Building an intelligent agent typically involves several steps, from problem definition, model selection, training, to deployment. This process applies to various types of agents, including those used in reinforcement learning, planning, and robotic control. Here are the general steps for building an agent: 1. Define the Problem and Task Before constructing an agent, it is … Read more
Introduction Three months ago, OpenAI launched its latest work – OpenAI O1, which quickly became a hot topic in the AI community. The biggest highlight of OpenAI O1 is its ability to reason like humans, meaning it can not only simply match known data patterns when dealing with complex problems, but also execute a process … Read more
DeepSeek-R1 uses reinforcement learning to significantly enhance the model’s inference capabilities. In tasks such as mathematics, coding, and natural language reasoning, its performance rivals that of OpenAI’s official version o1.The small model distilled from DeepSeek-R1 effectively inherits the reasoning patterns learned by the large model.This article primarily tests DeepSeek-R1-Distill-Llama-8B-GGUF using Llama Edge. Welcome to experiment … Read more
Introduction The development of large language models (LLMs) is advancing rapidly, with each significant update potentially bringing substantial performance improvements and expanding application scenarios. Against this backdrop, Alibaba’s latest release of the Qwen2.5 series models has garnered widespread attention. This technical report provides a detailed overview of the development process, innovations, and performance of Qwen2.5, … Read more
In December 2024, the paper “Qwen2.5 Technical Report” from Tongyi Qianwen was released. This report introduces Qwen2.5, a series of comprehensive large language models (LLMs) designed to meet diverse needs. Compared to previous iterations, Qwen 2.5 has made significant improvements in both pre-training and post-training phases. In terms of pre-training, the high-quality pre-training dataset has … Read more
The differences and connections between AI Agents and Agentic AI AI Agents and Agentic AI are two important yet distinct concepts in the field of artificial intelligence, with both connections and significant differences between them. Connections 1.Technical Foundation: Both are built on artificial intelligence and machine learning technologies, relying on capabilities such as perception, reasoning, … Read more
By / Li Xihan, Google Developers Expert This article is excerpted from “Simple and Brutal TensorFlow 2”, reply “Manual” to get the collection. It should have been introduced long ago, the deep reinforcement learning in TensorFlow, yes, it is finally done! This article will introduce the process of implementing the Q-learning algorithm using TensorFlow in … Read more
This article is reproduced with permission from the WeChat public account Paper Weekly (ID: paperweekly). Paper Weekly shares interesting papers in the field of natural language processing every week. “In-depth Analysis: GAN Models and Their Progress in 2016” [1] provides a detailed introduction to the progress of GANs over the past year, which is highly … Read more
How to Obtain Resources 1. Follow the public account below, and click【Like】 and 【View】 2. Click 【Get Course】 to obtain this material. Resources are from Baidu Cloud Disk:《Introduction and Practice of LangGraph Based on Large Model Agent》 Introduction and Practice of LangGraph Based on Large Model Agent In the field of artificial intelligence, with the … Read more
We are transitioning from a “play-to-earn” model to a more exciting era: games that are rich in genuine fun and infinitely scalable. Author: Sid, IOSG Ventures Original Title: IOSG Weekly Brief | The Integration of Gaming, AI Agents, and Cryptocurrency #260 Cover: Photo by Lorenzo Herrera on Unsplash This article is for educational exchange only … Read more