Dad of Bo & Mila & Husband. MSc Computer Science, Data scientist and Machine learning engineer

België
Joined November 2011
Kristof Slechten retweeted
Andrew Ng just dropped the best 2-hour course on Graph Engineering: from single agent to full automation 9:14 - your first agent 33:11 - loop engineering 1:02:46 - graph engineering 1:30:15 - agents that rewrite themselves 1:49:05 - full graph system two hours, and it replaces every agent tutorial you bookmarked this year Prompts → Agents → Loops → Graphs most people will stop after the first agent and call it automation he saves the last forty minutes for the graph that runs it without him same model, same tokens, completely different week watch it today the step-by-step guide is below, save it while it is still early ↓
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Kristof Slechten retweeted
Andrej Karpathy just explained the 5 shifts turning LLMs into agentic systems. 00:00 - Memory turns chat into personal AI 06:41 - Multimodal AI reads the world 16:58 - Thinking models solve harder tasks 24:51 - Search makes LLMs live 30:58 - Tools turn LLMs into workers Most people are still treating LLMs like chatbots. Karpathy is showing the full stack: Memory → Vision → Reasoning → Search → Tools Prompting is the old workflow. Agentic systems are the new one. This 40-minute talk is worth more than most paid AI agent courses. Bookmark and watch it before everyone catches up. Then read how to turn LLMs into self-improving agent loops below
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Kristof Slechten retweeted
Google Deepmind argues that LLMs can never make real scientific discoveries. They published a paper breaking down Albert Einstein’s private view of scientific discovery. In a famous letter to his friend Maurice Solovine, Einstein drew a diagram of how science actually happens. It is a cyclical loop. First, you experience raw sensory data. Then, through a mysterious, non-logical act of intuition, you make an intuitive "jump" to abstract axioms. Finally, you use strict logical deduction to derive consequences from those axioms. Generative AI has completely mastered two-thirds of this loop. • Induction: Statistical pattern matching across billions of tokens. • Deduction: Formal proof generation, like AlphaProof solving complex math Olympiads. AI can crunch data and it can prove theorems. But it cannot make the jump. The paper argues that AI completely lacks Abduction, the generation of novel explanatory hypotheses when observational data is scarce. The prevailing tech myth says that "creativity is just data compression." That if you feed an LLM enough text, scientific breakthroughs will naturally pop out. Einstein’s formulation of General Relativity proves that is a delusion. When Einstein formulated relativity, the observational data didn't demand a new physics framework; classical mechanics was still massively successful. The breakthrough required a conceptual rupture. An intuitive leap from physical reality to a brand-new set of foundational axioms. An LLM can execute the math once the axioms are given. But it is structurally incapable of formulating those premises on its own. It can interpolate inside existing human thought, but it cannot transcend it. The translation of physical reality into formal axioms remains the absolute, hard bottleneck of artificial scientific invention. We can build models with trillions of parameters. We can scale compute into the stratosphere. We can make the calculator infinitely fast. But until we solve grounding, the machine can process all the data in the universe. It still can't make the jump.
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Kristof Slechten retweeted
Andrew Ng: “AI agents are doing almost 100% of my tasks now - the hype has exceeded my expectations. in 4-6 months, we’ll all be building graphs to orchestrate self-improving agents. No more prompting.” In a 20-minute talk, Andrew Ng explains how to build self-improving agentic systems from scratch. Worth more than a $500 agentic course. Watch this video, then read the article below on how to become a graph architect.
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Kristof Slechten retweeted
Don't just prompt Claude. Build a system that can prompt itself. In this 45-minute session, she explains how Anthropic builds AI agents that can remember past work, learn from mistakes, and improve with every run.Ione of the best free resources for learning how AI agents work.
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Kristof Slechten retweeted
Andrej Karpathy just challenged one of the biggest assumptions in AI. Most people think better agents come from bigger models. He argues the opposite. In 16 minutes, he explains why small models, the right tools, and closed feedback loops are where real capability comes from. Watch it. Bookmark it.
Brands are quietly replacing ad shoots with this. One product photo in. A complete storytelling ad out. Vivago AI turns a single image into a full video campaign with scenes, motion, pacing, and narrative built in. The workflow is ridiculous: → Go to vivagoai.go.link/hHbzx → Click Skill → Select Story Ad Director → Upload your product photo → Type a simple prompt → Hit generate No actors. No cameras. No editing software. No complicated prompts. Just a product and an idea. This feels less like an AI tool and more like hiring a creative team on demand. Try it here: vivagoai.go.link/hHbzx
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