Tout le monde me demande le code de la dernière vidéo sur le trading par IA, donc réponse globale : > Oui, le code sera disponible. Ne vous inquiétez pas, il est déjà prêt sur GitHub comme vous pouvez le voir, mais il sera publié après la vidéo partie 2, comme expliqué en fin
MACHINE LEARNING
-
Segment Anything Models Advance Flood Monitoring and Disaster Response
By
–
Our Segment Anything Models are helping advance flood monitoring and disaster response.
— AI at Meta (@AIatMeta) 22 décembre 2025
See how @USRAedu and @USGS have fine-tuned SAM to automate a key bottleneck in real-time river mapping, enabling faster, scalable, and more cost-effective disaster preparedness:… pic.twitter.com/kSHkaOKlheOur Segment Anything Models are helping advance flood monitoring and disaster response. See how @USRAedu and @USGS have fine-tuned SAM to automate a key bottleneck in real-time river mapping, enabling faster, scalable, and more cost-effective disaster preparedness:
-

GLM-4.7 Model Benchmark Performance and Competitive Analysis
By
–
BREAKING : GLM-4.7 by @Zai_org scored 42% on the HLE benchmark, representing a 38% improvement over GLM-4.6 and approaching GPT-5.1 performance. New SOTA open source on SWE?
-
Limitations of basic embedding and keyword search in AI systems
By
–
yes mais là c'est plus que de l'embedding ou du keyword qu'il faut ^^
-
Technical limitations of LLMs in specific NLP tasks
By
–
Grave et c’est surtout un des rares sujets de NLP impossible à adresser actuellement par des LLM.
-
Topic Modeling Project Recommendation for AI Portfolios
By
–
Je sais que pendant les vacances, vous êtes plein d'étudiants en IA à chercher des projets portfolio à montrer en entretien. J'en ai un qui se fait en 3 jours pour un pirate. C'est du topic modeling, c'est ultra visible et je vous garantis que c'est un sujet que 100 % des boîtes
-

Research Challenges Scaling Myths for AI Agent Tool Calling
By
–
This paper quietly destroys one of the most repeated myths in AI: that bigger models are always better for agents. The researchers took a 350M-parameter model and fine-tune it specifically for agentic tool calling. Not chatting. Not creativity. Just one job: pick the right tool,
-
Using World Models to automate companies, thanks @spisallyouneed
By
–
Thanks @spisallyouneed for such an interesting look at how you are using World Models to change how companies can automate themselves.
-
Self-driving car improves weekly, first human-free drive this year
By
–
It improves every week or so. It is a DRAMATICALLY DIFFERENT experience today than it was 12 months ago. And this year was the first time it drove around without a human in the car.
-

LLaDA2.0: Converting Auto-Regressive Models to Discrete Diffusion
By
–
LLaDA2.0, a new method that converts existing auto-regressive models into discrete diffusion models using a novel 3-phase training scheme. This approach preserves the model's learned knowledge while unlocking parallel decoding. The resulting models, LLaDA2.0-mini (16B) and
