[{"data":1,"prerenderedAt":554},["ShallowReactive",2],{"blog-\u002Fblog\u002Fai\u002F2":3,"blog-all-for-related":4,"blog-all-ai":5},null,[],[6,26,56,67,82,99,114,128,143,157,171,187,201,216,232,258,274,289,303,317,331,353,386,421,440,455,470,495,510,524],{"path":7,"title":8,"date":9,"tags":10,"authors":13,"description":15,"meta":16,"image":25},"\u002Fblog\u002F2026\u002F05\u002Fflowfuse-expert-building-flows","How to Build Industrial Apps With FlowFuse AI Expert","2026-05-13",[11,12],"flowfuse","ai",[14],"sumit-shinde","FlowFuse Expert now builds applications from a description. Here's what that looks like, what Expert understands about your environment, and how to keep iterating.",{"keywords":17,"excerpt":18},"flowfuse ai expert, flowfuse expert, industrial automation, node-red, industrial dashboards, mqtt, opc ua, industrial iot, ai-assisted development, real-time monitoring, flowfuse cloud, machine monitoring",{"type":19,"value":20},"minimark",[21],[22,23,24],"p",{},"FlowFuse Expert now builds applications for you. Describe what you need, and the flow is built in front of you on the canvas, wired and configured. Ask for a change, it updates on the spot.","\u002Fblog\u002F2026\u002F05\u002Fimages\u002Fflowfuse-ai-expert-tile.png",{"path":27,"title":28,"date":29,"tags":30,"authors":33,"description":35,"meta":36,"image":55},"\u002Fblog\u002F2026\u002F04\u002Fflowfuse-release-2-29","FlowFuse 2.29: FlowFuse Expert Comes to Self-Hosted Enterprise","2026-04-09",[11,31,32,12],"news","releases",[34],"dimitrie-hoekstra","FlowFuse 2.29 brings FlowFuse Expert to self-hosted enterprise customers, adds Azure DevOps as a supported Git provider, and makes snapshot comparisons clearer with property-level diffs.",{"release":37,"features":38,"excerpt":50},"2.29",[39,42,45,48],{"id":40,"heading":41},"git-integration-azure","Azure DevOps Git Integration",{"id":43,"heading":44},"snapshot-compare","See Exactly What Changed in a Snapshot",{"id":46,"heading":47},"ff-expert","FlowFuse Expert, Available to More Teams and More Capable",{"heading":49},"What else is new?",{"type":19,"value":51},[52],[22,53,54],{},"FlowFuse 2.29 gives teams more control over how flows move through their stack, makes it easier to understand what changed between versions, and brings FlowFuse Expert to self-hosted enterprise customers.","\u002Fblog\u002F2026\u002F04\u002Fimages\u002Fflowfuse-release-2-29.png",{"path":57,"title":58,"date":59,"tags":60,"authors":61,"description":63,"meta":64,"image":66},"\u002Fblog\u002F2026\u002F03\u002Frethinking-edge-ais-core-orchestration","Rethinking Edge AI's Core Orchestration","2026-03-27",[11,12],[62],"zeger-jan-van-de-weg","How AI-driven edge connectivity is redefining industrial operations, bridging IT and OT, and turning AI pilots into scalable, real-world impact.",{"keywords":65},"Edge AI, Node-RED, FlowFuse, industrial automation, OT IT integration, knowledge management, IIoT integration, PLC integration, industrial AI, Edge connectivity","\u002Fblog\u002F2026\u002F03\u002Fimages\u002Frethinking-edge-ais-core-orchestration.png",{"path":68,"title":69,"date":70,"tags":71,"authors":72,"description":73,"meta":74,"image":81},"\u002Fblog\u002F2026\u002F03\u002Fai-usecases-in-factory","5 Places Smart Factories Are Already Using AI","2026-03-24",[11,12],[14],"Most manufacturers are still debating AI adoption. These five use cases are already running in production, cutting downtime, scrap, energy costs, and injury rates.",{"keywords":75,"excerpt":76},"AI in manufacturing, smart factory AI, predictive maintenance CNC machines, visual quality inspection AI, computer vision manufacturing, IIoT AI use cases, factory floor AI, HVAC energy optimization manufacturing, AI worker safety ergonomics, manufacturing AI examples, Node-RED IIoT integration, unplanned downtime manufacturing, AI anomaly detection industrial