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
In recent years, the demand for artificial intelligence (AI) software has significantly increased among organizations of all sizes, as they seek to leverage AI to remain competitive. This article details a range of AI software and related services, such as generative AI, machine learning, natural language processing, computer vision, and deep learning, aimed at solving … Read more
Machine Heart Release Author: Tony, Researcher at Zhuiyi Technology AI Lab Everyone knows that language models like BERT have been widely used in natural language processing. However, a question sometimes arises: do these language models truly understand language? Experts and scholars have different opinions on this. The author of this article elaborates on this topic … Read more
1、Qwen 2.5-Max Model Overview 1.1 Model Introduction Alibaba Cloud officially launched the Tongyi Qwen 2.5-Max on January 29, 2025, this is a large-scale Mixture of Experts (MoE) model that demonstrates exceptional performance and potential in the field of natural language processing. As an important member of the Qwen series, Qwen 2.5-Max stands out in comparison … Read more
Author: PicturesqueOriginal: https://zhuanlan.zhihu.com/p/13700531874 >>Join the Qingke AI Technology Exchange Group to discuss the latest AI technologies with young researchers/developers Technical Report: https//arxiv.org/abs/2412.15115 Github Code: https//github.com/QwenLM/Qwen2.5 0 Abstract Qwen2.5 is a comprehensive series of LLMs designed to meet various needs. Compared to previous versions, Qwen2.5 has significant improvements in both the pre-training (Pretrain) and post-training (SFT, … Read more
Introduction The development of large language models (LLMs) is advancing rapidly, with each major update potentially bringing significant improvements in performance and extending application scenarios. In this context, the latest Qwen2.5 series models released by Alibaba have garnered widespread attention. This technical report provides a detailed overview of the development process, innovations, and performance of … Read more
New Media Manager Author Introduction Liú Shūlóng, currently an engineer in the technology department of Daguan Data, with interests primarily in natural language processing and data mining. Word2vec is one of the achievements of the Google research team, and as a mainstream tool for obtaining distributed word vectors, it has a wide range of applications … Read more
word2vec was launched by Google in 2013. The methods for obtaining word vectors, CBOW and Skip-gram models, are elaborated in the paper “Efficient Estimation of Word Representations in Vector Space.” The strategies for efficiently training models, Hierarchical Softmax and Negative Sampling, are discussed in “Distributed Representations of Words and Phrases and their Compositionality.” Since the … Read more
This Article Overview: 1. Background Knowledge Word2Vec is a type of language model that learns semantic knowledge from a large amount of text data in an unsupervised manner, and is widely used in natural language processing. Word2Vec is a tool for generating word vectors, and word vectors are closely related to language models. Therefore, we … Read more
word2vec Word2Vec is a model used to generate word vectors. These models are shallow, two-layer neural networks trained to reconstruct linguistic word texts.The network represents words and needs to predict the input words in adjacent positions. In Word2Vec, under the bag-of-words model assumption, the order of words is not important. After training, the Word2Vec model … Read more