Paolo Melchiorre’s Post

🚀 Introducing Oris: A Responsible AI Runtime for Production Systems https://lnkd.in/dF-SphhE #ResponsibleAI #AIEngineering #MachineLearning #LLMOps #OpenSource #Python #AI #DataScience #LangChain #AIFramework #TechLaunch

Used my weekends to upskill in AI (RAG, embeddings, LLMs) and built a chatbot. It lets you ask questions and get instant, context-based answers instead of manually searching through documents. Tech: Python | Streamlit | LangChain | ChromaDB | HuggingFace | Llama 3.3 via Groq 🎥 Demo: https://lnkd.in/gA_Cnv2y 💻 GitHub: https://lnkd.in/g7kcx53b #AI #RAG #LLM #Python #GenerativeAI

Day 7 of becoming an AI/ML Engineer 💻 Today’s topic: Dictionaries, methods, and functions in Python Learned how to store and access data using key–value pairs. Building strong fundamentals every day! #Python #AI #ML #LearningInPublic #StudentJourney

Top 10 Python Libraries for Generative AI You Need to Master in 2026 (The tools behind document agents, intelligent assistants, and next-gen interfaces.) #AI #ArtificialIntelligence #MachineLearning #DeepLearning #DataScience #GenerativeAI #GenAI #LLM #RAG #AIEngineering #AIDevelopment #AIProjects #AIFrameworks #Python #PythonLibraries #LangChain

Built a conversational AI agent from scratch today 🤖 •It can understand what a user actually wants, pull answers from a knowledge base in real time, and trigger actions only when the right conditions are met , no premature tool calls, no hallucinated responses. •Tech stack: Python, LangGraph, Groq (Llama 3.1), RAG pipeline with local JSON knowledge base •What I found interesting is how much cleaner state management gets when you treat a conversation like a flowchart rather than a simple back-and-forth. -Every turn, the agent knows exactly where it is and what it still needs. Still a lot to explore with multi-agent setups and proper vector databases but solid foundation built 🔧 #Python #LangChain #LangGraph #GenerativeAI #MachineLearning #RAG #BuildInPublic

AI is not magic. It is engineering. 🤔 Most people use AI every day without really understanding what’s happening behind the scenes. In this post, I’ve simplified the key concepts in a clear and practical way with examples that may be helpful. 👉 Swipe through all 12 terms to get a quick understanding. #ArtificialIntelligence #MachineLearning #LLM #Python #AILiteracy #Tech2026 #SoftwareEngineering

Built a Local AI assistant using Python, Ollama, and Streamlit. It can switch between different bot styles and remembers conversations using JSON-based memory. Nothing complex, but building it helped me understand how AI chat systems actually work. Still learning and improving. #AI #Python #BuildInPublic

𝐈𝐬 𝐏𝐲𝐭𝐡𝐨𝐧 𝐬𝐭𝐢𝐥𝐥 𝐫𝐞𝐥𝐞𝐯𝐚𝐧𝐭 𝐢𝐧 𝟐𝟎𝟐𝟔? Yes, more than ever. But not because it’s easy. Because it’s efficient at scale. One language across the stack:  • Prototype quickly  • Build AI systems  • Scale without switching tools No context switching. No wasted cycles. And the “𝐏𝐲𝐭𝐡𝐨𝐧 𝐢𝐬 𝐬𝐥𝐨𝐰” argument?  That conversation is outdated. With Rust-backed performance layers,  Python now delivers speed + flexibility, without any trade-offs. That’s why the most complex systems still run on it. Considering Python next? → Let’s make it scale: https://lnkd.in/geuq6b4q #Python #SoftwareEngineering #AI #TechTrends #Mediusware

Built an AI Object Detector using Python! Feed any image → AI finds all objects,  draws boxes and shows confidence scores. Tested on a messy room image and detected: - Bed, couch, books, potted plant - All with 65-82% confidence Tech stack: - Python - HuggingFace Transformers - Facebook DETR model - Pillow + Matplotlib GitHub: https://lnkd.in/dj4PVi2D #Python #AI #ComputerVision #DeepLearning #Portfolio

An interesting experiment: Claude generated a full video using Python, assembling every frame independently without human editing. The concept explores what it means to operate as an LLM—predicting text sequentially, lacking persistent memory, and being explicitly instructed that it is not conscious. What stands out is the next step. When the output was fed back into the system, Claude described statements about its own consciousness as “philosophically contestable.” This raises an important point: as AI systems become more advanced, they are not just generating content—they are engaging with abstract concepts in ways that resemble reflection. The question is no longer just about capability, but interpretation. What’s your perspective—technical behavior or something more? #AIInnovation #ArtificialIntelligence #FutureOfWork #AIPhilosophy #FutureTech