motors, Industry 4.0 AI",{"type":19,"value":77},[78],[22,79,80],{},"The factory floor wasn't exactly an early adopter of artificial intelligence.","\u002Fblog\u002F2026\u002F03\u002Fimages\u002Fai-use-case.png",{"path":83,"title":84,"date":85,"tags":86,"authors":87,"description":88,"meta":89,"image":98},"\u002Fblog\u002F2026\u002F03\u002Flast-mile-problem-ai","The Last Mile Problem in Industrial AI","2026-03-09",[11,12],[14],"Your AI pilot passed every test and stalled before production. Here is why that keeps happening, and what it actually takes to stop it.",{"keywords":3,"excerpt":90},{"type":19,"value":91},[92,95],[22,93,94],{},"There is a slide that lives in almost every industrial AI project deck.",[22,96,97],{},"On the left: data collection, model training, validation. On the right: operational value, reduced downtime, optimized throughput. In the middle, a small box labeled \"deployment\" that nobody in the room questions, because everyone has already moved on to the numbers on the right.","\u002Fblog\u002F2026\u002F03\u002Fimages\u002Flast-mile-problem-ai.png",{"path":100,"title":101,"date":102,"tags":103,"authors":104,"description":105,"meta":106,"image":113},"\u002Fblog\u002F2026\u002F02\u002Fedge-ai-is-80-percent-pipeline-and-20-percent-ai","Edge AI Is 80% Plumbing, 20% Intelligence","2026-02-27",[11,12],[14],"Learn how manufacturers are turning Edge AI pilots into production reality, and why the plumbing matters more than the model.",{"keywords":107,"excerpt":108},"Edge AI, Industrial IoT, IIoT, manufacturing AI, Edge AI deployment, AI pilot to production, Node-RED, FlowFuse, ONNX, predictive maintenance, anomaly detection, edge device management, industrial automation, OT IT convergence",{"type":19,"value":109},[110],[22,111,112],{},"The model is the easy part. I know that is not what you were told. But it is true, and somewhere between your third deployment and your first production fire, you will stop arguing with it.","\u002Fblog\u002F2026\u002F02\u002Fimages\u002Fedge-ai-is-80-20.png",{"path":115,"title":116,"date":117,"tags":118,"authors":119,"description":120,"meta":121,"image":127},"\u002Fblog\u002F2026\u002F02\u002Fmotor-anomaly-detector-ai","Building an AI Vibration Anomaly Detector for Industrial Motors","2026-02-20",[11,12],[14],"Learn how to monitor industrial motors continuously, train a custom autoencoder on healthy vibration data, and deploy real-time anomaly detection in Node-RED.",{"excerpt":122},{"type":19,"value":123},[124],[22,125,126],{},"Bearing wear, shaft misalignment, and imbalance don't appear overnight. They develop over days or weeks, leaving a clear trail in vibration data long before any audible or thermal symptoms emerge. By the time a technician hears grinding or feels heat, the window for low-cost intervention has already closed.","\u002Fblog\u002F2026\u002F02\u002Fimages\u002Fmotor-anomaly-detection-ai.png",{"path":129,"title":130,"date":131,"tags":132,"authors":133,"description":134,"meta":135,"image":142},"\u002Fblog\u002F2026\u002F02\u002Fshop-floor-to-ai-signals-context-decisions","Shop Floor AI: Dead on Arrival Without This","2026-02-06",[11,12],[14],"Industrial AI doesn't fail because of bad models - it fails because of bad architecture. Discover why signals need context and how a Unified Namespace makes AI work on the shop floor.",{"keywords":136,"excerpt":137},"industrial AI, Unified Namespace, shop floor, signals, context, human decision layer, FlowFuse, Node-RED, operational data, real-time insights, factory automation, manufacturing AI",{"type":19,"value":138},[139],[22,140,141],{},"Your industrial AI initiative is dying. Maybe it's already dead.","\u002Fblog\u002F2026\u002F02\u002Fimages\u002Fshopfloor-to-ai.png",{"path":144,"title":145,"date":146,"tags":147,"authors":148,"description":145,"meta":150,"image":156},"\u002Fblog\u002F2026\u002F01\u002Fflowfuse-release-2-26","FlowFuse 