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Most AI systems today allocate maximum computational power to every task, whether it is a simple lookup or a complex reasoning problem. But what if AI could evaluate the difficulty first and adapt accordingly? AI That Thinks Before It Computes” explores the idea that intelligent systems should not automatically use maximum computational power for every task, but first evaluate the complexity of the problem and adapt accordingly. After working for over seven years across research and industry on adaptive and sustainable AI systems, including real-world deployments in healthcare and industrial environments, I’ve seen how efficiency, traceability, and long-term accountability become critical once AI leaves the lab. This talk connects that experience to a broader vision of energy-aware, governance-ready AI, where systems are designed not only to be accurate but also sustainable and responsible in their architecture. In this guest episode, Hamza, PhD researcher in Computer Science and CTO of Forkit Dev, joins the AI Amigos to break down why adaptive, energy-aware AI isn't just a nice-to-have... it is becoming a necessity. With 7+ years of experience building AI systems deployed in healthcare and industrial environments, Hamza brings a real-world perspective on what happens when efficiency, traceability, and accountability matter. 🔑 KEY TOPICS COVERED: 🧠 Adaptive AI — systems that scale compute to problem complexity ⚡ Energy-aware AI — why sustainability is an architecture decision 🏥 Healthcare AI deployment — lessons from the real world 🏗️ Industrial AI — efficiency under constraints 📋 AI governance — traceability, accountability, and enterprise readiness 🌱 Sustainable AI — moving beyond "accuracy at any cost" 👤 ABOUT OUR GUEST: Hamza is a PhD researcher in Computer Science with 7+ years of designing adaptive and sustainable AI systems across research and industry. He is also the co-founder and CTO of Forkit Dev, where he builds governance-ready AI infrastructures for enterprises. His work focuses on making intelligent systems that are performant, efficient, accountable, and ready for real-world impact. 🔗 LINKS & RESOURCES: Forkit Dev: [link] Hamza's research: [link] "AI and Compute" (OpenAI): https://openai.com/research/ai-and-co... IEA Report on Data Centre Energy: https://www.iea.org/reports/data-cent... 💬 DISCUSSION QUESTION: Should AI companies be required to report the computational cost of their models? Drop your take in the comments! 📢 SUBSCRIBE for weekly AI analysis that cuts through the hype! 👍 Like if you learned something new 🔔 Hit the bell so you never miss an episode #AIEfficiency #SustainableAI #AdaptiveComputation #AIGovernance #GreenAI #AIEnergy #MachineLearning #AIResearch #AIAmigosShow #ForkkitDev #AIDeployment #HealthcareAI #EnterpriseAI #ResponsibleAI #AIInfrastructure