Imagine a system that can accurately determine whether you are cooking, cleaning, or exercising, solely based on sensor data from your smartphone. The research team at Apple is making this scenario a reality by developing a novel multimodal sensor fusion method based on large language models (LLMs) for human activity recognition.This research was conducted in … Read more
Hello, everyone, I am your Yuan Ge. Recently, a new term has emerged in the AI community—”AI Agent”. It sounds quite mysterious, like something out of a sci-fi movie. I thought to myself, isn’t this just giving AI “hands” and “brains” so it can work on its own? As a hardcore tech enthusiast who loves … Read more
AI-Agent is like breaking down large models into smaller details, decomposing them into independent agents, similar to how biological organisms are composed of individual cells, where each cell contains genes. To be more precise: each cell carries the entire organism’s genes, all embedded with holographic images within the agents. Each AI-Agent based on large models … Read more
In the current era of large language models (LLMs), building an efficient inference framework from scratch allows us to gain a deeper understanding of the underlying logic of AI-generated content. C++, with its close-to-hardware and low-overhead characteristics, has become the preferred language for implementing lightweight LLM inference. This article will integrate the core design ideas … Read more
As AI becomes increasingly popular, its applications are becoming more widespread. This article shares some knowledge points related to the implementation of AI! If we say that large language models (LLMs) provide AI with a “smart brain,” then AI Agents are the “hands and feet” that enable this brain to perceive the environment, plan decisions, … Read more
🤖 Self-Evolution: How LLM Achieves Breakthroughs in General Domain Capabilities through “Three Kingdoms Kill”? — In-Depth Analysis of Multi-Agent Evolve (MAE) 🌟 Introduction: Breaking Through the “Data Drought” and “Reward Wall” in LLM Training Large Language Models (LLMs) have shown tremendous potential in reasoning tasks, but their capability enhancement is often constrained by two core … Read more
[Image] Life is like a river. It is neither centralized logical reasoning nor a dramatic one-time event; it is a continuous evolutionary process, a river. The same goes for agents. At the beginning of 2023, as we delved deeper into the development of LLMs, we believed: “The core of this AI revolution lies in agents; … Read more
1. BackgroundRecently, I have been learning some knowledge related to AI Agents. The purpose of writing this article is to clarify the context of the knowledge I have acquired, making it easier for deeper learning in the future.2. What is LLMLLM (Large Language Model) technology has developed rapidly in recent years, and there are now … Read more
Background of Agentic AI The initial product form of LLM was the ChatBot led by OpenAI, supported by the Transformer architecture large language model, which initially focused on AI applications in the field of language text. LLM ChatBots have profoundly changed our work and life. With the popularization of LLM technology in toC and toB … Read more
Introduction When AI first emerged, it was simply a chatbot interface. Over time, it has gradually added functionalities, such as internet connectivity, tool configuration, and custom workflows for agents. With agents, AI can be applied to various real-world business scenarios, marking a process of gradual evolution and implementation. For instance, AI programming, which we programmers … Read more