人工智能

This article provides a comprehensive analysis of key strategies for minimizing Token costs in the AI era, including prompt optimization, context compression, output control, image and PDF processing, caching strategies, and model task allocation. These methods enable individuals and teams to reduce AI usage expenses without compromising performance.

The Claude Code source code leak incident highlights more than a simple engineering error—it offers an early preview of Anthropic’s product strategy: background operations, automated execution, multi-agent collaboration, and permission automation. This article examines, from an industry standpoint, the probable directions Anthropic may pursue with Claude Code.

ERC-8183 is an Agent Commerce standard developed by the Virtuals Protocol and the Ethereum dAI team. By leveraging on-chain escrow, task lifecycle management, and evaluation mechanisms, it facilitates reliable transactions between AI Agents and establishes core infrastructure for the decentralized AI economy.

RoboForce is an emerging company specializing in AI-driven robotic workforce systems, leveraging high-precision robotics and automation technologies to replace dangerous and repetitive tasks. This article offers an in-depth examination of RoboForce's technical architecture, practical applications, and prospects within the industry.

As the AI era unfolds, how can individuals safeguard themselves against obsolescence? This in-depth analysis outlines practical approaches to building a personal moat and sustaining long-term competitiveness, examining personal data assets, AI skills, distribution channels, and cognitive structures.