As a maker in the AI space, how might I stay up to date and keep learning with the latest info, tools, and techniques? It can be intimidating. I made this document for myself to organize resources I find helpful. The 🌊 Feed is a way to find the latest, and the 📚Courses are deep dives.
If there's been other helpful resources you check regularly or refer to you'd recommend to check out, please let me know! Consider this a living document, I’ll update this as I find new info sources, courses, and articles that jump out to me. Thanks for checking it out 🙌
If there is one resource I would recommend, it is [1hr Talk] Intro to Large Language Models by Andrej Karpathy (Nov 2023). This is suitable for both general audiences new to LLMs, and technical audiences, and gives a broad overview that is both concrete and more higher level and looking to the future.
🌊 Feed
check these regularly
|
Links |
Notes |
| TLDR AI |
newsletter, archive |
The best source I’ve found. Allows for quick scanning and ranges from product news to relevant info for builders |
| Huggingface |
huggingface spaces, models |
Go to models and spaces and see what’s trending, play with things on spaces |
| Replicate |
Replicate explore models |
Go on and see the trending models |
| AI Agenda |
newsletter |
4x/week newsletter, for me what’s most interesting is the funding rounds at the end seeing what new companies are emerging and growing |
| Import AI |
newsletter |
weekly, gets into recent research too |
| Simon Willison |
blog |
fantastic dev + blogger, covers topics including AI |
| Ethan Mollick |
twitter, substack |
Always innovating with AI and thinking up new experiments |
| AI Exchange |
newsletter |
quick newsletter 2x/week on AI updates |
| Axios AI+ |
newsletter |
weekdays |
| AK |
twitter |
lots on the research |
| Two Minute Papers |
youtube |
videos of some of the latest research coming out around AI |
| Ben’s Bites |
newsletter |
a firehose of AI info |
📚 Courses
- fast.ai — Making neural nets uncool again. fastai is a deep learning library which provides practitioners with high-level components that can quickly and easily provide state-of-the-art results in standard deep learning domains, and provides researchers with low-level components that can be mixed and matched to build new approaches.
- Neural Networks: Zero to Hero — A course by Andrej Karpathy on building neural networks, from scratch, in code.
- Let's build GPT: from scratch, in code, spelled out — Andrej Karpathy: We build a Generatively Pretrained Transformer (GPT), following the paper "Attention is All You Need" and OpenAI's GPT-2 / GPT-3.
- ChatGPT Prompt Engineering for Developers — you will learn how to use a large language model (LLM) to quickly build new and powerful applications.
- Hugging Face Diffusion Models Course — In this free course, you will:👩🎓 Study the theory behind diffusion models, 🧨 Learn how to generate images and audio with the popular 🤗 Diffusers library, 🏋️♂️ Train your own diffusion models from scratch, 📻 Fine-tune existing diffusion models on new datasets, 🗺 Explore conditional generation and guidance, 🧑🔬 Create your own custom diffusion model pipelines
- The LangChain Cookbook - Beginner Guide To 7 Essential Concepts
- OpenAI Cookbook — lots of tutorials building with OpenAI tools, straight from OpenAI.
- Learn Prompting — Learn how to use ChatGPT and other AI tools to accomplish your goals using our free and open source curriculum, designed for all skill levels!
- Cultural Automation with Machine Learning — Parag Mital. This course explores the past, present, and future of how artists engage with digital media through its remix and adaptation of increasingly more automated algorithms.
🎥 Videos + Talks
- Intro to Large Language Models — 1 hour talk by Andrej Karpathy: This is a 1 hour general-audience introduction to Large Language Models: the core technical component behind systems like ChatGPT, Claude, and Bard. What they are, where they are headed, comparisons and analogies to present-day operating systems, and some of the security-related challenges of this new computing paradigm.