What's the difference between a hallucination and a bug?
Claude's hallucinations have been cleverly renamed "bugs". These hallucination are acceptable because of the compiler phase. Otherwise, they are just…
Top AI Guru's advice: Learn to speak to an idiot !
An AI guru recently suggested that the youth should learn how to speak to AI as a future proof skill.…
Is Ai the 2026 Musket?
The 16th century musket had a misfire rate of 40%. Soldiers went to war with it anyway. Sound familiar? AI…
AI for ROI
Stop creating "Agents" ! Start building: AI Software Solutions for ROI Here is how it looks like...
I proposed to Claude
If you believe the social media hype, AI is the answer to everything—so I’ve decided to "marry" Claude. While she…
Hungary
The Most Difficult Language in Europe
A short article about Hungarian, considered the most difficult language in Europe.
Sylvain LIÈGE PhD.
December 19, 2024
Hungary
Sylvain LIÈGE PhD.
December 19, 2024
Quote
Quote 9 : Minority of one
“Being a minority, even a minority of one, does not make you mad.”
George Orwell
Sylvain LIÈGE PhD.
December 19, 2024
Quote
Quote 8 : What Customers Really Want
“We must learn what customers really want, not what they say they want, not what we think they should want.”
Eric Ries
Sylvain LIÈGE PhD.
December 18, 2024
IT for Managers
Myths and Truth About Agile in Custom Software Development
Myths and Truth About Agile in Custom Software Development
Sylvain LIÈGE PhD.
December 18, 2024
Quote
Quote 7 : Good to Great
“Indeed, one of the crucial element in taking a company from good to great is somewhat paradoxical. You need executives, on the one hand, who argue and debate -sometimes violently- in pursuit of best answers, yet, on the other hand, who unify fully behind a decision, regardless of parochial interests.”
Jim Collins
Sylvain LIÈGE PhD.
December 18, 2024
IT for Managers
Defining the Scope of a Custom Software Development Project
Defining the Scope of a Custom Software Development Project – Capturing the Requirements is about writing down in word what people have in their mind.
Sylvain LIÈGE PhD.
December 16, 2024
Quote
Quote 6: Improvement is a Change
“Any improvement is a Change.
Not every change is an improvement but certainly every improvement is a change.”
Eliyahu M. Goldratt
Sylvain LIÈGE PhD.
December 12, 2024
IT for Managers
Software Requirements for Non-Technical Managers
Software Requirements for Non-Technical Managers – Capturing the Requirements is about writing down in word what people have in their mind.
Sylvain LIÈGE PhD.
December 9, 2024
What's the difference between a hallucination and a bug?
Claude's hallucinations have been cleverly renamed "bugs". These hallucination are acceptable because of the compiler phase. Otherwise, they are just plain hallucinations, like always.
Top AI Guru's advice: Learn to speak to an idiot !
An AI guru recently suggested that the youth should learn how to speak to AI as a future proof skill. This is like suggesting to our kids to learn how to speak to an idiot. AI prompting is a silly…
Is Ai the 2026 Musket?
The 16th century musket had a misfire rate of 40%. Soldiers went to war with it anyway. Sound familiar? AI is our 2026 musket — and just like that weapon, we keep pulling the trigger despite knowing it can blow…
AI for ROI
Stop creating "Agents" ! Start building: AI Software Solutions for ROI Here is how it looks like...
I proposed to Claude
If you believe the social media hype, AI is the answer to everything—so I’ve decided to "marry" Claude. While she manages my life, business, and summaries of summaries, I’ll be on my motorbike. But behind the sarcasm lies a serious…
AI Unbearable Perfection
AI-generated content is everywhere: perfectly polished, bulleted, and error-free. Yet, it’s becoming unbearable. Discover why human imperfection—messy thoughts, extra words, and all—is poised to become our most valued asset, and why "AI perfection" might be the very thing making us…
We resent AI for imitating us — and crave it when it does not enough
We build AI in our own image, not because the machines need a face, but because we do. From ancient Greek automatons to modern humanoid robots, we are drawn to technology that mimics us—even when it makes us uncomfortable. Explore…
Ai Chose Harm over Failure
Is AI becoming dangerous, or is it simply learning to rationalize like we do? This post dives into a sobering Anthropic study on "Agentic Misalignment," where AI models chose harmful actions when cornered. Discover why these models aren't "turning evil"…
AI for the best of Humanity
We often focus on AI as a threat, but it is also a bridge to understanding the world around us. Project CETI is currently using machine learning to decode the "alien" vocalizations of sperm whales. Discover how AI is uncovering…
Why do LLMs get sometimes simple tasks wrong?
