between any supported vector formats by file extension, alongside the existing targeted converters. - Richer camera tours: Per-keyframe hold and transition duration controls for finer pacing, plus save and reload of a named tour setup. - Better story maps: A hide-itinerary toggle, subtitle and byline fields on the printable handout, and dedicated start and closing slides. - Styling and plugin extras: A transparent (no fill / no outline) option in the color picker, a Legend populated from a paletted raster's color table, and plugins can now use the maplibre-gl-raster stack and the projection control. Try it out - Launch GeoLibre web: - GitHub: - Documentation: - Release notes: #GIS #Geospatial #OpenSource #RemoteSensing #DataVisualization #MapLibre #Python

GeoLibre v1.9.0 is here! GeoLibre is a free and open-source, lightweight, cloud-native GIS platform for visualizing, exploring, and analyzing geospatial data. It runs everywhere you do, in the web browser, on the desktop, on mobile, and inside Jupyter notebooks, all while keeping your data local and private. This release brings CAD drawing import, smarter WMS and WFS service discovery, and a docked SQL workspace with autocomplete. What's new in v1.9.0 - CAD import: Add CAD drawings (DXF/DWG) as a layer, with a picker for choosing which drawing layers to load and a CRS selector for placing them correctly on the map. - Smarter service discovery: WMS and WFS panels now read the service's GetCapabilities, so you pick available layers and feature types from a populated dropdown instead of typing names by hand. - Docked SQL Workspace: The SQL Workspace now docks as a resizable panel beside the map, with editor autocomplete for tables, columns, and SQL keywords. - Generic Vector to Vector conversion: Convert between any supported vector formats by file extension, alongside the existing targeted converters. - Richer camera tours: Per-keyframe hold and transition duration controls for finer pacing, plus save and reload of a named tour setup. - Better story maps: A hide-itinerary toggle, subtitle and byline fields on the printable handout, and dedicated start and closing slides. - Styling and plugin extras: A transparent (no fill / no outline) option in the color picker, a Legend populated from a paletted raster's color table, and plugins can now use the maplibre-gl-raster stack and the projection control. Try it out - Launch GeoLibre web: - GitHub: - Documentation: - Release notes: #GIS #Geospatial #OpenSource #RemoteSensing #DataVisualization #MapLibre #Python

Qiusheng Wu

19,611 次观看 • 1 个月前

I’m usually skeptical of “AI workspace” products, but Bloome has a few ideas I actually like: You can put humans + multiple agents in the same conversation. One agent can draft something, another can poke holes in it, and another can clean up the final version. You can also bring in different agents/models like Claude, ChatGPT, DeepSeek, etc. instead of constantly bouncing between tabs. And because the whole conversation stays in context, teammates can join later and still understand how the work got to the final output. It also works across web, desktop, and mobile, though if you’re using it for real work, I’d especially recommend trying the desktop app. Feels closer to how real teams actually work.

I’m usually skeptical of “AI workspace” products, but Bloome has a few ideas I actually like: You can put humans + multiple agents in the same conversation. One agent can draft something, another can poke holes in it, and another can clean up the final version. You can also bring in different agents/models like Claude, ChatGPT, DeepSeek, etc. instead of constantly bouncing between tabs. And because the whole conversation stays in context, teammates can join later and still understand how the work got to the final output. It also works across web, desktop, and mobile, though if you’re using it for real work, I’d especially recommend trying the desktop app. Feels closer to how real teams actually work.

AI Breakfast

78,285 次观看 • 1 个月前

HEY CUTIE... - Short Animation Test It's finally out! A short little animation test between Jaizybel and Noa we've been working on for a while (along other things eheheh...)! The goal of this animation test is to settle on a finished look and show you what stylization we aim for

HEY CUTIE... - Short Animation Test It's finally out! A short little animation test between Jaizybel and Noa we've been working on for a while (along other things eheheh...)! The goal of this animation test is to settle on a finished look and show you what stylization we aim for

Joyark Toons

161,300 次观看 • 1 年前

I've been working on web projects with Three.js more and more lately — 2D, 3D, XR — and the one thing I've noticed is the lack of tools compared to game engines. That's why I decided to start building on the side a library of 3D assets that are actually little programs, AI-native, and fully customizable. I called this Polyfork , and it's already being used by dozens of people that have an AI centric workflow, since the website can be fully understood and used by agents. Assets are being built each day, at a rate of 100+ a week, and I'm planning to make it the biggest programmatic-3D library on the internet. Almost half of the models are free, and I opened slots for "founding" members, who can make a one-time payment for lifetime access, with access to all current models and kits, plus everything built from now on. Get one before they run out.

I've been working on web projects with Three.js more and more lately — 2D, 3D, XR — and the one thing I've noticed is the lack of tools compared to game engines. That's why I decided to start building on the side a library of 3D assets that are actually little programs, AI-native, and fully customizable. I called this Polyfork , and it's already being used by dozens of people that have an AI centric workflow, since the website can be fully understood and used by agents. Assets are being built each day, at a rate of 100+ a week, and I'm planning to make it the biggest programmatic-3D library on the internet. Almost half of the models are free, and I opened slots for "founding" members, who can make a one-time payment for lifetime access, with access to all current models and kits, plus everything built from now on. Get one before they run out.

