
Professor, researcher, developer at Univ Lyon - Head of CITI Lab @citi_lab @insadelyon @inria - Dynamid Team - #distributed #systems #middleware #iot #smartcity
Lyon, France
Joined September 2008
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Les TP réseaux commencent au département Telecom ! @insadelyon #IP
"En terme d'outils, j'ai renoncé à avoir une politique unifiée, parce que cela va trop vite" #IA youtube.com/watch?v=AiytemqB…
Top A.I. Leaders Call for Slowing Down A.I. Development nytimes.com/2026/09/12/techn…
Frédéric Le Mouël ⛵️🇫🇷🇲🇽🇨🇳 retweeted
Así finalizó el noticiero de la Televisión Pública Española. Magistral.
“Our ultimate goal is to develop compact devices that can actively control heat radiation, much like electronic circuits control the flow of electricity" - Making heat behave like data eurekalert.org/news-releases…
Frédéric Le Mouël ⛵️🇫🇷🇲🇽🇨🇳 retweeted
刚看了一段伯克利工程学院的毕业典礼演讲,是今年看过最打动人的一段视频
演讲者收到伯克利博士录取通知的时候,96岁的奶奶跟她说:"我很为你骄傲,但我不想让你走。因为我不知道我还能不能再等五年,看到你博士毕业。"
她说从那一刻开始,她一直在想一个问题:一个PhD的重量到底是什么?
不只是论文和答辩。是导师的指导,是实验室里无数个孤独的夜晚,是家人替你承担的那些你看不到的代价
她的奶奶成长在动荡年代,连小学都没读完。但今天她坐在台下,看着孙女成为博士
演讲里有一段话我反复听了几遍:工程是人类最古老的职业之一,从石器到蒸汽机到今天的AI。我们有建造和定义时代的力量,但每个系统背后都是真实的人生,每个决定都有重量
现在AI这么热,大家都在聊模型多强、效率多高。但偶尔需要有人提醒一下:技术最终是服务于人的,不是反过来
她最后说,她设计传感器的时候,总会想象奶奶生活在这个技术世界里
Mostly right.
Researchers study the world while engineers seek to transform it.
Replying to @francoisfleuret
Major difference in my mind:
- an engineer, given a problem, invents and tries multiple solutions and stops when the solution is good enough. The goal is product innovation and shipping.
- a scientist asks new questions, proposes various new solutions, compares them (sometimes with old ones), and writes about it. The methodology must be sound or else peers will sneer. The goal is scientific breakthroughs and technological progress.
Both can be called "researchers". Many people can do both: these are activities, not identities.
Importantly, most product innovations are built on scientific breakthroughs and technological innovations that happened 2, 5, 10, or 20 years earlier.
Frédéric Le Mouël ⛵️🇫🇷🇲🇽🇨🇳 retweeted
Replying to @francoisfleuret
Major difference in my mind:
- an engineer, given a problem, invents and tries multiple solutions and stops when the solution is good enough. The goal is product innovation and shipping.
- a scientist asks new questions, proposes various new solutions, compares them (sometimes with old ones), and writes about it. The methodology must be sound or else peers will sneer. The goal is scientific breakthroughs and technological progress.
Both can be called "researchers". Many people can do both: these are activities, not identities.
Importantly, most product innovations are built on scientific breakthroughs and technological innovations that happened 2, 5, 10, or 20 years earlier.
Frédéric Le Mouël ⛵️🇫🇷🇲🇽🇨🇳 retweeted
One of the problems with AI coding is that the narrative on X (and other social media platforms) is mostly set by people who don't have the deep coding and software engineering experience of the likes of Bjarne Stroustrup.
Meanwhile the fundamental problems remain unaddressed:
1- AI generates super-human volumes of code
2- The code can be buggy, have security holes, be inefficient, etc.
3- The person who owns the code can be mostly unaware that such problems exist, so they won't even go after fixing them
4- The people who can actually fix the code (i.e., the software engineers who understand design, architecture, security best practices, etc.) are so overwhelmed that some of them will give up
Meanwhile, AI companies are constantly pushing the narrative that you don't need to look at the code and the AI will fix everything itself. What they don't tell you is that if your code fails, you'll be held accountable, not them.
Creator of C++, Bjarne Stroustrup:
AI-generated code isn't ready — it generates more bugs, more bloat, more security holes, and is nearly impossible to validate
"senior developers are already retiring rather than deal with it"
The problem is that even a small prompt change can shift the entire codebase in unpredictable ways
Frédéric Le Mouël ⛵️🇫🇷🇲🇽🇨🇳 retweeted
🇫🇷/🇺🇸 La start-up quantique française Alice & Bob a annoncé ce vendredi que le géant américain Nvidia entrait à son capital à un niveau minoritaire.
Article à lire ici ➡️ l.latribune.fr/SxS
Frédéric Le Mouël ⛵️🇫🇷🇲🇽🇨🇳 retweeted
A Norwegian neuroscientist spent 20 years proving that the act of writing by hand changes the human brain in ways typing physically cannot, and almost nobody outside her field has read the paper.
Her name is Audrey van der Meer.
She runs a brain research lab in Trondheim, and the paper that closed the argument was published in 2024 in a journal called Frontiers in Psychology. The finding is brutal enough that it should have changed every classroom on Earth.