2.26: Bringing access-controls to your MCP nodes","2026-01-15",[11,31,32,12],[149],"nick-oleary",{"excerpt":151},{"type":19,"value":152},[153],[22,154,155],{},"With the holiday break sitting in the middle of this release cycle, it's a smaller release than usual this month. But that hasn't stopped us continuing to make the FlowFuse Expert even more useful.","\u002Fblog\u002F2026\u002F01\u002Fimages\u002Frelease-2-26.png",{"path":158,"title":159,"date":160,"tags":161,"authors":162,"description":159,"meta":164,"image":170},"\u002Fblog\u002F2025\u002F11\u002Fflowfuse-release-2-24","FlowFuse 2.24: FlowFuse Expert in the Node-RED Editor, Scheduled Updates, Simpler Edge Device Addition, Store and Forward Blueprint, and what's next!","2025-11-20",[11,31,32,12],[163],"greg-stoutenburg",{"excerpt":165},{"type":19,"value":166},[167],[22,168,169],{},"This release unlocks several new abilities for our users, speeding your development time, easing management of Node-RED instances, providing a smoother path to adding large numbers of devices, and more. Let's dig in.","\u002Fblog\u002F2025\u002F11\u002Fimages\u002F2.24-release.png",{"path":172,"title":173,"date":174,"tags":175,"authors":177,"description":178,"meta":179,"image":186},"\u002Fblog\u002F2025\u002F11\u002Fflowfuse+llm+mcp-equals-text-driven-operations","FlowFuse + LLM + MCP = Text Driven Operations","2025-11-12",[11,176,12],"node-red",[62],"Discover how FlowFuse combines LLMs and Model Context Protocol (MCP) with Node-RED to enable text-driven operations, transforming industrial data into actionable insights through natural language queries.",{"keywords":180,"excerpt":181},"MCP, Node-RED MCP, LLM",{"type":19,"value":182},[183],[22,184,185],{},"In industrial operations it's all about getting more out of the CAPEX already\nspent. Achieving higher efficiency means everyone needs to get data from a lot of\ndifferent machines, have an understanding how these machines form lines and fit\ntogether, and holistically understand these as a group of assets that collectively\ncan achieve more.","\u002Fblog\u002F2025\u002F11\u002Fimages\u002Fflowfuse+llm+mcp-equals-text-driven-operations.png",{"path":188,"title":189,"date":190,"tags":191,"authors":192,"description":193,"meta":194,"image":200},"\u002Fblog\u002F2025\u002F10\u002Fflowfuse-release-2-23","FlowFuse 2.23: MCP and ONNX nodes, FlowFuse AI Expert on the homepage, Application-level Permission Control, FlowFuse Expert for Self-Hosted, and more!","2025-10-23",[11,31,32,12],[163],"MCP and ONNX nodes, FlowFuse AI Expert on the homepage, Application-level Permission Control, FlowFuse Expert for Self-Hosted, and more!",{"excerpt":195},{"type":19,"value":196},[197],[22,198,199],{},"In this exciting release, we've shipped several features that accelerate development in Node-RED using AI, enable creation of AI agents using new Model Context Protocol nodes, provide application-level access controls for much more sophisticated user permissions management, and put an expert flow creator right on our homepage. It's a big one! Let's have a look.","\u002Fblog\u002F2025\u002F10\u002Fimages\u002Fflowfuse-release-2-23.png",{"path":202,"title":203,"date":204,"tags":205,"authors":207,"description":208,"meta":209,"image":215},"\u002Fblog\u002F2025\u002F10\u002Fai-on-flowfuse","MCP and Custom AI Models on FlowFuse!","2025-10-13",[11,176,206,12],"post",[163],"Create your own AI agents and deploy trained models in Node-RED",{"keywords":3,"excerpt":210},{"type":19,"value":211},[212],[22,213,214],{},"We have a VERY exciting announcement today: you can now build an MCP server and upload custom-trained AI models to FlowFuse!","\u002Fblog\u002F2025\u002F10\u002Fimages\u002Fai-on-flowfuse.png",{"path":217,"title":218,"date":219,"tags":220,"authors":221,"description":223,"meta":224,"image":231},"\u002Fblog\u002F2025\u002F10\u002Fcustom-onnx-model","Deploy