What is Embedding? Why AI can search by semantics
Embedding can be understood as converting text, images, audio, and other content into a string of digital vectors. AI can search by semantic not becau...
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What is RAG? Why knowledge base Q&A can't do without searching
RAG stands for Retrieval-Augmented Generation, commonly called Retrieval-Augmented Generation in Chinese. Its core is not to have the model remember a...
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What is A2A Protocol (Agent2Agent)? Why multi-agent collaboration is starting to want a common language
A2A protocol, full name Agent2Agent, refers to a set of universal interaction protocols that allow different AI agents to discover each other's capabi...
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What is AI Native? Why more and more products are not "connected to AI" but "redone around AI"
AI Native generally refers to a system designed around AI capabilities from the underlying logic, interaction methods, and workflow structure of the p...
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What is Agent Memory? Why is the biggest shortcoming of many agents not being able to do it, but not being able to remember
Agent memory refers to how an agent retains, recalls, and updates task-related information outside of a single conversation. It can be user preference...
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What is Model Router? Why multi-model products are becoming more and more like routing and answering later
Model Router can be understood as a scheduling layer that "helps you decide which model to use first". It does not answer questions directly, but dist...
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What is VLA? Why can't we avoid Vision-Language-Action when it comes to action control when it comes to robot landing?
VLA is an abbreviation for Vision-Language-Action, which literally translates to the "Vision-Language-Action" model. The biggest difference from ordin...
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What are Reasoning Tokens? Why it has become a new metric for many teams when looking at inference costs
Reasoning Tokens can be understood as the part of the tokens that the model consumes to complete internal reasoning before giving a final answer. It's...
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