Oh, great, AI will read X and post more memes in 2026. Will need to have an AI read those memes and tell me which ones are the funniest. 🙂
MACHINE LEARNING
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New fast-learning AIs: World Models trend in 2026, Tesla leads
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Yup. And new AIs are on the way that learn faster. Which is why World Models will be a huge trend in 2026. Who has the best World Model? Tesla.
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Centralization for routing, Tesla ensures safe offline operation
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Yes. Now there is a role for centralization. Where should the robot drive to pick up next rider, for instance. But because of how Tesla was trained it will be able to complete the job even if everything goes down. And do it safely.
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Multi-Fingered Hand Assembly: Engineering vs Machine Learning Trade-offs
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Precision assembly is common but OK! Doing it with a multi-fingered hand is interesting: how much of this demo is due to Model-Free Learning and how much is Good Old-Fashioned Engineering (GOFE)? I'll bet it's mostly the latter. Now use it to generate data for the former…
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Discussion on using Alpaca for trading
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Merci pour la mention ! Et pas mal d'avoir utilisé alpaca j'y ai pas pensé ! C'est du paper trading ou du vrai ?
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Release of AI-based trading project code on GitHub
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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
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Segment Anything Models Advance Flood Monitoring and Disaster Response
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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:
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GLM-4.7 Model Benchmark Performance and Competitive Analysis
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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?
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Limitations of basic embedding and keyword search in AI systems
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yes mais là c'est plus que de l'embedding ou du keyword qu'il faut ^^
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Technical limitations of LLMs in specific NLP tasks
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Grave et c’est surtout un des rares sujets de NLP impossible à adresser actuellement par des LLM.