LLMs

Goodbye SSE, Embrace Streamable HTTP

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Goodbye SSE, Embrace Streamable HTTP

With the rapid development of artificial intelligence (<span>AI</span>), efficient communication between AI assistants and applications has become particularly important. The Model Context Protocol (<span>MCP</span>, abbreviated as <span>MCP</span>) has emerged to provide a standardized interface for large language models (<span>LLMs</span>) to interact with external data sources and tools. Among the many features of <span>MCP</span>, the <span>Streamable … Read more

Two Heads are Better Than One: The Adaptive Multi-Agent Framework M500 Achieves a 41% Improvement

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Two Heads are Better Than One: The Adaptive Multi-Agent Framework M500 Achieves a 41% Improvement

“Two Heads are Better Than One” (两个脑袋比一个好/双Agent更优) is an old saying in English. Researchers of the MAS-TTS framework have creatively applied this simple wisdom to LLMs, enabling multiple agents to collaborate like an expert think tank. Experimental data strongly demonstrates that in the face of complex problems, multi-agent systems achieve 60.0% performance, significantly outperforming single … Read more

Experience with Coze Multi-Agent Mode!

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Experience with Coze Multi-Agent Mode!

Recently, Coze in China has updated its Multi-Agent mode, nearly six months since the last release. So, what exactly is Multi-Agent? What is the difference between Multi-Agent and Single-Agent? What are some famous and pioneering Multi-Agent research or projects? With these questions in mind, we will provide some simple answers. If you are new to … Read more

Artificial Intelligence (AI) vs. Artificial General Intelligence (AGI): How to Distinguish Between the Two

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Artificial Intelligence (AI) vs. Artificial General Intelligence (AGI): How to Distinguish Between the Two

Today’s artificial intelligence (AI) is much like Schrödinger’s cat: it seems to be within reach, mimicking humans, while being entirely devoid of humanity. Imagine an AI that can not only answer questions like ChatGPT but also brew your morning coffee, wash the dishes, and even care for your elderly parents while you’re busy working. This … Read more

Understanding LoRA: The Right Approach to Fine-tuning LLMs

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Understanding LoRA: The Right Approach to Fine-tuning LLMs

↑ ClickBlue Text Follow the Jishi Platform Author丨CW Don’t Be Boring Editor丨Jishi Platform Jishi Guide Big questions about the popular LoRA in the model training community! Dive deep into understanding LoRA with source code analysis.>> Join the Jishi CV Technology Group to stay at the forefront of computer vision. Introduction Since ChatGPT sparked the trend … Read more

ReLoRA: Efficient Large Model Training Through Low-Rank Updates

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ReLoRA: Efficient Large Model Training Through Low-Rank Updates

This article focuses on reducing the training costs of large Transformer language models. The author introduces a low-rank update-based method called ReLoRA. A core principle in the development of deep learning over the past decade has been to “stack more layers,” and the author aims to explore whether stacking can similarly enhance training efficiency for … Read more