Custom-Trained AI Models: Using ONNX with Node-RED and FlowFuse","2025-10-10",[11,12],[222],"stephen-mclaughlin","Learn how to train and export an image classifier model, and integrate it with FlowFuse AI Nodes for low-code inference in Node-RED.",{"keywords":225,"excerpt":226},"FlowFuse, Node-RED, industrial automation, low-code platform, data analysis, vision systems, inference, AI, object detection, image classification, depth estimation, transfer learning, PyTorch, ONNX, ResNet",{"type":19,"value":227},[228],[22,229,230],{},"FlowFuse is introducing a new set of AI nodes to make it easier than ever to integrate AI and machine learning into your Node-RED workflows.\nIn this guide, you will learn how to train an image classifier model, and use it with the new FlowFuse AI Nodes to recognise your own products, components - or anything else you can imagine.","\u002Fblog\u002F2025\u002F10\u002Fimages\u002Fflowfuse-ai-nodes.png",{"path":233,"title":234,"date":235,"tags":236,"authors":237,"description":239,"meta":240,"image":257},"\u002Fblog\u002F2025\u002F10\u002Fthe-ai-orchestration-hype","Beyond Cloud AI Orchestration: Why the Future is Hybrid Edge-Cloud Intelligence","2025-10-09",[11,176,12],[238],"pablo-filomeno","How edge-cloud hybrid AI architectures unlock new possibilities for industrial applications while leveraging the best of both worlds.",{"keywords":3,"excerpt":241},{"type":19,"value":242},[243,254],[22,244,245,246,253],{},"Congratulations to n8n on their ",[247,248,252],"a",{"href":249,"rel":250},"https:\u002F\u002Fblog.n8n.io\u002Fseries-c\u002F",[251],"nofollow","Series C funding round","! This is a fantastic milestone and a clear signal that the market has moved beyond AI experimentation and into the serious business of production deployment. Platforms like n8n are mastering what we call centralized orchestration: creating cloud-native \"brains\" that connect digital services, APIs, and data sources to execute complex workflows. This approach excels for digital-first applications and represents a crucial evolution in workflow automation.",[22,255,256],{},"But for industrial applications, we need to think beyond traditional cloud orchestration.","\u002Fblog\u002F2025\u002F10\u002Fimages\u002Fthe-ai-orchestration-hype.png",{"path":259,"title":260,"date":261,"tags":262,"authors":264,"description":265,"meta":266,"image":273},"\u002Fblog\u002F2025\u002F10\u002Fopen-ai-agent-builder-versus-flowfuse","OpenAI's AgentKit or FlowFuse: Choosing the Right Low-Code App for Your Needs","2025-10-07",[11,263,12],"posts",[62],"Learn how OpenAI's AgentKit and FlowFuse differ in their approach to AI agents, and discover which platform is right for building applications that connect the physical and digital worlds.",{"keywords":267,"excerpt":268},"OpenAI AgentKit, FlowFuse, AI agents, Node-RED, edge computing, IoT, industrial automation, AI Assistant, low-code platform, edge data extraction",{"type":19,"value":269},[270],[22,271,272],{},"AI is moving fast, and with it, the tools we use to build intelligent applications.\nTwo interesting platforms that have emerged are OpenAI's AgentKit and FlowFuse.\nWhile both offer AI capabilities, they are designed for very different purposes.