What is Intelligence?
An examination of cognitive science and computational physics in light of Artificial General Intelligence There’s no shortage of opinions on whether LLMs are intelligent. I’ve spent time studying two perspectives on this question, rooted in separate yet complementary scientific fields. While the combined view appears almost complete, there is a gap between them that points to something I believe is the one of today’s most important unsolved problems on our path towards true intelligence. Two Views: Cognitive Science and Computational Physics The first perspective comes from cognitive science — the psychological view. One of its prominent voices in the AI debate is Gary Marcus , Professor Emeritus at NYU, founder of Geometric Intelligence (acquired by Uber), and author of multiple books on
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How to Embed ChatGPT in Your Website: 5 Methods Compared [2026 Guide]
You want ChatGPT on your website. Maybe for customer support. Maybe to answer FAQs automatically. Or maybe you're running live events and need AI to handle the flood of questions pouring into your chat room. Learning how to embed ChatGPT in your website is simpler than you think - but there's more to consider than most guides tell you. Here's the thing: most guides only cover half the picture. They show you how to add a basic AI chatbot widget. But what happens when 5,000 people hit your site during a product launch? What about moderating AI responses before your chatbot tells a customer something embarrassingly wrong? And what if you need AI assistance in a group chat, not just a 1-to-1 support conversation? To embed ChatGPT in your website, you have two main approaches: use a no-code pla

Why I Run 22 Docker Services at Home
Somewhere in my living room, a 2018 gaming PC is running 22 Docker containers, processing 15,000 emails through a local LLM, and managing the finances of a real business. It was never supposed to do any of this. I run a one-person software consultancy in the Netherlands; web development, 3D printing, and consulting. Last year, I started building an AI system to help me manage it all. Eight specialized agents handling email triage, financial tracking, infrastructure monitoring, and scheduling. Every piece of inference runs locally. No cloud APIs touching my private data. This post covers the hardware, what it actually costs, and what I'd do differently if I started over. The Setup: Three Machines, One Mesh Network The entire system runs on three machines connected via Tailscale mesh VPN: do
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