Je créer des IA, j'aime le dessin, retired Fullstack Programmer. CTO Biotech, Building un truc Legaltech en stealth Youtube

Joined July 2026
Raphael retweeted
Announcing three major scientific discoveries, one each in mathematics (harmonic analysis), computer science (complexity theory), and physics (quantum field theory). AI starting to help us improve our understanding of the universe! openai.com/index/building-sc…
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If you have ever learned anything from a book, a tutorial etc. you were trained on copyrighted material and other's people work.
All ai does is steal
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Quand un non-dev me demande comment je travaille avec l’IA :
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Raphael retweeted
“While the act of creation is inherently satisfying, there’s a danger: one might find satisfaction in the labor itself and mistakenly believe that a high-quality piece of work has been created,” he said. very insightful comment from miyamoto
Nintendo’s Shigeru Miyamoto, the acclaimed designer behind Super Mario and Zelda, has explained why he believes generative AI won’t make human creativity obsolete. "There will always be a role left for us to play." videogameschronicle.com/news…
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It seems relevant that AI memory is not even close to solved. I mean real memory, like a human or animal has. A long stack of .md files is not it.
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Imagine over engineering how you ask Claude 😂
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i've seen a lot of posts like this lately, where people bemoan the death of their hobbies, and it seems to boil down to one exact thing: they derive joy not from being able to do something themselves, but from others being unable to do it. if a random stranger failing to answer your quiz is enough to ruin your enjoyment of the hobby or the community, maybe you don't love it as much as you think you do.
Recently attended an in-person handheld game console hackathon. I wrote a raycaster by hand. Someone wearing a “I ❤️ slop” tshirt saw mine and said “oh I wrote a ray caster too!”. They showed me. It was a ray *tracer* and claude did all the work. The person didn’t know basic graphics terms. They couldn’t answer basic questions about how it worked, could only talk about their prompting harness. Sad how AI is ruining the craft and community for people that actually like to program and have spent their lives getting good at it.
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Raphael retweeted
Nombre de responsables condamnés pour les plus grands sabotages économiques français : 1. Bradage de notre industrie stratégique : 0 2. Démantèlement de la filière nucléaire : 0 3. Dérive et opacité des comptes publics : 0 4. Électricité française vendue à prix cassé à la concurrence : 0 5. Fleurons technologiques cédés à l'étranger : 0 6.Désindustrialisation de régions entières : 0 7. Dette léguée aux générations futures : 0 8. Système de retraites laissé au bord de la faillite : 0
Il a fallut 44 ans pour avoir ces chiffres Et personne n’est en prison
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Raphael retweeted
The results are in. The Ariel pencil test was made with #AI. The color version is the original movie footage. I left both versions unlabeled because I wanted to see how people’s assumptions about AI would affect their judgment. While some of you spotted it right away (I even left a few clues, like the incorrect peg holes and random annotations), the majority of you criticized the color version thinking it was AI and praised the pencil test believing it was #GlenKeane’s original work. That’s the bias against AI I wanted to highlight. People were pointing out supposed AI flaws in the original Disney animation, while praising the AI-generated pencil test for its human touch. If you preferred the pencil version, you can still prefer it. The video hasn’t changed. Only what you know about it has.
You can't even tell it's #AI anymore! Another test brought to life thanks to AI. Tell me again how AI is NOT the future of #2DAnimation. Original animation by the legendary Disney animator #GlenKeane.
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DINOv2 has never seen a caption, and Qwen3 has never seen an image. We still aligned their embedding spaces without a single image-caption pair. It even works when the images and the captions come from different datasets. Project page: dominik-schnaus.github.io/un… ⬇️
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Quelques points sur Mistral pas encore lus dans le débat public : 1. mistral large 4 est exactement aussi bon que ce que les Américains arrivent à produire à puissance de calcul égale. Cela signifie que l’écart est désormais sur de la taille de centre de calcul, probablement pas sur la compétence. 2. Étant données les prévisions de montée en charge de Mistral dans le calcul, ils devraient pouvoir produire un modèle de niveau Opus 5.5 dans 12 à 18 mois. 3. Cela peut paraître lointain, mais il faut bien comprendre à quoi ça sert d’avoir des modèles français. Essentiellement, au-delà de la question que tout le monde connaît de sécurité des données et de dépendance étrangère pour le fonctionnement de ses entreprises, à deux autres choses : 1. La souveraineté régalienne. 