L'expertise française en IA : les incantations et les spasmes d'un urologue
J’ai parcouru les six premières pages du dernier livre du guide officiel de la France en intelligence artificielle.
L’urologue qui nous secoue, remet en cause nos certitudes et nous ouvre les yeux sur notre avenir.
L’extrait est disponible sur le site de la fnac par exemple.
Le loto des dates
Je ne les reproduis pas ici mais c’est avant tout un enchevêtrement de dates, lâchées au petit bonheur la chance.
2025-11-14 07:00:00 +0000 UTC
L'expertise française en IA : un économiste nous vend son livre
Olivier Babeau a parlé de l’intelligence artificielle sur France Inter le 23/10/2025.
Il a coécrit un livre avec Laurent Alexandre qui nous enjoint à abandonner les études.
https://www.radiofrance.fr/franceinter/podcasts/le-debat-de-la-grande-matinale/le-debat-du-7-10-du-jeudi-23-octobre-2025-3967367
J’ai décidé de décortiquer cette interview.
Je ne m’attends à aucun sursaut de lucidité mais à une redite d’arguments d’autorités répétés en boucle.
(0:44)
Babeau : “Le titre est un peu marketing mais on va essayer de préciser un peu quand même.”
2025-11-13 07:00:00 +0000 UTC
Factuality in generative artificial intelligence: is there an elephant in the room?
Two years ago, I wrote an article on biases and “fallback answers” in generative artificial intelligence.
Back in time, I used simple examples like colors of taxis and phone booths to try to illustrate a wider problem.
It’s now time in 2025 to review this and try to measure the improvements or changes in this regard.
[Are all taxis yellow? A story of biases]
I’ll apply the same strategy by using simple verifiable elements that are linked with an unambiguous and well-defined context.
Objects, colors and patterns that are obvious for us humans. A reality we can observe on a daily basis.
2025-10-18 07:00:00 +0000 UTC
Nenuphars and gas consumption : let's ask Gemini !
In a previous article from October 2023 I was trying to test Llama and GPT's logic by trying to solve simple math problems.
https://www.kindrobot.org/article/nenuphars-gas-consumption-and-crypto-stories-coding-is-not-dead-yet/
And the results were not this impressive.
As the technology evolves and improves and as editors claim "giant" progress loudly on a regular if not daily basis, let's try to challenge one of them: Google Gemini.
Gemini, the large language model developed by Google was launched last December. A big roadshow.
2024-03-23 07:00:00 +0000 UTC
Large language models are not truly performant polyglots: how to escape the english centric trap?
Many people claim that large language models and particularly ChatGPT can speak and answer in almost all languages like humans.
Those marketing messages take a big shortcut by advertising those tools as efficient polyglots.
The progress in natural language processing is real but some problems and limits do remain on the table.
Are those tools equally efficient in all languages like some of us seem to think?
Isn't English better represented and related prompts receive better outputs?
How are those models trained and how important is the choice and volume of the initial corpus? How do editors fight against hallucinations and cultural biases?
2023-11-12 07:00:00 +0000 UTC
Recipes, books, car driving: how good are large language models to assist us with chronology and order?
We already noted that Large language models were not good at logic and particularly at Maths.
You can read this previous article containing simple experiments to highlight those issues:
[Nenuphars, gas consumption and crypto stories? Coding is not dead. Yet.]
Today we'll try to experiment with Google Bard the notions of order and chronology in texts.
This idea came from experiments run by my dear friend Joachim.
2023-10-28 07:00:00 +0000 UTC
Nenuphars, gas consumption and crypto stories? Coding is not dead. Yet.
Developers will be replaced massively by AI as coding becomes a useless task, starting today.
This idea and those statements started to grow after a few influencers experienced asking a chatbot to code a Tetris and deploying it and “it was working”.
They decided to take a big shortcut and concluded that “no-code” will be the new reality soon and the capacities of GPT and Large Language Models would make coders obsolete in the very near future.
It’s a simplistic opinion based on one single non representative use case used as a universal proof.
It does overestimate the capacities of the models we use.
2023-10-21 07:00:00 +0000 UTC
Are all taxis yellow? A story of biases
I had the idea to use Stable Diffusion XL to create images and illustrate articles I’m about to write.
To be honest, I was not obtaining the result expected and was failing prompts after prompts.
Prompting is probably a form of art but it’s also complicated to identify which parts are assumed and covered (and how) by the model and which ones need to be detailed.
Many voices have begun to say that the gap between humans and artificial intelligence systems is shrinking quickly.
Let’s confront the state of art and challenge this statement using simple experiments.
2023-10-12 07:00:00 +0000 UTC
Kindrobot : Who ? Why ? How ?
The main part of this article was written in 2017.
6 years after a lot has changed but many important questions remain on the table.
[Text from 2017]
Artificial intelligence does become an important topic and everyone's business.
When we hear about enthusiastic reactions from technical, marketing and financial parts of the society, we have a great idea of the growing buzz around the subject.
Our phones, computers, cars, and hospitals already use these technologies.
Things are going fast.
The technological revolution has begun. Impacts will appear everywhere in our lives within 10 years.
Many personal "thinking" assistants will pop up in our living rooms. Chatbots, image recognition, speech recognition.
More and more data will be collected, analyzed to feed the models.
Data that we provide everyday and which is sometimes used without our clear consent.
[/Text from 2017]
[2023 Update]
The rise of Large Language Models begins to shape our link with creativity, reality, efficiency.
Even our relation to work is challenged by those new tools.
Has this recent rise helped in creating and promoting clarity and transparency? How inclusive or even helpful is AI today?
For example, OpenAI switched from an open source approach to an aggressive commercial one to annihilate concurrency.
In the meantime, we seem to forget (or some of us let us forget on purpose) that the very roots of AI come from the open source world through research, universities, and massively public data.
[/2023 Update]
2023-10-08 07:00:00 +0000 UTC