Lucas Martinic

25,084 次观看 • 12 天前

New short course on Building Applications with Vector Databases, taught by Pinecone’s Tim Tully! At the heart of a vector database is the ability to store a collection of vectors and then query against that, meaning input a new vector and find similar ones. This is useful for many AI applications. In this course, you'll learn how to use vector databases to build: (i) Semantic Search: Create a text search tool that goes beyond keyword matching, and instead focuses on the meaning of content. (ii) RAG (retrieval augmented generation): Enhance your LLM output by incorporating context from sources the model wasn't trained on. (iii) Recommender System: Combine semantic search and RAG to recommend topics, and demonstrate it with a news article recommender. (iv) Hybrid Search: Build an application that finds items using both images and descriptive text -- by combining both sparse and dense vector representations of the data -- using an eCommerce dataset as an example. (v) Image Similarity: Use image vector embeddings to create an app to compare facial features, using a database of public figures to determine the likeness between them. (vi) Anomaly Detection: Build an anomaly detection app that identifies unusual patterns in network communication logs. I hope you’ll enjoy learning how to build all these types of applications! Please sign up here:

New short course on Building Applications with Vector Databases, taught by Pinecone’s Tim Tully! At the heart of a vector database is the ability to store a collection of vectors and then query against that, meaning input a new vector and find similar ones. This is useful for many AI applications. In this course, you'll learn how to use vector databases to build: (i) Semantic Search: Create a text search tool that goes beyond keyword matching, and instead focuses on the meaning of content. (ii) RAG (retrieval augmented generation): Enhance your LLM output by incorporating context from sources the model wasn't trained on. (iii) Recommender System: Combine semantic search and RAG to recommend topics, and demonstrate it with a news article recommender. (iv) Hybrid Search: Build an application that finds items using both images and descriptive text -- by combining both sparse and dense vector representations of the data -- using an eCommerce dataset as an example. (v) Image Similarity: Use image vector embeddings to create an app to compare facial features, using a database of public figures to determine the likeness between them. (vi) Anomaly Detection: Build an anomaly detection app that identifies unusual patterns in network communication logs. I hope you’ll enjoy learning how to build all these types of applications! Please sign up here:

Andrew Ng

137,091 次观看 • 2 年前

I don't think specialized vector databases will survive for much longer. They were a big thing for a while, but now, you have pro-grade databases like MongoDB offering native support for vector search. If you don't understand how vector search is an absolutely bonkers, mind-blowing invention, watch the attached video. Give me 4 minutes, and I promise you'll understand how vectors have completely changed the game. Honestly, MongoDB is cracked! They have become a one-stop shop for AI implementations in addition to its document and non-relational model. You'll find a link below to the source code of 7 examples of AI agents that use MongoDB: 1. A factory safety assistant agent 2. A research assistant agent 3. An investment researcher agent 4. A recommendation system agent using RAG 5. A human resources chatbot agent 6. An AWS Bedrock agent 7. An asset manager assistant agent Everything is on a GitHub repository. Link below.

I don't think specialized vector databases will survive for much longer. They were a big thing for a while, but now, you have pro-grade databases like MongoDB offering native support for vector search. If you don't understand how vector search is an absolutely bonkers, mind-blowing invention, watch the attached video. Give me 4 minutes, and I promise you'll understand how vectors have completely changed the game. Honestly, MongoDB is cracked! They have become a one-stop shop for AI implementations in addition to its document and non-relational model. You'll find a link below to the source code of 7 examples of AI agents that use MongoDB: 1. A factory safety assistant agent 2. A research assistant agent 3. An investment researcher agent 4. A recommendation system agent using RAG 5. A human resources chatbot agent 6. An AWS Bedrock agent 7. An asset manager assistant agent Everything is on a GitHub repository. Link below.

Santiago

60,065 次观看 • 1 年前

It takes 5 minutes to create a world-class web research agent that runs 24/7 and returns structured search results. 1. You can limit the sources it's allowed to use 2. You can specify the goals it needs to complete 3. You can design the format structure of the results 4. You can configure how much computing power it will use I show you how to set up a Web Search Agent in the video. A few benefits here: 1. This is great for complex research tasks 2. It's really easy to add this like a LEGO piece to a more complex workflow 3. Create an agent once, and reuse it with different inputs 4. The agent adapts to your use case as you work with it By the way, Nimble published a whole library of templates and research agents you can reuse and modify. You can start sending queries to one of these existing agents, and it will begin to adapt to Go here to try it out: Thanks to the Nimble team for partnering with me on this post.

It takes 5 minutes to create a world-class web research agent that runs 24/7 and returns structured search results. 1. You can limit the sources it's allowed to use 2. You can specify the goals it needs to complete 3. You can design the format structure of the results 4. You can configure how much computing power it will use I show you how to set up a Web Search Agent in the video. A few benefits here: 1. This is great for complex research tasks 2. It's really easy to add this like a LEGO piece to a more complex workflow 3. Create an agent once, and reuse it with different inputs 4. The agent adapts to your use case as you work with it By the way, Nimble published a whole library of templates and research agents you can reuse and modify. You can start sending queries to one of these existing agents, and it will begin to adapt to Go here to try it out: Thanks to the Nimble team for partnering with me on this post.

Santiago

20,943 次观看 • 12 天前

‼️MENU CUSTOMIZATION‼️ With the latest upcoming update, you can now change the main menu with your favorite TEKKEN character. This includes the ability to switch between default costume presets. No word has officially been made on whether this also includes customization presets. Video by Kayane

‼️MENU CUSTOMIZATION‼️ With the latest upcoming update, you can now change the main menu with your favorite TEKKEN character. This includes the ability to switch between default costume presets. No word has officially been made on whether this also includes customization presets. Video by Kayane

YellowMotion

37,812 次观看 • 1 年前