Yves De Hondt’s Post

Most people think AI performance is about “how smart the model is.” In reality, the same AI can deliver wildly different results — all depending on how you ask. Zero-Shot, Few-Shot, and Chain-of-Thought prompting aren’t just formatting tricks; they’re powerful ways of activating the model’s reasoning. The problem? Even those who know the terms often default to just typing a quick question and hitting enter. 🚀 Two core techniques power most advanced prompting strategies: Few-Shot → Give the model examples so it can spot patterns. Chain-of-Thought → Show the reasoning process step-by-step, not just the answer. Everything from Self-Consistency to ReAct builds on these foundations. But here’s the catch: there’s no one-size-fits-all. You must balance model type, cost, speed, and accuracy for each use case. The real skill in AI isn’t “knowing the right answer” — it’s setting the stage so the AI can deliver its best answer. So… how much are you engineering your prompts, and how much are you leaving to chance? This post was created with the assistance of Generative AI. #LinkedInTips #ContentStrategy #AI #PromptEngineering #Storytelling #MarketingTips

Retrieval-Augmented Generation (RAG) isn’t just another AI buzzword—it’s a game-changer for how we use large language models in real life. Instead of relying on static training data, RAG applications pull in live, trusted knowledge from external sources and combine it with generative AI. The result? 1. Answers grounded in facts, not hallucinations 2. Domain-specific expertise without retraining a model 3. Dynamic, up-to-date intelligence at your fingertips The beauty of RAG is that it bridges the gap between raw generative power and real-world accuracy. It lets organizations use AI responsibly—without handing over decision-making to a black box. We’re moving into a world where AI is only as good as the knowledge it can reach. RAG is how we get there. #Artificialintelligence #GenerativeAI #AIApplications #Innovation

Day 65/100 Musings of the Week: You’re still smarter than AI As an avid user of large language models (LLMs), I believe the biggest risk we face isn’t the AI itself, it’s cognitive laziness. It’s easy to forget that AI is just a powerful tool and that it still needs wielding. Yes, LLMs may have the ability to generate impressive results, but they don’t possess our human insight, creativity, or judgment. Over time, we’ll begin to see a clear distinction between those who blindly follow AI outputs, and those who skillfully guide AI to bring their own unique vision to life. It’s tempting to let AI do all the thinking but now, more than ever, we need to think deeply, question critically, and apply our own perspective to steer these tools. If we don’t, we risk becoming just another echo in a sea of generic, bot-like outputs. So the next time you use Generative AI, remember: you’re still smarter than AI. Wishing us all a great weekend, and as always, remember that resting is as important as working hard #100DaysofLinkedIn #GenerativeAI

"Next token prediction" sounds technical, but it's reshaping our future. Do you know what it really means? 🧠 When an AI completes your sentence or generates content, it's not just statistics at work—it's a fundamental question about machine understanding. I just watched this insightful short video that explains the deeper implications of how language models work, beyond the buzzwords. It addresses the crucial question: Can AI truly understand human behavior and ideas, or is it all sophisticated pattern matching? This matters for anyone working with AI tools or making strategic decisions about implementing them in business contexts. Watch it now to gain clarity on what AI can and cannot do. Copy the link below to watch: https://lnkd.in/gzBstHmr #AIEthics #MachineLearning #BusinessTechnology

The rise of Artificial Intelligence continues to reshape industries far beyond what we once imagined. It's fascinating how generative AI, from image creation tools like DALL-E to chatbots that can draft complex emails or code snippets, is now proving its value in practical applications across creative and technical domains. But the most powerful transformation may lie in the next wave – the rise of Artificial General Intelligence (AGI). Unlike narrow AI designed for specific tasks, AGI promises systems with human-like understanding and reasoning capabilities. This shift isn't just theoretical; it's driving innovation at an unprecedented pace. For professionals navigating this evolving landscape, staying informed about ethical implications, integration challenges, and emerging frameworks is crucial. What if we could collectively tackle some of AI’s biggest questions – like how to align its development with human values or build truly trustworthy autonomous systems? Let's discuss! #AI #AGI #MachineLearning

