Source: DeepHub IMBA This article is about 1000 words long and is recommended to read in 5 minutes. When real information exceeds a few words, the chance of exact matching becomes too slim. In RAG systems, actual fact recall evaluation may face the following issues: There has not been much attention paid to automatically verifying … Read more
Source: Chen Wei Talks on Chips, This article will introduce the characteristics, functions, technical architecture, limitations, industrial applications, investment opportunities, and future of ChatGPT. Author: Dr. Chen Wei, the author previously served as the chief scientist of a Huawei-affiliated natural language processing (NLP) company. Integrated storage/computing/GPU architecture and AI expert, senior title. Expert in the … Read more
The Most Complex Artificial Intelligence Super AI GPT-3 is destined to be one of the most important breakthroughs in the field of artificial intelligence in 2020. It is currently the most complex artificial intelligence language model in the world, developed by the renowned artificial intelligence open platform OpenAI. How complex is GPT-3? Technically, the most … Read more
This article is approximately 6000 words long and is recommended for a reading time of over 10 minutes. Table-GPT is a large language model specifically designed for table analysis, unifying tables, natural language, and commands. 1 Abstract Language models like GPT-3 and ChatGPT exhibit exceptional abilities in following various human instructions and executing different tasks, … Read more
TL;DR Perplexity.ai is an AI-based search engine that uses natural language processing technology to help users quickly obtain accurate and concise answers. Unlike traditional search engines, Perplexity.ai can understand complex questions and provide comprehensive, detailed responses. Users can register for free and use it to get real-time intelligent answers by simply inputting questions. It is … Read more
Source: Submission Author: Aksy Editor: Senior Sister Video Link: https://ai.deepshare.net/detail/p_5ee62f90022ee_zFpnlHXA/6 5. Comparison of Models (Model Architectures Section of the Paper) Before the introduction of word2vec, NNLM and RNNLM trained word vectors by training language models using statistical methods. This section mainly compares the following three models: Feedforward Neural Net Language Model Recurrent Neural Net Language … Read more
Source: Submission Author: Aksy Editor: Senior Sister Video Link: https://ai.deepshare.net/detail/p_5ee62f90022ee_zFpnlHXA/6 Article Title: Efficient Estimation of Word Representations in Vector Space Author: Tomas Mikolov (First Author) Unit: Google Conference and Time: ICLR 2013 1. Research Background 1.1 Prior Knowledge Mathematics Knowledge: Calculus in Advanced Mathematics Matrix Operations in Linear Algebra Conditional Probability in Probability Theory Machine … Read more
Microsoft recently released its latest language model Phi-4, which has been open-sourced on Hugging Face, attracting widespread attention. Although Phi-4 is smaller in scale, it is powerful and outperforms larger competitors in reasoning tasks. Overview of the Phi-4 Model Phi-4 is a small language model (SLM) developed by Microsoft Research with 14 billion parameters, focusing … Read more
Original: https://zhuanlan.zhihu.com/p/682253496 Compiled by: Qingke AI Leave a message in the backend ‘ Exchange ‘, Join the NewBee discussion group 1. Background Introduction RAG (Retrieval Augmented Generation) method refers to a combination of retrieval-based models and generative models to improve the quality and relevance of generated text. This method was proposed by Meta in the … Read more
1. RAG (Retrieval Augmented Generation) RAG technology is a method that combines retrieval and generation. It typically relies on two core components: a large language model (such as GPT-3) and a retrieval system (such as a vector database). RAG first uses the retrieval system to extract relevant information from a vast amount of data, then … Read more