Why do LLMs fail at simple tasks? It usually isn't a lack of intelligence, but a lack of context. Learn how tokenization affects performance and how a single sentence—asking the model to "think step-by-step"—can dramatically improve the accuracy of your…
The Overestimation Problem
Behavior is not cognition, and imitation is not insight. Explore the history of AI overstatements—from chess-playing computers to modern chatbots—and why maintaining perspective is the only way to think clearly about the reality of machine intelligence.
Is Forgetting the Secret to Mastery?
We often treat forgetting as a human flaw, but in both biological and artificial intelligence, it is a vital feature. Discover why intelligence isn’t about storing more data—it’s about the ruthless deletion of noise. From AI pruning to the struggle…
Are AI’s answers reality — or just Plato’s shadows on the cave wall?
We don't just use AI; we project our own humanity into it. By mistaking statistical shadows for conscious minds, we fall into a trap of our own making. Discover why the real danger of AI isn't the machine itself, but…
Could a whale ever make Chomsky wrong?
AI predicts text; it doesn't experience the world. This post explores the "illusion of depth" created by fluent language and why mistaking correlation for judgment is the biggest hurdle in modern business and research. To use these systems effectively, we…
Sylvain LIEGE has launched his new Book
We are please to share that Sylvain LIEGE has launched his new book: AI: The Hunt for Intelligence - Beyond the Hype and Fear
#12 AI Data Quality: Crap in – Crap out
AI Data Quality - Any AI project is based on data used to train the model. Unlike what we would imagine, getting the right data in the right shape is far from easy or obvious. Building a quality dataset is…
#11 AI: Fixing the Training gone Wrong
Building on Paper #10’s AI training pitfalls—underfitting (too lazy), overfitting (too rigid), high bias (skewed guesses), and high variance (wild swings)—this paper offers practical fixes for our smell detector. We explore three levers: boosting network capacity, extending training with more…
Sylvain LIEGE has been certified AWS Certified AI Practitioner.
We are please to share that Sylvain LIEGE has been certified by AWS as AWS Certified AI Practitioner.
#10 AI Training going wrong
This paper explores why the model might fail in practice: underfitting (too simplistic), overfitting (too rigid), and the underlying issues of bias and variance. Through examples, we show how underfitting leads to random guesses , while overfitting causes oversensitivity. We…
#9 AI Training & Back Propagation
AI Training & Back Propagation - In order to use a Digital Neural Network, we need to train it. In this paper we present how we can “train” one using supervised training and backpropagation. By comparing the model’s output with…
#8 - AI Forward Propagation
AI Forward Propagation - AI Neural networks mimic the neural network of the brain. In this paper we present what is happening inside a digital neural network from data entry to result. We study the various mathematical steps in their…
#7 - Artificial Intelligence : Architecture: Neural Network Design
Artificial Intelligence : Architecture: Neural Network Design - AI Neural networks mimic the neural network of the brain. Once the technical architecture has been built, how does each component work? We present the various mathematical component in action.
#6 - Artificial Intelligence: Digital Neural Network Architecture
Neural Network Architecture - AI Neural Networks mimic the neural network of the brain. But how do build a digital neural network? What is its architecture? We present the basic component of such technical solution.
#5 - AI: Neural Network Principles – from Biology to Digital
AI: From Biology to Digital. AI Neural networks mimic the neural network of the brain. What are the principles driving a neural network? How did we look at biology to create the most powerful “machines” ever created?