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Humans Can See, AI Can't: The Essential Difference That Hidden Heart Reveals

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A static black-and-white noisy image will show a dynamic heart pattern when viewed through a cell phone or zoomed in on a page, which cannot be recognized by AI models such as Gemini 2.5 Pro, GPT-5, and Beanbag. The study shows that AI can only analyze discrete static frames due to "time blindness" and cannot perceive dynamic information between frames. Humans rely on Gestalt psychology's "Law of Common Fate" and the visual system's predictive coding ability to instantly capture motion trajectories, and SpookyBench tests show that human recognition accuracy exceeds 981 TP3T, while the AI model's accuracy is 01 TP3T, revealing the fundamental limitations of AI's integration of spatial and temporal information.

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An article to read about Web3 technologies and applications

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Web3 has moved from concept to reality, with a global market size of $21.35 billion in 2025, and the scale of China's related industry exceeding $20 billion. Its core lies in user sovereignty, and power redistribution is realized through blockchain, smart contract, NFT and DID. The five major application scenarios include DeFi (TVL over $120 billion), NFT utility (e.g. Starbucks equity), DAO (over 5,000 active organizations), GameFi (over 3,100 games) and decentralized identity. The market is shifting from speculative to value-driven, with future opportunities focusing on the creator economy, digital identities and RWA asset tokenization, with the goal of rebuilding digital trust and equity.

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Cursor MCP Servers Configuration Guide and Cursor Practical MCP Recommendations

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MCP (Model Context Protocol) is a protocol that allows large models to interact with external tools and services. Cursor IDE supports AI assistants to invoke tools to perform searches, browse the web, and code operations through the MCP Servers feature. MCP servers can be added through the Settings interface and configured at both the global and project levels.MCP is written in multiple languages and allows the AI to run tools automatically or manually and return results, including images. Recommended resources include Awesome-MCP-ZH, AIbase, and several MCP client tools. Commonly used MCP services such as Sequential Thinking, Brave Search, Magic MCP, etc. enhance AI's ability to think, search, front-end development efficiency, and other features, respectively.

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Gemini 2.0 PDF Explained: Code Examples and Best Practices

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The Gemini 2.0 model, introduced by Google DeepMind, significantly improves PDF document processing capabilities. Compared to traditional solutions in terms of accuracy, cost and scalability deficiencies, Gemini 2.0 significantly optimizes the PDF parsing process through structured data extraction, semantic chunking and efficient batch processing, and provides a variety of model options to balance performance and cost.

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A deeper understanding of LangGraph: a new paradigm for building intelligent AI workflows

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LangGraph is a revolutionary AI framework for processing complex tasks through graph structures that support multi-step reasoning, dynamic decision-making, and multi-intelligence collaboration. Its core includes node, edge and state management, suitable for building intelligent workflows. Compared with traditional chaining frameworks, LangGraph is equipped with conditional routing, loop control and visualization features, and has a wide range of applications in intelligent customer service, text processing and other fields.

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