516: AI's agentic future is here. GitHub Copilot CLI and Fabric integration showcase its power. A true leader in agentic AI. #AI #AgenticAI #GitHubCopilot #TechInnovation

⚠️ 80% of AI projects fail between Stage 2 and Stage 4. Not because AI is hard. Because the foundations weren't right. Save this. Share it with your AI team. 📌 #AI #MLOps #DataEngineering #GenerativeAI #EnterpriseAI #CodesmoTech

⚠️ 80% of AI projects fail between Stage 2 and Stage 4. Not because AI is hard. Because the foundations weren't right. Save this. Share it with your AI team. 📌 #AI #MLOps #DataEngineering #GenerativeAI #EnterpriseAI #CodesmoTech

Built something exciting — Finora AI 💡 An AI-driven solution that transforms complex financial data into simple, meaningful insights. From handling raw PDFs to extracting key information, this project pushed me to explore real-world AI applications beyond theory. Still improving. Still learning. 🚀 #AI #RAG #LLM #Innovation #JrAIDeveloper #DCI

Talvi - the new kid on the block at Learning Technologies AI-native: built from scratch with AI as the foundation. Every decision about how content is ingested, chunked, vectorised, indexed and retrieved was made knowing exactly how modern AI works. This is not AI bolted onto a legacy product. This is what the next era of L&D technology looks like. Built in 2025. Come and see it working. Stand B65, ExCeL London, 29-30 April. talvi.ai | learningtechnologies.co.uk #LT26 #LT26UK #AI #LearningTechnology #LandD

Just published a new piece on how Anthropic’s Claude evolved from “the safer alternative” into arguably the AI agent platform to beat. I break down: • why Claude gained traction with power users and developers • how long-context workflows changed the game • the rise of AI agents and automation ecosystems • where OpenAI, Google, and Anthropic are diverging strategically • why the next AI battle may be less about chatbots — and more about autonomous systems This wasn’t written as hype. It’s a look at the competitive and structural shifts happening inside the AI industry right now. Read here: https://lnkd.in/eEN3gSpJ #AI #ArtificialIntelligence #Claude #Anthropic #AIAgents #MachineLearning #TechStrategy #GenerativeAI

🤖 Everyone talks about AI detection and classification. But strip away the buzzwords… and you end up learning something much simpler — and quite powerful. Today, watching a video about battlefield AI, I stumbled on this Swift pattern: That line 👇 case let s where s.contains(...) Almost reads like a rule engine. No dataset. No model. Just observe → match → classify. Of course, real AI scales this with probabilities and massive data. But the foundation? It starts with thinking like this. #Swift #LearningByBuilding #SystemsThinking #AI

Exploring the Anote product's unique approach to AI. The video delves into its human-centered AI philosophy, the structure of its MLOps platform, and the crucial definitions of datasets and metrics. It highlights the processes for model evaluation and customization, showcasing a comprehensive system designed for effective AI development. This provides valuable insight into building and refining AI solutions. #AI #MLOps #DataScience #ArtificialIntelligence #ProductOverview

Everyone talks about AI models. Nobody talks about what makes them actually work. #AI #MachineLearning #DataAnnotation #ComputerVision #MLOps #DataQuality #AIInfrastructure #BuildInPublic #DataScience #VideoAnnotation #AIEngineering #LessonsLearned #VisionRD #VisionRDResearch

AI is great, but its memory retrieval systems are often broken, leading to nonsense answers. Traditional Retrieval-Augmented Generation (RAG) relies on vector search, which basically shreds document structure and loses crucial context, acting more like a simple keyword search. A new open-source tool called EdgeQuake fixes this by turning flat documents into an intelligent, interconnected knowledge graph. Written in Rust, this high-performance GraphRAG framework delivers massive improvements: Blazing Fast: Query latency is 5 times faster, responding in under 200 milliseconds. Deeper Understanding: It maps out relationships to find 3 times more key concepts than traditional RAG. Vision Pipeline: It can actually "see" and extract data from complex multi-column PDFs and scanned documents. We are moving from simple AI information lookup to genuine AI reasoning. What complex data would you want to analyze with an AI that actually understands context? Let me know below! 👇 #EdgeQuake #GraphRAG #AI #Rust #TechTrends https://lnkd.in/gByA9bAF