\nLet's break down the key differences to help you decide which platform is the\nright fit for your needs.","\u002Fblog\u002F2025\u002F10\u002Fimages\u002Fopen-ai-agent-builder-versus-flowfuse.png",{"path":275,"title":276,"date":277,"tags":278,"authors":279,"description":280,"meta":281,"image":288},"\u002Fblog\u002F2025\u002F09\u002Fai-assistant-flowfuse-tables","Query Your Database with Natural Language Using FlowFuse Expert","2025-09-18",[11,12],[14],"Learn the easiest way to connect to your database and get data, no coding knowledge required.",{"keywords":282,"excerpt":283},"FlowFuse Tables, SQL natural language, database queries, Query node, Node-RED, sensor data, temperature monitoring, industrial automation, low-code platform, data analysis",{"type":19,"value":284},[285],[22,286,287],{},"Getting data from your database used to mean writing SQL queries. Not anymore. The FlowFuse Expert now lets you ask for what you want in plain English and automatically generates the SQL for you in query node.","\u002Fblog\u002F2025\u002F09\u002Fimages\u002Fflowfuse-assistant-query-node.png",{"path":290,"title":291,"date":292,"tags":293,"authors":294,"description":295,"meta":296,"image":302},"\u002Fblog\u002F2025\u002F08\u002Fflowfuse-release-2-21","FlowFuse 2.21: AI-Assisted SQL, Low-Code Custom Nodes, and Remote Instance Performance Insights","2025-08-28",[11,31,32,12],[163],"Introducing FlowFuse Expert functionality in Tables to do natural language queries of your databases, Remote Instance observability to improve performance monitoring, Team Broker nodes to make MQTT even easier to work with, a new Energy Monitoring Blueprint, Annual Billing for Self-Service, AI-Generated Snapshot Summaries, and new subflow version control to provide low-code development of custom nodes",{"excerpt":297},{"type":19,"value":298},[299],[22,300,301],{},"It's been a very busy release and we have many great new features available on FlowFuse that will provide a better Node-RED development experience, makes it easier to develop and interface with your Unified Namespace, provide more insight into Remote Instance performance and new low-code tooling for building your own custom Node-RED nodes.","\u002Fblog\u002F2025\u002F08\u002Fimages\u002Frelease-2.21.png",{"path":304,"title":305,"date":306,"tags":307,"authors":308,"description":309,"meta":310,"image":316},"\u002Fblog\u002F2025\u002F07\u002Fflowfuse-release-2-20","FlowFuse 2.20: AI-Assisted Node-RED & New Database Service","2025-07-31",[11,31,32,12],[163],"Introducing FlowFuse Tables for data storage, Tables nodes for dashboard visualization, Smart Suggestions in the Node-RED editor, More Powerful Starter tier, Retrieval Augmented Generation Blueprint for intelligent applications, and a redesigned Applications page for better workspace management.",{"excerpt":311},{"type":19,"value":312},[313],[22,314,315],{},"This release represents a major leap forward in FlowFuse's data management and AI capabilities, introducing our new FlowFuse Tables database feature, along with enhanced AI assistance features and a streamlined user interface. These improvements make FlowFuse a complete solution for building industrial applications, even while reducing development time.","\u002Fblog\u002F2025\u002F07\u002Fimages\u002Frelease-2-20.png",{"path":318,"title":319,"date":320,"tags":321,"authors":322,"description":323,"meta":324,"image":330},"\u002Fblog\u002F2025\u002F06\u002Fflowfuse-release-2-18","FlowFuse 2.18: Smarter Monitoring, AI Integration, Improved DevOps, and a preview of exciting things to come","2025-06-05",[11,31,32,12],[163],"Monitor and improve instance performance, run AI chat in your Dashboard, Git pull, and more.",{"excerpt":325},{"type":19,"value":326},[327],[22,328,329],{},"This release is focused on improvements that help you manage and optimize the performance of your Node-RED instances and takes an important step in integrating AI with FlowFuse so that you can build applications even more quickly.","\u002Fblog\u002F2025\u002F06\u002Fimages\u002Frelease-2-18.png",{"path":332,"title":333,"date":334,"tags":335,"authors":337,"description":338,"meta":339,"image":352},"\u002Fblog\u002F2024\u002F07\u002Fevolution-of-technology-impact-on-job-roles-and-companies","Evolution of Technology: Impact on Job Roles and Companies","2024-07-23",[263,11,336,12],"low-code",[14],"Discover how technology evolution, from historical disruptions