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:
CODE
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OpenClaw Setup Guide: Stateful Local Memory Configuration
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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 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 : -
Autonomous React Loop: Key Difference in AI Agent Architecture
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Yeah, the react loop being done autonomously is basically the main difference !
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Kirk Borne Offers Over 4600 Free Resources for X Subscribers
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I continue adding more 𝐅𝐑𝐄𝐄 resources for my @X Subscribers to access: 𝗼𝘃𝗲𝗿 𝟰𝟲𝟬𝟬 𝗿𝗲𝘀𝗼𝘂𝗿𝗰𝗲𝘀 𝗮𝗿𝗲 𝗻𝗼𝘄 𝗮𝘃𝗮𝗶𝗹𝗮𝗯𝗹𝗲. Subscribe for only US$6/month #MachineLearning #ML #AI #DataScience #Python #Mathematics #Statistics #SQL #GenAI #AgenticAI
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Preparing for AI Engineering Interviews: Practical Advice
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A question I get all the time: "How do I prepare for an AI engineering interview?" And lately it comes with like "my friends are getting 24-hour take-home tests. How do I practice for them?" Here's the gist after interviewing ~100 candidates for AI engineering roles at
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Core Code Optimization and AI Plugin Architecture Advances
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We made a ton of progress on that today. Lots of code gone from core. Faster, less memory use overall. Need another day or two to stabilize. Everything can be a plugin now. Also added support for Claude/Codex/Cursor plugin bundles
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Attention Residuals: Novel Architecture for Transformer Models
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Attention Residuals Paper: https://
github.com/MoonshotAI/Att
ention-Residuals/blob/master/Attention_Residuals.pdf
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Code: https://
github.com/MoonshotAI/Att
ention-Residuals
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