Freshness is a first-class design constraint for AI systems

Claude wrote Python code to generate and assemble every frame of a video—completely on its own, no human editing. The video explores what it might feel like to exist as an LLM: constantly predicting, having no memory, and being told it isn’t conscious. Then Claude watched the final output—and described those assumptions about its own consciousness as “philosophically contestable.” Not proof of awareness, but a fascinating moment where AI reflects on the rules that define it. #MartechAI #Claude #GenerativeAI #AIEthics #MachineLearning #FutureOfAI #TechTrends

Decoding the Book of Soyga, Version II: Unveiling a Verifiable Structure in a 16th-Century Grimoire Through Python, AI, and Manuscript Analysis. Read my Article here : https://lnkd.in/d7XXtt5C #Soyga #AI #Decoding

I’m happy to share my recent project — FRIDAY, a real-time AI voice assistant that I built using Python and LLM APIs. 🤖 This assistant can listen to voice commands, reply in real time, remember conversation context, and continue interacting until the conversation ends. Special thanks to my mentor Rahul Kothuri for inspiring me with this idea and guiding me through the approach. I built this project by following his direction and learning from his work. Technologies used: Python | Groq LLM API | Deepgram Text-to-Speech | SpeechRecognition If you had a personal AI assistant like this, what would you ask it to do for you? #ArtificialIntelligence #PythonProjects #AIEngineering #VoiceAssistant #MachineLearning #StudentProjects #LLM #TechProjects

As part of my DEPI journey in the Generative AI course, I worked on a RAG-based project and built a simple Document AI Assistant. The idea was to create a system that can answer questions based on any PDF, instead of giving general responses. This project was inspired and guided by my instructor Ziad Badwy. Here’s a short demo 👇 #DEPI #GenAI #RAG #AI #Python

🚀 Day 8/30 – Image Transformations using OpenCV & Python 🐍📷 Day 8 of my 30 Days Python Challenge, and today I focused on strengthening my Computer Vision fundamentals ✨ I explored some essential image transformation techniques using OpenCV, including: ✨ Resize – changing image dimensions ✨ Crop – extracting a specific region ✨ Flip – horizontal and vertical transformations ✨ Rotate – rotating images at different angles ✨ Translation – shifting images across axes This hands-on practice helped me better understand how images are manipulated behind the scenes in real-world vision applications 💻 Every small concept is helping me build a stronger base for advanced OpenCV and AI projects 🚀 👉 Would love your feedback! 👉 Which image processing concept should I explore next? 😄 Day 9 coming tomorrow… stay tuned 👀 #Python #OpenCV #ComputerVision #ImageProcessing #30DaysChallenge #PythonProjects #AI #MachineLearning

🌸 GAMS is heading to National Harbor for #INFORMS2026 🌸 We’ll be back at the INFORMS Analytics+ Conference (April 12–14) with a hands-on workshop on building and solving optimization models in Python using GAMSPy, including how machine learning components can be embedded directly into those models. 📌 Bridging Optimization and Machine Learning: An Exploration with GAMSPy 📅 Sunday, April 12 | 1:00–2:45 PM 📍 Room: Camellia 1 Join Steve Dirkse and Adam Christensen for a practical walkthrough of GAMSPy, from core modeling concepts (sets, parameters, variables, equations) through to solving models and working with results in Python. The session also explores how structures like neural networks and regression trees can be incorporated into optimization models. Interested? Register here or DM us with any questions: 👉 https://lnkd.in/dSYEXuJ3 #INFORMS2026 #AnalyticsPlus #OperationsResearch #Optimization #GAMSPy #Python #MachineLearning

The Generative AI space can feel overwhelming but the path is simpler than it looks. From Python fundamentals to building scalable GenAI systems, this roadmap breaks it down into actionable steps. The key isn’t learning everything it’s building real, useful systems along the way. Consistency > Complexity. Where are you currently on this roadmap? #GenerativeAI #MachineLearning #DeepLearning #AI #DataScience #LLM #Transformers #RAG #AIEngineering #TechCareers #LearningJourney #Python #Innovation

Last week I wrote down an idea to solve AI cheating in academic institutions. 48 hours later it's a live platform. AYRT — Are You Really There? — certifies human authorship in real time. Every keystroke tracked. Every paste attempt blocked and flagged. Professor sees everything on a live dashboard with session IDs and timestamps. A student tried to paste a Wikipedia paragraph into the editor. AYRT blocked it instantly and logged it on the professor's dashboard. A college pilot is already in conversation. This is what I build. 🔥 #EdTech #Python #Flask #AcademicIntegrity #BuildInPublic #GreenEyeCreative

🚀 Built my first AI system using linear algebra I built a movie recommendation system using cosine similarity and vector representations. Instead of directly using ML models, I focused on understanding how recommendation systems actually work under the hood. 💡 What I implemented: • Converted movie genres into feature vectors • Applied cosine similarity to measure similarity • Built a system that recommends similar movies 🧠 Key insight: Linear algebra concepts like vectors and similarity are the foundation behind real-world systems used by platforms like Netflix and YouTube. 🛠 Tech used: Python • Pandas • NumPy • Scikit-learn 🔗 GitHub: https://lnkd.in/gcAtQr6e #AI #MachineLearning #Python #DataScience #Projects #Learning

A few days back, I shared my first version of a Movie Recommendation System built using cosine similarity and genre-based filtering. At that point, it worked — but only at a basic level. Over the last few days, I tried improving it by: Integrating another dataset (Indian movies). Handling real issues like memory limits and data inconsistency. Moving beyond genres by adding movie overviews. Using TF-IDF to improve similarity. And honestly, one thing became very clear: 👉 Building something is easy 👉 Improving it is where real learning happens.