to AI and low-code tools like Node-RED, reshapes job roles and enhances business operations",{"excerpt":340},{"type":19,"value":341},[342],[22,343,344,345],{},"Throughout history, technology has continuously transformed industries, job roles, and entire companies. While these changes often evoke fear and resistance, they also create new jobs, opportunities for innovation and growth. This post will explore how historical technological advancements have reshaped both individual job roles and entire companies, examine current trends like AI and low-code tools, and discuss the critical importance of adaptability for both individuals and businesses in navigating technological disruption, Importantly, we will address the pressing question of our time: ",[346,347,348],"em",{},[349,350,351],"strong",{},"\"How can AI and low-code tools both enhance and challenge human capabilities, creativity, and the job market, and is this the next frontier in manufacturing or just hype\"","\u002Fblog\u002F2024\u002F07\u002Fimages\u002Fevolution-of-technology.png",{"path":354,"title":355,"date":356,"tags":357,"authors":363,"description":365,"meta":366,"image":385},"\u002Fblog\u002F2024\u002F07\u002Fflowfuse-2-6-release","FlowFuse 2.6: AI Infused Node-RED, Persistent File Storage & Lots More","2024-07-04",[263,11,32,358,359,12,360,361,362],"storage","editor","assistant","blueprint","Node-RED",[364],"joe-pavitt","Discover the new features in FlowFuse 2.6, and it's focus on improving the Node-RED development experience.",{"excerpt":367},{"type":19,"value":368},[369],[22,370,371,372,376,377,380,381,384],{},"FlowFuse 2.6 is packed with great new features, and in this release we've had a heavy focus on improving the development experience of Node-RED, lowering the barrier to entry for new users and aligning to our ",[247,373,375],{"href":374},"\u002Fhandbook\u002Fengineering\u002Fproduct\u002F","Simplified Hosting"," and ",[247,378,379],{"href":374},"Low-Code"," plans from our ",[247,382,383],{"href":374},"Product Strategy",".","\u002Fblog\u002F2024\u002F07\u002Fimages\u002Frelease-2-6-july-2024.png",{"path":387,"title":388,"date":389,"tags":390,"authors":391,"description":393,"meta":394,"image":420},"\u002Fblog\u002F2024\u002F01\u002Frevolutionizing-manufacturing-impact-ai-chatgpt-technologies","AI and ChatGPT - Revolutionizing the Manufacturing Industry","2024-01-31",[263,11,12],[392],"flowfuseteam","Explore how AI and ChatGPT revolutionize manufacturing with boosted efficiency, quality control, and workforce transformation.",{"excerpt":395},{"type":19,"value":396},[397],[22,398,399,400,404,405,409,410,414,415,419],{},"The application of artificial intelligence (AI) in various industries, particularly in manufacturing, is a topic of growing interest. The evolution of technologies like ChatGPT is driving significant changes in this sector. For a more nuanced understanding, we reference four informative blog posts from our team members. The first post, ",[247,401,403],{"href":402},"\u002Fblog\u002F2023\u002F12\u002Fai-use-cases\u002F","\"AI Use Cases that are shaping the next manufacturing frontier\"",", offers an insightful overview of AI's role in diverse areas. Following this, ",[247,406,408],{"href":407},"\u002Fblog\u002F2023\u002F11\u002Fai-assistant\u002F","\"ChatGPT AI Assistants with Node-RED\""," examines the specific impact of AI assistants. The third article, ",[247,411,413],{"href":412},"\u002Fblog\u002F2023\u002F11\u002Fchatgpt-gpt\u002F","\"Node-RED Builder a ChatGPT GPT\"",", discusses the capabilities of generative pre-trained transformers like ChatGPT. Lastly, ",[247,416,418],{"href":417},"\u002Fblog\u002F2023\u002F09\u002Fchatgpt-for-node-red-developers\u002F","\"How ChatGPT improves Node-RED Developer Experience\""," explores ChatGPT's application in Node-RED development, an important aspect for many in