Compiled by | Yan Zheng Data & AI entrepreneur, investor Oliver Molander recently joked in a LinkedIn post: “If you had asked AI experts what LLMs were before the launch of ChatGPT in 2022, many might have answered that it’s a law degree.” He added that many people find it hard to accept that AI … Read more
Yunzhong from Aofeisi Quantum Bit | WeChat Official Account QbitAI It has been a full year since ChatGPT and GPT-4 ignited a new round of artificial intelligence revolution. In this year, numerous companies both domestically and internationally have flooded into the “beast arena” of large models, accelerating the iteration and leap of large model technology. … Read more
mPLUG Team Contribution QbitAI | WeChat Official Account New SOTA in Multimodal Document Understanding! Alibaba’s mPLUG team has released the latest open-source work mPLUG-DocOwl 1.5, proposing a series of solutions to tackle four major challenges: high-resolution image text recognition, general document structure understanding, instruction following, and external knowledge incorporation. Without further ado, let’s take a … Read more
Machine Heart Column Machine Heart Editorial Team In the past few months, with the successive releases of major works like GPT-4V, DALL-E 3, and Gemini, “the next step for AGI”—multimodal generative large models have rapidly become the focus of scholars worldwide. Imagine, AI not only chats but also has “eyes” that can understand images, and … Read more
Multimodal fusion aims to integrate information from various modalities to achieve more accurate predictions. Significant progress has been made in multimodal fusion across a wide range of scenarios including autonomous driving and medical diagnosis. However, the reliability of multimodal fusion in low-quality data environments remains largely unexplored. This paper reviews the common challenges and recent … Read more
Machine Heart Report Machine Heart Editorial Team What is the progress of multi-modal large language models?Here are 26 of the current best multi-modal large language models. The focus in the field of AI is shifting from large language models (LLMs) to multi-modal capabilities. Thus, multi-modal large language models (MM-LLMs) that enable LLMs to have multi-modal … Read more
Better integration and exploration of industry data is expected to provide new possibilities for the development of multimodal large models in vertical fields. How can the traditional research advantages of Hong Kong connect with industrial opportunities, and how can international channels collaborate with local resources? By｜《财经》special correspondent in Hong Kong, Jiao Jian Editor｜Su Qi The … Read more
Author: Wang Yonggang, Founder/CEO of SeedV Lab, Executive Dean of AI Academy at Innovation Works The advent of ChatGPT/GPT-4 has completely transformed the research landscape in the NLP field and ignited the first spark towards AGI with its multimodal potential. Thus, the era of AI 2.0 has arrived. But where will the technological train of … Read more
In recent years, Generative Adversarial Networks (GAN) have rapidly developed and become one of the main research directions in the field of machine learning. GAN is based on the idea of zero-sum games, where its generator and discriminator learn in opposition to capture the data distribution of given samples, generating new sample data. A large … Read more
Click the “Expert Knowledge” above to follow for more AI knowledge! [Introduction] Thematic aggregation knowledge is one of the core functions of Expert Knowledge, providing users with systematic knowledge learning services in the field of AI. Thematic aggregation offers users a collection of the essence (Awesome) knowledge materials about the theme from the entire network, … Read more