By / Google TensorFlow Team TensorFlow has evolved into one of the most popular and widely adopted machine learning platforms in the world, and we sincerely thank all the developers and their contributions who have supported us along the way: Researchers: (Predicting earthquake aftershocks, detecting prostate cancer …… ) Developers: (Identifying diseased plants, applications to … Read more
Written by Laurence Moroney, AI Technology Advocate We know that machine learning technology can be used to solve various scenarios (such as healthcare) important tasks, and educators and experts in various fields are guiding and training developers on how to use machine learning technology to solve real-world problems. We are excited to share with everyone … Read more
Yunzhong from Aofeisi Quantum Bit Edited | Public Account QbitAI In today’s era of artificial intelligence, most people pay attention to deep learning technologies, but please do not overlook the understanding of traditional machine learning techniques. In fact, when you truly engage in AI work, you will find that the dependence on traditional machine learning … Read more
The Machine Heart Column The Machine Heart Editorial Team The PreFLMR model is a general-purpose pre-trained multimodal knowledge retriever that can be used to build multimodal RAG applications. The model is based on the Fine-grained Late-interaction Multi-modal Retriever (FLMR) published at NeurIPS 2023 and has undergone model improvements and large-scale pre-training on M2KR. Paper link: … Read more
Interpretation: AI Generates the Future This article introduces the Multimodal Large Language Model (MLLM), its definition, applications using challenging prompts, and the top models that are reshaping computer vision. Table of Contents What is a Multimodal Large Language Model (MLLM)? Applications and Cases of MLLMs in Computer Vision Leading Multimodal Large Language Models Future Outlook … Read more
“Multimodal” refers to the ability to simultaneously process and understand various types of information or data. In the field of artificial intelligence, modality typically refers to the representation or perception of information, such as text, images, audio, and video. For example, humans perceive the world through multiple senses, including sight, hearing, and touch, which is … Read more
In 2024, significant progress has been made in the field of “multimodal + reinforcement learning”. Researchers have proposed various innovative methods to integrate data from different modalities to enhance the performance and applicability of reinforcement learning algorithms. For example, methods mentioned in the literature include utilizing Masked Multimodal Learning to achieve the fusion of visual … Read more
Pan Titanium Technology’s generative AI Agent solution integrates mainstream open-source and closed-source large language models from home and abroad, based on a self-developed Multi-Agent architecture, to build an enterprise-level service ecosystem that provides scenario-based solutions for various government, enterprise, and industry clients in finance, education, and other fields. Background of the Solution 1. Industry and … Read more
Introduction In recent years, the technology of Artificial Intelligence Generated Content (AIGC) has shown great potential in various media fields such as news editing, virtual anchors, and documentary production. This article focuses on the practical application of AIGC technology and discusses how county-level converged media centers can innovate personalized content and improve content production efficiency … Read more
As we all know, “generative AI” has become one of the most well-known selling points in the smartphone industry today. No matter the price segment, smartphones typically promote their integration of “generative AI” features. Some of these features manifest as conversational “voice agents” that can naturally and smoothly interact with users and generate various suggestions, … Read more