2nd Edition — now at http://
amzn.to/45Y3LyI v/ @PacktDataML Graph Machine Learning — Latest advancements in Graph Data to build robust #MachineLearning algorithms 𝓚𝓮𝔂 𝓕𝓮𝓪𝓽𝓾𝓻𝓮𝓼:
Master new graph ML techniques through updated examples using PyTorch Geometric and
AI
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Graph Machine Learning 2nd Edition with PyTorch Geometric Advancements
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OpenClaw Setup Guide: Stateful Local Memory Configuration
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Detailed set-up guide: https://
byterover.dev/blog/curated-s
tateful-local-memory-for-openclaw?utm_source=sumanth&utm_campaign=openclaw_skill&utm_content=X_0326
… Byterover Skill: -
OpenClaw ByteRover Auto-Plugin Support Persistent Memory
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Soon there will be auto-plugin support for OpenClaw with ByteRover. Zero manual setup for persistent memory. Support this feature → like the PR:
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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 Adoption Strains Energy Infrastructure: Preparing for Future Demand
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#READ | As AI adoption accelerates, one critical question emerges: Is our energy infrastructure ready for the AI era? At the pre-summit session “AI and Electric Energy: Complementing for a Sustainable and Resilient Future”, held ahead of the India AI Impact Summit 2026 and
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AI Sovereignty and Energy: Understanding Policy Implications
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And Rubin is delivering! I honestly think the problem is that the vast majority of policy makers dont understand that AI, sovereignty and energy are linked at most macro level. Let alone tokens-per-watt and industrial electricity prices.
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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 -
Agentic AI Periodic Table: Memory, Planning, Tools, Safety
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Agentic AI has a “Periodic Table.” It includes: LLM, RL, RAG
PLAN, MAS, LTM
SAFE, TEST, HUMAN
A2A, CREW, NET
HR, MKT, LEGAL use cases Autonomous AI = memory + planning + tools + safety + collaboration. It’s an ecosystem, not a feature. Credit: Prem Natarajan #AgenticAI -
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 :