1. Definition and Core Features An AI Agent is an intelligent system capable of perceiving its environment through sensors, making autonomous decisions, and utilizing tools to perform tasks. Its core features include: Autonomy: Operates without continuous human intervention. Goal-Oriented: Breaks down tasks and plans around predefined objectives. Adaptability: Dynamically adjusts strategies through feedback mechanisms. Interactivity: … Read more
In the field of large language models, the pre-training + fine-tuning paradigm has become an important foundation for deploying various downstream applications. Within this framework, the use of low-rank adaptation (LoRA) methods for efficient fine-tuning of large model parameters (PEFT) has resulted in a large number of reusable LoRA adapters tailored for specific tasks. However, … Read more
The AIxiv column is a section published by Machine Heart that features academic and technical content. Over the past few years, the AIxiv column has reported on more than 2000 pieces of content, covering top laboratories from major universities and companies worldwide, effectively promoting academic exchange and dissemination. If you have excellent work to share, … Read more
We are very excited to share some amazing advancements in bringing the latest generative AI and large language models (LLMs) to edge computing. Since the introduction of Transformers and NVIDIA’s launch of the Ampere GPU in 2020, we have witnessed a rapid increase in the scale and intelligence of models, approaching human levels. This has … Read more
Deep learning dominates various fields and fundamentally changes human society. Efficiency is a key factor in democratizing deep learning and expanding its application scope. This has become increasingly important as Moore’s Law slows down and the pace of model size expansion accelerates. We need efficient algorithms and systems to help bridge this gap. In this … Read more
Click Follow us by clicking the blue text above This paper introduces a modular blueprint and the X1 framework aimed at advancing the development of accessible and scalable Reasoning Language Models (RLMs) by combining reinforcement learning and hierarchical reasoning strategies, simplifying the design and deployment of RLMs, enhancing efficiency, and reducing costs. Paper Introduction By … Read more
By | Li Dongshuo, Founder, Chairman, and President of UMU Source | Training Magazine July Issue It is not easy to elaborate on the definition of Artificial Intelligence (AI). The reason is that AI has the characteristic of phased development, forming new shapes and connotations over time. Three years ago, when people talked about AI, … Read more
· Desktop Robot Development Practical Course· Exploring the Application Potential of Edge AI and Large Language Models 01 Course Background With the acceleration of digital transformation across various industries, edge AI and cloud-based large model technologies are leading a new wave of innovation in smart devices. This year, the Ministry of Industry and Information Technology … Read more
Source: DeepHub IMBA This article is approximately 2400 words long and is recommended for a 5-minute read. In this article, we will see how to use vLLM with multiple LoRA adapters. We all know that using LoRA adapters can customize large language models (LLMs). The adapters must be loaded on top of the LLM, and … Read more
MLNLP community is a well-known machine learning and natural language processing community at home and abroad, covering domestic and international NLP graduate students, university teachers, and corporate researchers. The vision of the community is to promote communication and progress between academia, industry, and enthusiasts in natural language processing and machine learning, especially for beginners. Selected … Read more