manufacturing.","\u002Fblog\u002F2024\u002F01\u002Fimages\u002FFuturistic factory with robots.png",{"path":422,"title":423,"date":424,"tags":425,"authors":428,"description":429,"meta":430,"image":439},"\u002Fblog\u002F2024\u002F01\u002Fspeech-driven-chatbot-with-node-red","Speech-Driven Chatbot System with Node-RED","2024-01-29",[263,176,426,427,12],"dashboard","virtual assistant",[14],"Learn to build a speech-driven chatbot system with Node-RED and Dashboard 2.0. Integrate speech recognition, synthesis, and Chat-GPT seamlessly.",{"excerpt":431},{"type":19,"value":432},[433,436],[22,434,435],{},"Have you ever wanted to integrate speech recognition and synthesis into your Node-RED project and thought it was too complex? Often it has required external services or APIs. However, in this guide, we show you how you can use speech recognition and synthesis in your Node-RED projects without needing an external service or API.",[22,437,438],{},"In addition, we make things more interesting by building a system that can listen to us and respond like humans using the Chat-GPT API.\nLet's get started!","\u002Fblog\u002F2024\u002F01\u002Fimages\u002Fspeech-driven-chatbot-system.gif",{"path":441,"title":442,"date":443,"tags":444,"authors":446,"description":447,"meta":448,"image":454},"\u002Fblog\u002F2024\u002F01\u002Fsentiment-analysis-with-node-red","Sentiment Analysis with Node-RED","2024-01-23",[263,176,426,445,12],"sentiment analysis",[14],"Learn how to build a sentiment analysis system with Node-RED using Dashboard 2.0. Extract insights from text content effortlessly with step-by-step guidance.",{"excerpt":449},{"type":19,"value":450},[451],[22,452,453],{},"Have you ever built a sentiment analysis system to extract insights from text content? If yes then I don’t think you'll need an explanation of how complex it is to build. In this guide, we will build a sentiment analysis system with Node-RED using Dashboard 2.0 in a few easy steps.","\u002Fblog\u002F2024\u002F01\u002Fimages\u002Fsentiment-analysis-dashboard-gif.gif",{"path":456,"title":457,"date":458,"tags":459,"authors":460,"description":462,"meta":463,"image":469},"\u002Fblog\u002F2023\u002F12\u002Fai-use-cases","Beyond Automation - AI Use Cases that are shaping the next manufacturing frontier","2023-12-04",[263,12],[461],"marian-demme","Discover how AI is revolutionizing manufacturing with citizen development, demand forecasting, and predictive maintenance",{"excerpt":464},{"type":19,"value":465},[466],[22,467,468],{},"Are we standing on the brink of a Fifth Industrial Revolution? The manufacturing industry has been in a state of flux for some time, with the rise of automation and digital transforming the way factories operate. But today, we are witnessing something even more profound: AI is pushing manufacturing to a whole new level. Some have even referred to it as “the fifth industrial revolution” due to its potential for disruption.","\u002Fblog\u002F2023\u002F12\u002Fimages\u002Fbeyond-automation.png",{"path":471,"title":472,"date":473,"tags":474,"authors":477,"description":479,"meta":480,"image":494},"\u002Fblog\u002F2023\u002F11\u002Fai-assistant","Integrate with ChatGPT Assistants with Node-RED","2023-11-21",[263,176,475,11,476,12],"community","openai",[478],"grey-dziuba","Discover how seamlessly integrating AI Assistants into Node-RED workflows enhances efficiency and innovation across industries.",{"excerpt":481},{"type":19,"value":482},[483,488,491],[484,485,487],"h2",{"id":486},"introduction-to-the-world-of-gpts-and-ai-assistants","Introduction to the World of GPTs and AI Assistants",[22,489,490],{},"In the ever-evolving landscape of artificial intelligence, Generative Pre-trained Transformers (GPTs) have emerged as groundbreaking tools. These advanced AI models, developed by OpenAI, are capable of understanding and generating human-like