Why bigger context windows won’t make RAG disappear.
We sometimes hear that RAG (Retrieval Augmented Generation) is destined to disappear because LLMs have an increasingly large context window and can therefore...
Machine Learning
Padding strategy matters when Fine tuning LLMs
A poor padding strategy can disrupt an LLM after fine-tuning, and the reasons are quite subtle. This is especially true since there is no pad_token in the Ll...
Assessing the Criticality of AI Failures
What is the criticality of a bad prediction from your algorithm? In my opinion this is one of the first questions to ask before considering a generative AI o...
The Non-Determinism of OpenAI and Anthropic Models
OpenAI and Anthropic's models are not deterministic, even at temperature zero and with a fixed seed, and this can be a real problem. How is it that some...
Math Skills vs. Pragmatism in Data Science
Math skills are often considered fundamental to becoming a data scientist. This is true, but we often forget to mention that in practice, machine learning is...
The Decline of TensorFlow, The Rise of PyTorch
TensorFlow was once essential, but I see fewer and fewer reasons to use it today. PyTorch seems to be establishing itself as the go-to deep learning framewor...
From Classic ML to LLMs: Similar Development Trajectories?
It's interesting to see how certain patterns in Machine Learning seem to recur, including with LLMs: Classic ML: </p> Step 1: The nature of the mo...
4 Simple Tips for Improving RAG Performance
Here are four simple tips for improving the performance of your RAG (Retrieval Augmented Generation): </p> Understand the RAG: The RAG combines a "R...
Speed Learning Machine Learning concepts in 1 Hour
If I only had one hour to familiarize myself with an unknown machine learning subject, I would try to choose some steps from the following list (ranked by pr...
Questioning the AGI Dream
I don't really know what to think about these AGI (Artificial General Intelligence) stories. Many players like OpenAI, Anthropic or Deepmind are pursuing thi...
Riding the LLM Hype Wave
I'd be lying if I said there wasn't hype around LLMs. Of course, the emergence of ChatGPT has propelled LLMs into the spotlight. Today, even people outside o...
Entrepreneurs: having a good idea is not enough to succeed.
There is a myth surrounding entrepreneurs that having a good idea is enough to succeed. This seems increasingly true today with the emergence of accessible A...
From Data Scientist to Data Engineer… ultimately to AI Engineer.
(This article is a transcript in English of one of my french LinkedIn posts) Lately, a clear trend of many Data Scientists moving towards Data Engineer ro...
Unmasking Confidential Data in ML Models with Membership Inference Attacks
(This article is a transcript in English of one of my french LinkedIn posts) MIA, or Membership Inference Attack, is a technique that lets you determine w...
Are you ready for the Machine Unlearning challenge ?
(This article is a transcript in English of one of my french LinkedIn posts) Have you heard about the Machine Unlearning challenge? It's an ethics-o...
Mutual information simply explained with example and code - A generalization of the correlation concept.
Mutual information is a very nice statistical tool that can be seen as a generalization of the correlation concept. Indeed, the pearson's correlation allo...
Intuitive explanation of bayes theorem - Part 1/2
One of the most important formula in statistics is perhaps the bayes theorem. Many people see this formula as somewhat magical and struggle to understand ...
Deploy a sentence transformer model on AWS Lambda via Docker
Today, let's dive into the beautiful (and sometimes very painful) world of deployment. This is really when things start to be very exciting as a you gener...
What is Entropy ? — Intuitive explanation with code.
You may be familiar with variance, it is a useful measure when looking for how spread the data is. When I say spread, I'm referring to the dispersion of d...
Cosine similarity: an Intuitive and simple explanation
Cosine similarity is one of the most important metric in Natural Language Processing. It is most often used to quantify a distance between two embedding...
Understanding projections - They are everywhere in Machine Learning !
These days I felt like writing an article about projections. Simply because I noticed that projections are one of these mathematical tools that people dai...