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Get zero API bills for your AI agent with your own ASUS Phoenix RTX 3060 PC
This content discusses running AI agents locally on consumer hardware (ASUS Phoenix RTX 3060 PC) to eliminate API costs. By leveraging local GPU computation instead of cloud services, developers can reduce operational expenses from approximately $1.50/day to near-zero. The approach demonstrates cost-effective alternatives to cloud-based AI agent infrastructure.
- Local GPU inference on consumer hardware (RTX 3060) eliminates recurring API bills for AI agents
- Cloud pricing for equivalent daily agent work estimated at ~$1.50/day
- ASUS Phoenix RTX 3060 provides sufficient compute for running AI models locally
- +4 more key points...
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Agent Teams
Hermes, OpenClaw & Grokbot: AI Agent Setup for Beginners (LIVE)
This live session provides a beginner-friendly introduction to setting up AI agents using Hermes, OpenClaw, and Grokbot. The content walks through basic harness setup and configuration for these agent frameworks, making it accessible for those new to AI agent development. Viewers learn foundational concepts and practical steps to get their first agents running.
Justin Coleman
OpenClawに仕事を丸投げしたら、何回呼び戻される？｜実際に試した
This video demonstrates a practical test of OpenClaw's autonomous task handling by delegating the selection of meeting rooms based on 7 documents with specific conditions. The experiment measures how many times the AI agent needs to call back for additional information or clarification before completing the task. The test reveals the iterative nature of AI agent workflows and their ability to handle complex, multi-document decision-making scenarios.
Log & Bugle
【第61回】OpenClaw Scheduler をマスターする - 那珂将人
This is a presentation from the 61st AI Social Implementation Study Group held on July 25th, featuring Masato Naka discussing mastery of OpenClaw Scheduler. The session covers techniques and best practices for using OpenClaw Scheduler in AI agent development workflows. Key focus areas include scheduler configuration, workflow optimization, and practical implementation strategies for managing agent tasks efficiently.
AI社会実装勉強会
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