Artificial Intelligence

repo: owainlewis/awesome-artificial-intelligence
category: Theory related: Deep Learning · Machine Learning

Awesome Artificial Intelligence

A curated collection of must-use, actively maintained resources for building and shipping AI systems.

Focus: AI engineering (RAG, agents, evals, guardrails, deploy) plus the best books, guides, papers, and a carefully selected set of tools.

🏛 Core Resources (Evergreen)

The foundations — these will still be valuable five years from now, even if today’s tools are gone.

📚 Books

Modern & Practical

• [Designing Machine Learning Systems](https://www.oreilly.com/library/view/designing-machine-learning/9781098107956/) — Scalable, maintainable ML pipelines (Chip Huyen).
• [Generative Deep Learning (2nd Edition)](https://www.oreilly.com/library/view/generative-deep-learning/9781098134174/) — GANs, VAEs, diffusion models (David Foster).
• AI Engineering — End-to-end AI product building (Chip Huyen).
• 100 Page Language Models Book — This book guides you through the evolution of language models, starting from machine learning fundamentals.

Foundational

• Artificial Intelligence: A Modern Approach — Comprehensive AI theory (Russell & Norvig).
• Deep Learning — Neural networks & architectures (Goodfellow, Bengio, Courville).
• [Reinforcement Learning: An Introduction (2nd Edition)](https://web.stanford.edu/class/psych209/Readings/SuttonBartoIPRLBook2ndEd.pdf) — RL fundamentals (Sutton & Barto).

🏗 AI Engineering

Frameworks and design patterns for building robust, production-grade AI systems.
Personal note: you don't need tons of frameworks — start with simple LLM calls and work up.

📖 Guides & Playbooks

• Building Effective Agents (Anthropic) — ⭐ Patterns, pitfalls, and tradeoffs for designing AI agents.
• OpenAI Agents Guide — Practical guide on building agents
• Google AI Agents Paper - Practical guide to building AI agents from Google
• Google Agents Companion Paper - Guide from Google
• OpenAI Cookbook — Example code, recipes, and best practices for working with OpenAI APIs.
• LLM Engineer Handbook — A goldmine of useful links for AI engineers

🤖 Frameworks

• PocketFlow — Extremely minimalist AI agent framework in just 100 lines of code. Fantastic way to learn.
• Google ADK — Google's Agent Development Kit (Python, Java). Great local development experience + A2A + MCP.
• Pydantic-AI — Typed, structured LLM orchestration framework built on Pydantic models for safe, predictable outputs.
• LangGraph — Build multi-agent workflows with stateful graphs on top of LangChain.
• CrewAI — Agent orchestration with structured tasks and human-in-the-loop controls.
• AutoGen — Microsoft’s framework for multi-agent conversation and collaboration.

📦 Retrieval-Augmented Generation (RAG)

• LlamaIndex — Data framework for ingesting, indexing, and querying private data with LLMs.
• Haystack — Open-source search/RAG framework with modular pipelines.
• Docling — Great library for ingesting any kind of document for RAG ⭐

Evals

• OpenAI Evals — OpenAI's framework for writing evals

📄 Landmark Papers

Research that shaped modern AI — worth reading to understand the "why" behind today’s architectures.

• Attention Is All You Need — Transformer architecture.
• Scaling Laws for Neural Language Models — Model/data/compute scaling.
• Language Models are Few-Shot Learners — GPT-3 capabilities.
• Constitutional AI — Safer model alignment.

🎓 Courses

Learn from the best — structured content for every level.

Beginner

• [Google Generative AI Learning Path](https://www.cloudskillsboost.google/paths/118)
• Hugging Face LLM Course
• Fast.ai — Practical Deep Learning

Intermediate / Advanced

• Stanford CS324: Large Language Models
• Full Stack Deep Learning
• MIT 6.S191: Intro to Deep Learning

Focused

• DeepLearning.AI Short Courses
• Google Deepmind| Introduction to Reinforcement Learning
• Karpathy’s LLM Zero-to-Hero
• Neural Nets - Zero-to-Hero

📰 Newsletters

Stay current with AI developments without drowning in noise.

• The Rundown AI
• AlphaSignal
• Superhuman AI
• AI Engineer

⚡ Tools

Tools for building and deploying AI applications.

💬 Models

• ChatGPT — Best for general coding + reasoning.
• Claude — Best for long-context analysis and structured thinking.
• Gemini — Best for Google ecosystem integration.
• Perplexity — Best for quick research with live citations.
• Cohere — Best for enterprise LLMs with strong retrieval-augmented generation APIs.
• Mistral — Best for lightweight, high-performance open-weight models.
• Qwen — Best for multilingual and Chinese-first applications.
• DeepSeek — Best for efficient, cost-optimized large models with competitive reasoning.

👨‍💻 Code & Developer Tools

• Claude Code — IDE extensions with long-context code edits.
• GitHub Copilot — In-IDE code completion, chat, and refactors.
• Cursor — LLM-powered IDE for multi-file edits and codebase-aware chat.

🎨 Multimedia AI Tools

🖼 Image

• ChatGPT-4o Image Generation — Integrated image creation with style control.
• Midjourney — Artistic and photorealistic images and video.
• Adobe Firefly — Integrated into Creative Cloud.
• Ideogram — Precise, legible text in generated images.
• Flux — High-res, prompt-editable images.

🎥 Video

• Kling — Cinematic, realistic video generation.
• Google Veo 3 — High-quality video with synchronized audio.
• Runway — Video editing + generation.

🎙 Audio

• ElevenLabs — High-quality text-to-speech.
• Suno — AI music from text prompts.
• Aiva — Music composition for media.