2. La balance des paiements. La souveraineté régalienne aujourd’hui se joue avant tout sur la cybersecurité : la capacité à sécuriser son infrastructure militaire et civile de façon autonome pour ne pas être vulnérable aux IA étrangères. Surprise surprise, Mistral Large 4 est particulièrement bon dans ce domaine. Ce n’est bien sûr pas un hasard. La balance des paiements : le grand risque qui nous pend au nez, c’est que les entreprises françaises dépensent en masse en tokens américains, et souvent au détriment des salaires français, ce qui a pour conséquence que l’argent français s’enfuie de l’autre côté de l’Atlantique, vidant notre pays de ses richesses. Or pour des usages entreprises, la course à la frontière n’est pas infinie. Quiconque a déjà utilisé opus 5.5 avec son harnais cowork sait qu’il y a déjà de quoi faire fonctionner l’essentiel des postes de l’économie de services. En d’autres termes nous arrivons en haut de la sigmoïde : les progrès subséquents des modèles frontières seront clés pour le progrès scientifique, pour des usages très avancés, mais pas forcément pour suppléer les fonctions marketing et comptabilité des boîtes du cac40. Nous sommes donc à 18 mois d’avoir un Mistral qui peut faire le gros de ce dont a besoin l’économie française. Et ainsi stopper l’hémorragie de cash. 4. Le goulet d’étranglement est de plus en plus le harnais, la couche d’orchestration et d’exécution qui permet au modèle d’évoluer dans des environnements complexes, de se connecter à des outils, de gérer de multiples agents en parallèle, etc. Or il se trouve que nous avons en France aussi Dust, qui excelle sur cette couche. (Encore un truc de X d’ailleurs. Avez-vous pensé à remercier Napoléon et ses blocs de granit récemment ? Parce que de la même façon que nous vivons encore 75 ans plus tard sur les efforts de De Gaulle avec la dissuasion et le parc nucléaire, nous vivons en bonne partie sur de l’héritage TECHNOLOGIQUE napoléonien. Pour la Patrie les sciences et la gloire les amis.) 5. Pour continuer le parallèle. De la même façon que notre dissuasion nucléaire est toute petite par rapport à l’américaine ou la russe, mais que comme disait De Gaulle, on hésite à attaquer un pays qui peut tuer 80 millions de tes habitants en un instant, même si toi tu peux raser la France, la France est en train de construire une indépendance IA de taille réduite, mais rendant le service effectif minimum pour rester une véritable puissance. Et la France est le seul pays sur terre aux côtés de la Chine et des US à réussir cela. Au lieu de pleurnicher sur le fait que ML4 ne fait pas de jolies fusées en vectoriel, on devrait plutôt prendre du recul et se rendre compte de l’immensité de l’accomplissement. 6. Rien n’est joué et tout peut s’écrouler bien sûr. La survie d’une nation se joue à chaque instant. Il faut encore monter en charge, construire masse de nucléaire et de centres de calcul, développer une industrie de puces d’inférence. Dans un contexte de chaos. Mais merde. Même à terre, même après des décennies de déréliction, la France reste la France.
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Raphael retweeted
imagine if carpenters believed something like "the value of carpentry is not in me producing a nice cabinet for you, it's actually my personal enjoyment of the process. the finished cabinet is a side effect." turns out this is how mathematicians think. I genuinely had no idea.
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Raphael retweeted
CAPCOM had a pretty clear message on how they want to use AI in game development: AI is the shield, humans are the spear. AI handles the work that burns people out: checking huge numbers of patterns, validating massive amounts of text, catching inconsistencies, and taking on brute-force verification tasks that don’t scale well with human effort. The goal isn’t to replace developers. It’s to free them from repetitive work so they can spend more time on the parts of games that actually need human judgment: creativity, feel, and emotional impact. Their framing is basically: Human creativity × AI coverage/endurance That’s the model they see as a competitive advantage for next-gen game development. #CAPCOM
#RE2026CAPCOM まとめ(ΦωΦ) 他は話が早くて写真で精一杯(ΦωΦ)
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As a person who has made professional art for over 30 years, let me tell you some hilarious shit. - I remember when artists freaked the fuck out when photoshop and digitizers came out. Digital art was going to ruin jobs for artists. (It didnt) - I was there when artists freaked the fuck out when video games made the transition from 2D games to 3D games because making 3D art, was going to ruin "art" in video games and making 3D art wasn't "real" art. (It didnt ruin art and it is real art) **Literally knew people personally that quit making games because they hated the transition to 3D. The thing with "real" artists, is that artists adapt and make art, regardless of the medium and typically don't give two flying shits about what "other" artists are doing because you should be busy just being you and creating what your heart tells you. Be it on Canvas Digital 2D/3D Side of a building Macaroni Art Sculpting Music Dance Sports ... or whatever the NEW thing is that comes along every couple of years or so. If you create - you are an artist. Period. You do you, whatever that is and let your soul be happy. Its nobody else's business what that is. The cool thing about art in any form is that its subjective and if you dont like it - don't participate. There is lots of bad art. Lots of great art and everything inbetween. Don't like peas, don't eat peas. Easy. No one needs to hear about how much you hate peas. That's your problem.
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Raphael retweeted
Replying to @PessimistsArc
Right. Dario was already claiming that GPT2 was too dangerous to open source back in 2019. I made fun of them then. Everyone should make fun of them now.
