"We showed that transformers can execute programs efficiently inside their own inference loop, not as an external tool, but as part of the model itself. This opens a path toward AI systems that integrate learned representations with compiled algorithms inside a single
LLMS
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Wall Street Bankers Using Grok for Financial Modeling Applications
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Wall Street bankers building financial models in Grok is an interesting move. We'll see if domain expertise or LLM capabilities matter more here. I suspect it can become quite good, even though investing is most often more similar to betting, especially in the short term
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Kaggle Book: Master Data Science with ML and LLMs
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The Kaggle Book — Master Data Analysis and #DataScience Competitions with #MachineLearning, GenAI, and LLMs [2nd Edition]: http://
amzn.to/4pxJpTC v/ @PacktDataML Table of Contents:
Introducing Data Science Competition
Organizing Data with Datasets
Work & Learn with -
Architectural Innovation Over Compute Scale in AI Development
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The fact that throwing more compute at it isn't enough anymore is the real signal here. We might be entering a phase where architectural innovation matters more than scale again! At least, I certainly hope so…
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Extracting Agent Skills from Open-Source Code Repositories
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GitHub already has millions of repos full of procedural knowledge. The work introduces a framework for extracting agent skills directly from open-source repos. The pipeline analyzes repo structure, identifies procedural knowledge through dense retrieval, and translates it into
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LLM Curation Agent Scales Manual Content Moderation Automatically
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Yeah manual curation doesn't scale. The LLM curation agent handles it automatically
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OpenClaw Long-Term Memory Enhancement for Agent Workflows
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Give OpenClaw long-term memory that actually works! OpenClaw agents are powerful for dev work – scheduled workflows, automated testing, continuous monitoring of codebases. But there's a memory problem. Across sessions, OpenClaw's auto-memory gets stored by day in
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Mastering PyTorch: Create and Deploy Deep Learning Models
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Mastering PyTorch: Create and deploy deep learning models from CNNs to multimodal models, LLMs, and beyond – http://amzn.to/40IFEQR via @PacktDataML #AI #ML #MachineLearning #DataScience #DataScientist #GenAI
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AI tool automates a year of accounting in 20 minutes
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C'est DINGUE. J'ai uploadé mes relevés bancaires à Claude Opus 4.6. Il a analysé une année complète de transactions, séparé revenus et dépenses, et tout catégorisé. 20 minutes plus tard, la comptabilité était terminée.
Environ 11 000€ de travail comptable réglé en une -
AI Automation Dramatically Reduces Data Entry Time and Costs
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RÉSULTAT ATTENDU Avant ce prompt : 15-20h de saisie manuelle
Risques d'erreurs humaines
Ennui mortel
Coût comptable : 500-1500€ Après ce prompt : 20 minutes de traitement
90% du travail automatisé
Données structurées prêtes
Coût : 0€ (ou coût Claude API minimal) Économie :