Knowledge Base section
学习路径
12 articles in this section, sourced from the WaytoAGI Feishu knowledge base.
OpenAI & Langchain Guide for AI App Developers
This guide for AI application developers compiles official resources from OpenAI and Langchain, covering core functionalities like API libraries, models, text completion, image generation, and fine-tuning. It helps developers quickly get started building AI-powered applications.
AI for Beginners: A Practical Getting-Started Guide
A beginner-friendly introduction to AI applications, curated from easy-to-follow videos and articles. Learn the fundamentals of popular AI tools and start using them with confidence.
Must-Read AI Classics for Beginners: a16z's Recommended Resources
A curated collection of a16z's top AI introductory resources, offering clear explanations of modern AI concepts like Transformers and diffusion models, plus foundational materials on neural networks, backpropagation, and embeddings. Ideal for beginners and practitioners seeking a structured understanding of the AI revolution.
AI Courseware & Resources: PPTs, Presentations, and Insights
A curated collection of AI-related courseware, PPTs, speeches, and company analyses covering prompt engineering, AI agents, the AGI era, innovative startups, product building, and business insights. Ideal for AI learners and practitioners seeking practical knowledge and strategic perspectives.
AI Learning Path for Beginners: Courses and Tools
This guide provides a clear learning path for AI beginners, covering AI application usage, application development (OpenAI official guide), and model introduction. It also recommends practical tools like Kimi to help you quickly get started with artificial intelligence.
Startup & Life Wisdom: Classic Essays from Tech Legends
A curated collection of timeless essays on entrepreneurship and life from industry icons like Sam Altman, Paul Graham, Marc Andreessen, Kevin Kelly, Mu Li, and Fei-Fei Li. Topics span startup playbooks, work methodologies, product-market fit frameworks, and life optimization strategies for founders and thinkers.
What Does ChatGPT Actually Do, and Why Does It Work?
ChatGPT generates text by predicting the probability of the next word, using a neural network trained on massive amounts of human text. The temperature parameter controls randomness, directly shaping the creativity and variability of its outputs.
How Stable Diffusion Works: A Beginner-Friendly Explanation
Explore how Stable Diffusion transforms random noise into stunning images through a step-by-step denoising process, neural networks, and latent space magic. Understand the core mechanisms behind this popular AI art generator.
Large Language Model (LLM) Zone
A comprehensive LLM beginner's guide covering principles, multimodal, applications, deployment, training, architecture, etc., suitable for AI developers and learners.
OpenAI Articles Collection: GPT-4, o1, o3-mini, AGI Plans & More
A curated collection of OpenAI articles covering founder interviews, technical reports, model releases (GPT-4, o1, o3-mini, GPT-4.5), AGI plans, RLHF, and insights from WIRED, Andrej Karpathy, Lilian Weng, Sam Altman, and others.
State of GPT: Karpathy's Training Pipeline Explained
Andrej Karpathy's talk breaks down the four-stage training process for GPT assistants: pretraining, supervised fine-tuning (SFT), reward modeling, and reinforcement learning. It reveals how large language models work and how to use them effectively.
Transformer Model Explained: How GPT-3, BERT, and T5 Work
Introduced by Google in 2017, the Transformer architecture revolutionized deep learning with its attention mechanism, solving RNN parallelism issues. It powers major LLMs like GPT-3, BERT, and T5.
Sourced from the WaytoAGI Feishu knowledge base. English pages are AI-translated and continuously revised.