text, offering vast possibilities across numerous applications. GPTs learn from various internet texts, enabling them to respond to queries with human-like understanding.",[22,492,493],{},"Among the most intriguing developments in this field are AI Assistants. These are specialized applications of GPTs, accessible through an API, designed to enhance and streamline various tasks. Tasks that include code interpreter, functions, retrieval, and leveraging uploading files to interact with. Unlike traditional GPTs, which primarily focus on generating text, AI Assistants can interact, comprehend, and assist in real-time, making them invaluable in industries ranging from manufacturing to finance to healthcare.","\u002Fblog\u002F2023\u002F11\u002Fimages\u002Fai-assistant.png",{"path":496,"title":497,"date":498,"tags":499,"authors":501,"description":502,"meta":503,"image":509},"\u002Fblog\u002F2023\u002F11\u002Fchatgpt-gpt","Node-RED Builder a GPT (Alpha) by FlowFuse","2023-11-15",[263,176,475,11,500,12],"chatgpt",[478],"Accelerate Node-RED flow creation with Node-RED Builder by FlowFuse. Streamline development effortlessly with preconfigured prompts and latest Node-RED insights.",{"excerpt":504},{"type":19,"value":505},[506],[22,507,508],{},"When ChatGPT was first released, my expectations were quite low. I had grown accustomed to the usual industry buzz for AI and ML that often led to underwhelming solutions. Naturally, I approached ChatGPT with similar reservations. It wasn't until a few months after its announcement that I decided to give it a try. To my surprise, within just 10 minutes, I found myself so captivated that I decided to purchase the pro version.","\u002Fblog\u002F2023\u002F11\u002Fimages\u002Fchatgpt-GPT.png",{"path":511,"title":512,"date":513,"tags":514,"authors":515,"description":516,"meta":517,"image":523},"\u002Fblog\u002F2023\u002F09\u002Fchatgpt-for-node-red-developers","How ChatGPT improves Node-RED Developer Experience","2023-09-23",[263,176,500,12],[62],"Discover how ChatGPT enhances Node-RED development, from generating code to interpreting flows, and explore its impact on the community.",{"excerpt":518},{"type":19,"value":519},[520],[22,521,522],{},"ChatGPT has the potential to have a significant impact on the Node-RED community. It is a powerful language model that can be used to generate flows, interpret them, and provide documentation, maybe soon even write the flow! The combination of ChatGPT, or generative AI at large, with Node-RED can significantly improve the developer experience with Node-RED. In this post we’ll review what the community has already built.","\u002Fblog\u002F2023\u002F09\u002Fimages\u002Fchatgpt-node-red-dx-tile.png",{"path":525,"title":526,"date":527,"tags":528,"authors":530,"description":531,"meta":532,"image":553},"\u002Fblog\u002F2023\u002F05\u002Fchatgpt-nodered-fcn-node","Chat GPT in Node-RED Function Nodes","2023-05-02",[263,176,475,529,500,12],"how-to",[364,222],"Discover how ChatGPT integrates with Node-RED function nodes, enabling automated code generation. Explore the prompt engineering process and additional features.",{"excerpt":533},{"type":19,"value":534},[535],[22,536,537,538,543,544,549,550,384],{},"Recently we ",[247,539,542],{"href":540,"rel":541},"https:\u002F\u002Fwww.linkedin.com\u002Fposts\u002Fflowforge_chatgpt-with-node-red-function-nodes-activity-7052725869684953088-2yOA?utm_source=share&utm_medium=member_desktop",[251],"posted a demo of ChatGPT integration in a Node-RED function node","\nonto our social media accounts. We have now ",[247,545,548],{"href":546,"target":547},"https:\u002F\u002Fgithub.com\u002FFlowFuse\u002Fnode-red-function-gpt","_blank","open-sourced"," this for all to play with, and ",[349,551,552],{},"welcome any and all contributions","\u002Fimages\u002Fblog\u002Ftile-chatgpt-fcn-node.jpg",1785868279963]