The Role of Language in Reasoning and Conceptualization
Yann LeCun's recent statements about language not being necessary for reasoning are as fascinating as they are divisive. Among other things, he emphasizes th...
Personal Thoughts
Is There a Future for On-Device Open Source LLMs?
One obstacle to using open source LLMs is the cost of hosting them on GPU instances in the cloud. But perhaps there is a future for on-device open source? ...
RAG vs Finetuning - Complementary not Opposing
RAG and finetuning are often opposed: Should we fine-tune our LLM or do RAG? In reality, the approaches do not oppose each other. On the contrary, they compl...
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...
Most LLMs don’t succeed my “coco pops’ test”
Ah, really? Few good results for my Coco Pops test... The new Mistral model: surprising. Claude 2's response: legendary. Bard (PaLM2): Anthropic Cl...
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...
The Fleeting Value of LLM Benchmarks
You can't improve what you don't measure. However, the relevance of measurement can degrade over time. Regarding LLMs or machine learning in general, we of...
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...
Data Science Careers and Medical Specialties: An Amusing Parallel
I found it entertaining to draw a parallel between data science careers and medical specialties, to better convey the diversity of roles. The idea came to me...
Open source LLMs are sometimes cheaper than APIs
There are cases where using an open source LLM is cheaper than going through API calls. The main obstacle to using open source models is the inference cost a...
Is prompt engineering a scalable long-term approach ?
The Scalability Concerns of Relying on Prompt Engineering. I'm wondering if prompt engineering is a scalable long-term approach. I feel like today a large ...
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...
Did Microsoft leak the number of parameters in ChatGPT?
A Microsoft publication is causing quite a stir because it appears to have leaked the number of parameters in GPT-3.5 Turbo, which would be 20 billion ...
What is a Machine Learning Engineer in this World?
What is a Machine Learning Engineer in this World? It's not a Software Engineer It's not a Data Scientist It's not an MLOps Engineer It's not a Data Engin...
Can Python Really be Replaced Today?
Can Python Really be Replaced Today? I often see debates between Python and other programming languages on LinkedIn. Often, the arguments put forward are ...
The Fuzzy Notion of Overfitting with GPT4 - What Does it Mean to Overfit on All Knowledge?
What could it possibly mean to overfit on 'all available knowledge'? The notion of overfitting for GPT4 is fuzzy. Does it still make sense? With the emerg...
From Excel to Snowflake: Bridging the Data Culture Gap
(This article is a transcript in english of one of my french linkedin posts) We must realize that we live in a world where companies still fully operate w...
The future of generative AI will likely not be made of ever-larger models
(This article is a transcript in English of one of my french linkedIn posts) The future of generative AI will likely not be made of ever-larger models. In...
LinkedIn’s AI “Experts”
(This article is a transcript in English of one of my french linkedIn posts) AI experts are sprouting up on LinkedIn even as it becomes increasingly diff...
Data Science Students: Forget the Models, Focus on Deployment
(This article is a transcript in English of one of my french linkedIn posts) Recently, I started posting regularly on LinkedIn. As a result, many Data Sci...
Amazon will allow its users to have an amazing summary of all the reviews for a product
(This article is a transcript in English of one of my french linkedIn posts) Amazon will allow its users to have an amazing summary of all the reviews for...
Conveying complex ideas intuitively is an art
(This article is a transcript in English of one of my french linkedIn posts) Conveying complex ideas intuitively is an art. As Andrew Ng says "Before divi...