Recently, AutoGPT and HuggingGPT have become extremely popular. They automatically make decisions using the ChatGPT large model and call upon other models to achieve a high degree of automated decision-making, expanding the application scope of large models. However, the most critical aspect is understanding their specific implementation principles and how they operate internally, which is … Read more
New Intelligence Report Editor:LRS [New Intelligence Guide] A new paradigm combining large language models and AutoGPT has arrived! This paper presents a comprehensive benchmark study of Auto-GPT agents in real-world decision-making tasks, exploring the application of large language models (LLMs) in decision-making tasks. Paper link:https://arxiv.org/pdf/2306.02224.pdf The authors compared the performance of several popular LLMs (including … Read more
Yann LeCun announced on February 25, 2023, Beijing time, that Meta AI has publicly released LLaMA (Large Language Model Meta AI), a large language model that includes four parameter sizes: 7 billion, 13 billion, 33 billion, and 65 billion. The aim is to promote research on the miniaturization and democratization of LLMs. Guillaume Lample claimed … Read more
Data Digest authorized reprint from Xi Xiaoyao’s Cute Selling House Author: iven From GPT-3 to prompts, more and more people have discovered that large models perform very well under zero-shot learning settings. This has led to increasing expectations for the arrival of AGI. However, one thing is very puzzling: In 2019, T5 discovered through “hyperparameter … Read more
Click the “Blue Words” to Follow Us LlamaIndex, as a powerful framework, provides a solid foundation for building data pipelines that connect with large language models (LLMs). It implements a modular approach to query execution through structured workflows, simplifying solutions to complex problems. Today, let’s discuss the workflows of LlamaIndex. 1. Basics of LlamaIndex Workflows … Read more
Definition of AI Agent When it comes to agents, many people think it is a product of LLMs, but that is not the case. The modern definition of AI agents has gradually formed alongside the development of AI since the 1950s. Its roots can be traced back to earlier philosophical thoughts and scientific explorations. In … Read more
Source: Deephub Imba This article is about 5000 words long, and it is recommended to read for 10 minutes. This article will compare Mistral 7B vs Llama 2 7B and Mixtral 8x7B vs Llama 2 70B. To improve performance, large language models (LLMs) typically achieve this goal by increasing the model size. This article will … Read more
To avoid losing contact, please also follow the backup account. Large language models are machine learning models capable of generating natural language text based on context. In recent years, with the development of deep learning and big data, the performance and capabilities of language models have significantly improved, leading to the emergence of many applications … Read more
Paper: https://arxiv.org/abs/2501.00888 Github: https://github.com/Alibaba-NLP/CHRONOS Demo: https://modelscope.cn/studios/vickywu1022/CHRONOS In the digital age, the exponential growth of news information makes it crucial to extract and organize historical event timelines from massive texts. To address this challenge, Alibaba’s Tongyi Lab and researchers from Shanghai Jiao Tong University proposed a new framework for news timeline summarization based on agents—CHRONOS, named … Read more
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