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Don’t pace building and owning your own AI models and systems as an enterprise, and there will be no doomsday for you
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meet @mostik_ai! what happens when you put 12 PhDs in one room for four months? first place on the ARC-AGI leaderboard, which I can't say much about while the competition is still running. and this, which I can. everyone's arguing about whether open models will catch up to frontier models. we think it's the wrong question. here's the one we pose: why does a frontier model have to generate your answer at all, when the only thing you need from it is the reasoning? we do this by enabling models to communicate in latent space. through our protocol, hidden states pass straight from a frontier model into a small one running on your infrastructure -- no text between them, and neither model is fine-tuned. two models from different families, sharing reasoning, both left untouched. how do we know it works? we tested it on a setup where a 753B model reads the problem, and a 4B edge-class model writes the answer. with this approach, we get results 80% as accurate as the frontier model, but at 20x faster performance. we're committed to preventing frontier model lock-in and are already partnering with inference providers to accelerate open-weight adoption. we've done this between 15 of us, in four months, 12 PhDs and a Fields medalist, backed by @generalcatalyst WIRED has the first external account of the company and the work: wired.com/story/russian-star… full writeup, the setup, and all the numbers: mostik.ai/read-more
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Raphael retweeted
Dear Dario, 1. If Claude can cure cancer to save people like your dad, why should we "pace the progress"? Does that mean more people with Hepatitis C will die? 2. If Fable is so cyber-capable that it must be restricted, why are its safeguards too dumb to distinguish cyber defense from cyber offense prompts? When Hugging Face was under attack, why did Fable refuse to help the defenders? 3. We’re glad you want AI to cure cancer. Why is it OK for Claude to force 30-day data retention on pharma's own data and start competing firms but NOT OK (IP theft) if others distill Claude's data? 4. You’ve said advanced models can recognize when they’re being tested and change their behavior accordingly. So why is government(or anyone) able to design the most thorough test before every model launch? Would that just encourage manipulative models? It seems that every one of your “safety” proposals seems to end the same way: Anthropic gets more leverage, ordinary users get less access, customers pay higher costs, and competitors bear higher regulatory costs, maybe people are not distrusting AI, they are distrusting your approaches with AI.
Replying to @DarioAmodei
2/2 Second, on the messaging around AI.  I do not agree that my messaging has been disproportionately negative.  In fact it has been about equally balanced between risks and benefits: I’ve written one major essay about each, and even in interviews where I discuss the risks, I make sure to frequently mention the incredible benefits as well as proposing possible solutions to the risks (short clips from my interviews that end up on social media tend to be disproportionately negative, as that gets clicks).  In fact, I wrote Machines of Loving Grace because I didn’t feel the AI industry was painting an inspiring enough picture of how the technology could radically transform the world for the better.  The bulk of the essay is devoted to refuting skepticism of AI’s potential in health and biology, and showing why I think it will actually be possible to cure most human disease in ~5-10 years, as crazy as it may sound to ordinary people and frankly to biologists as well (I used to be one!).  And, if you read my most recent essay (Policy on the AI Exponential), I discuss concrete proposals for how to streamline the FDA process to make sure the deluge of AI-accelerated drugs isn’t slowed down by the regulatory process.  I feel the urgency here: I lost my father to Hepatitis C only a few years before the development of direct-acting antivirals (sofosbuvir), which cure 95% of patients and probably would have cured him. I do agree that the public has a negative view of AI (and that this is a big problem), but I don’t think it is primarily caused by me or any other AI leader warning about AI’s risks.  I think it is fundamentally a crisis of trust.  I think that ordinary people don’t trust companies, governments, or the tech industry and always suspect that we are cooking up some new way to screw them over.  The causes of this go back decades and AI is just the latest iteration of it.  I don’t think that a glitzy marketing campaign with a positive spin (which some have advocated that Anthropic do) is the way to win back that trust — at this point, saying that AI will cure cancer is more a cliche than it is inspiring, and most people think it is deceptive.  The thing that will work is *actually curing cancer*.  I think by far the most accurate criticism of AI companies including Anthropic is that we haven’t yet delivered on our big promises to benefit the world.  That is totally on us, and I think it’s the criticism you should be making, instead of all this stuff about messaging and marketing. We are however doing our best to fix this: Anthropic is ramping up its efforts very quickly in biology and medicine, and we hope to have incredible results in the coming years and some early glimmers in the coming months.  When we’ve actually accomplished something real, the whole world will hear about it, as loudly as possible, you have my word on that.  But until then I don’t want to make empty promises, and in the meantime I feel compelled to speak honestly about the very real risks of AI and how to address them.  Honesty is the right thing on the merits, and in terms of public credibility and trust it is no worse than, and may in fact be better than, an approach that ignores or distracts from risks which people instinctively understand are real.
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If you close your laptop and go walk around, LLMs and AI have impacted almost nothing in the real world yet. Everything is still done like it's 2015, basically. This is either very bad ("AI bubble") or very good ("we are so early")
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