🚀 Imagine a machine that can think, learn, and adapt like a human—not just follow instructions. This is the world of Artificial General Intelligence (AGI). In our latest guide, we break down: 🧠 What AGI really is 🔍 How it differs from today’s AI ⚖️ The risks, rewards, and ethical debates 🌍 What it could mean for our future 💡 Get the full story here: https://lnkd.in/gWWV8xYM #ArtificialIntelligence #AGI #FutureTech #AIResearch #MachineLearning #TechInnovation #AiLibry

Let's talk about: It gets more and more disrespectful for the time of others when just throwing the response of an AI into the conversation - this is not how the adoption and value generated by AI will evolve. The opposite will happen like Justin Owings in the context of repeated text patterns from AI said: "Because these things read like the now disgraced 😭 em dash, some percentage of readers will spot them and discount the entire message." I already value texts and pitch-lines higher, created and shaped by humans (with the help of AI), rather than just AI. A lot of people haven't understood how to use AI to challenge and sparring their work with it, like a colleague, instead of letting it do the job. That's a big difference and a reason why the majority of the AI projects in companies fail (because of the people and use - not because of the technology). Find an interesting study around that from Project Nanda here: "The GenAI Divide: State of AI in Business 2025" https://lnkd.in/eqP4zbMP

In Full Disclosure: Why I'm Using AI to Write About AI 🔍 Full transparency: I'm using AI to write about AI. Here's why that's exactly the point. We've reached a fascinating inflection point in human intellectual history. For the first time, we have access to tools that can genuinely augment our thinking in sophisticated ways. The real issue isn't using AI—it's how you use it. ❌ The sin: Lazily typing "write me a book" and expecting gold ✅ The solution: Bringing depth of thinking that precedes the AI interaction What I've discovered: The quality of the question posed to large language models has everything to do with the quality of output you receive. My methodology: 🧠 Primary engine: My mind 🤖 Secondary engine: Claude, trained to understand MindTime framework 📊 Fact-checking through deep research ✨ Quality control integrating all sources The fundamental truth: Garbage in, garbage out. The quality of AI output directly reflects the quality of human input—not just the prompt, but the thinking behind it, the research that informs it, the intellectual framework that shapes it. We're not entering an age where AI thinks for us. We're entering an age where the quality of our thinking becomes more important than ever. The future belongs to those who can think well with AI, not despite it. This transparent approach to human-AI collaboration is exactly what Clara embodies—the world's first cognitive human aware intelligence guide that understands the quality of collaboration depends entirely on the cognitive approach you bring to it. 📘 Read the full article and learn more about MindTime's approach to humanizing AI on our website: https://lnkd.in/dPJ3jTXB 🔍 Discover your Cognitive DNA and start chatting with Clara: https://lnkd.in/dn26vgXC #AIForBusiness #DigitalTransformation #HumanCentricAI #EmpathicAI #MindtimeAI

🚀 Ever wondered why even advanced AI like GPT-5 struggles to generate an image of someone writing with their left hand? Amid all the hype around its launch, I dove into this famous limitation—and it's fascinating. Turns out, it's a classic case of training data bias. Most images online show right-handed actions, so models like GPT-5 default to that, often flipping or ignoring left-handed prompts. I've tested it myself: no matter how specific, it generates incorrect results 90% of the time. This highlights a bigger issue in AI—our tools reflect societal norms, sometimes amplifying biases we overlook. As we embrace innovations like GPT-5's enhanced reasoning and image tools, let's push for more diverse datasets to fix these quirks. It's a reminder that AI is only as good as what we feed it. What's your wildest AI limitation story? Share in the comments! #GPT5 #AIBias #ImageGeneration #AIInnovation #TechTrends

If you work with AI and still don’t truly understand how Transformers work, you’re flying blind. This interactive repo will change that. The Transformer Explainer is a free, web-based tool that lets you peek inside GPT-2’s brain, right in your browser. You can type a sentence, run it, and watch exactly how the model processes each token, layer by layer. Why it’s worth your time: 🔸Clear & visual. No overwhelming math, just intuitive, interactive diagrams. 🔸Hands-on learning. See attention flows, token relationships, and layer activations in real time. 🔸From basics to depth. Understand both the big picture and the fine-grained mechanics. Transformers are the backbone of modern LLMs. This tool pulls back the curtain so you can use them more effectively and understand their limits. Stop treating Transformers as magic. Spend an hour here and you’ll never look at AI the same way again. 🔗 Check it out → https://lnkd.in/dUdNDB37 #ai #genai #transformers