The experiment was simple. She recruited 36 university students and put each one in a cap with 256 sensors pressed against their scalp to record brain activity. Words flashed on a screen one at a time.
Sometimes the students wrote the word by hand on a touchscreen using a digital pen, and sometimes they typed the same word on a keyboard. Every neural response was recorded for the full five seconds the word stayed on screen.
Then her team looked at the part of the data most researchers had ignored for years, which is how different parts of the brain were communicating with each other during the task.
When the students wrote by hand, the brain lit up everywhere at once.
The regions responsible for memory, sensory integration, and the encoding of new information were all firing together in a coordinated pattern that spread across the entire cortex. The whole network was awake and connected.
When the same students typed the same word, that pattern collapsed almost completely.
Most of the brain went quiet, and the connections between regions that had been alive seconds earlier were nowhere to be found on the EEG.
Same word, same brain, same person, and two completely different neurological events.
The reason turned out to be something nobody had really paid attention to before her work. Writing by hand is not one motion but a sequence of thousands of tiny micro-movements coordinated with your eyes in real time, where each letter is a different shape that requires the brain to solve a slightly different spatial problem.
Your fingers, wrist, vision, and the parts of your brain that track position in space are all working together to produce one letter, then the next, then the next.
Typing throws all of that away. Every key on a keyboard requires the exact same finger motion regardless of which letter you are pressing, which means the brain has almost nothing to integrate and almost no problem to solve.
Van der Meer said it plainly in her interviews.
Pressing the same key with the same finger over and over does not stimulate the brain in any meaningful way, and she pointed out something that should scare every parent who handed their kid an iPad.
Children who learn to read and write on tablets often cannot tell letters like b and d apart, because they have never physically felt with their bodies what it takes to actually produce those letters on a page.
A decade before her, two researchers at Princeton ran the same fight using a completely different method and ended up at the same answer. Pam Mueller and Daniel Oppenheimer tested 327 students across three experiments, where half took notes on laptops with the internet disabled and half took notes by hand, before testing everyone on what they actually understood from the lectures they had watched.
The handwriting group won by a wide margin on every question that required real understanding rather than surface recall.
The reason was hiding in the transcripts of what the two groups had actually written down.
The laptop students typed almost word for word, capturing more total content but processing almost none of it as they went, while the handwriting students physically could not write fast enough to transcribe a lecture in real time, which forced them to listen carefully, decide what actually mattered, and put it in their own words on the page.
That single act of choosing what to keep was the learning itself, and the keyboard had quietly skipped the choosing and skipped the learning along with it.
Two studies. Two countries. Same answer.
Handwriting makes the brain work. Typing lets it coast.
Every note you have ever typed instead of written went into your brain through a thinner pipe. Every meeting, every book highlight, every idea you captured on your phone instead of on paper was processed at half depth.
You did not forget those things because your memory is bad. You forgot them because typing never woke the part of the brain that would have made them stick.
The fix is the thing your grandmother already knew.
Pick up a pen. Write the thing down. The slower road is the faster one.
Frédéric Le Mouël ⛵️🇫🇷🇲🇽🇨🇳 retweeted
I strongly believe there are entire companies right now under heavy AI psychosis and its impossible to have rational conversations about it with them. I can't name any specific people because they include personal friends I deeply respect, but I worry about how this plays out.
I lived through the great MTBF vs MTTR (mean-time-between-failure vs. mean-time-to-recovery) reckoning of infrastructure during the transition to cloud and cloud automation. All those arguments are rearing their ugly heads again but now its... the whole software development industry (maybe the whole world, really).
It's frightening, because the psychosis folks operate under an almost absolute "MTTR is all you need" mentality: "its fine to ship bugs because the agents will fix them so quickly and at a scale humans can't do!" We learned in infrastructure that MTTR is great but you can't yeet resilient systems entirely.
The main issue is I don't even know how to bring this up to people I know personally, because bringing this topic up leads to immediately dismissals like "no no, it has full test coverage" or "bug reports are going down" or something, which just don't paint the whole picture.
We already learned this lesson once in infrastructure: you can automate yourself into a very resilient catastrophe machine. Systems can appear healthy by local metrics while globally becoming incomprehensible. Bug reports can go down while latent risk explodes. Test coverage can rise while semantic understanding falls. Changes happens so fast that nobody notices the underlying architecture decaying.
I worry.
Frédéric Le Mouël ⛵️🇫🇷🇲🇽🇨🇳 retweeted
Dans quelques moments #CATAI2026 Workshop en Colombie catai.fr/catai2026.html youtube.com/live/mUHmjKPIB9M… @France_Colombia
Frédéric Le Mouël ⛵️🇫🇷🇲🇽🇨🇳 retweeted
Primera vez desde que creamos la cooperación hace 13 años que no participaré en presencial. Sin embargo, se ha pasado el liderazgo a @ocrozo @citi_lab @CPELyon
Dans quelques moments #CATAI2026 Workshop en Colombie catai.fr/catai2026.html youtube.com/live/mUHmjKPIB9M… @France_Colombia
Matinée de travail à la I-Factory ! Quel beau cadre pour travailler et collaborer à la Doua 🥰 ! @insadelyon @Inria_lyon @UniversiteLyon


























