Edge Computing

Goodbye Large Models: MiniRAG for Efficient Knowledge Retrieval

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Goodbye Large Models: MiniRAG for Efficient Knowledge Retrieval

Today, I will share a retrieval-augmented generation method designed for resource-constrained scenarios: MiniRAG. Paper link: https://arxiv.org/pdf/2501.06713 Code link: https://github.com/HKUDS/MiniRAG Introduction With the rapid development of retrieval-augmented generation (RAG) technology, the performance of language models in knowledge retrieval and generation tasks has significantly improved. However, existing methods heavily rely on large language models (LLMs), leading to … Read more

Generative AI Inference Technology, Market, and Future

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Generative AI Inference Technology, Market, and Future

OpenAI o1, QwQ-32B-Preview,DeepSeek R1-Lite-Preview’s successive release signifies that generative AI research is shifting from pre-training to inference to enhance AI logical reasoning capabilities. This transition will greatly promote the development of upper-layer applications.Sequoia Capital recently pointed out, that in the foreseeable future, logical reasoning and computation during inference will be an important theme, ushering in … Read more

A Brief Introduction to AI Agents

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A Brief Introduction to AI Agents

1.Definition An AI Agent is a software or hardware entity capable of perceiving its environment through sensors and affecting it through actuators. It possesses autonomy, reactivity, proactiveness, and learning ability. 2. Core Features Autonomy: Able to operate and make decisions without human intervention. Reactivity: Capable of perceiving environmental changes and responding in real-time. Proactiveness: Not … Read more