I decided to go through all my posts on AI and pull out information that would be useful to anyone wanting to learn more about generative AI (often referred to as gen AI or genAI) and the LLMs they run. If you have used chatGPT, you have used genAI. But there’s much more to the technology than what you find on that site. To see what I mean, click on any of the blue underlined text and you will be taken to a site talking about something to do with gen AI.

Enjoy!

Tutorials/Introductions: for people just getting started with gen AI, I found these links useful: how generative AI works, what is generative AI, how LLMs works,  sentence word embeddings which kinda shows  how LLM works, best practices for prompt engineering with openai api,  a beginners guide to tokens, a chatGPT cheat sheet,  demystifying tokens: a beginners guide to understanding AI building blocks, what are tokens and how to count them, how to build an llm rag pipeline with llama 2 pgvector and llamaindex and finally this: azure search openai demo. (Some of these are introductory for technical people – don’t worry if you don’t understand all of them.)

For people who are comfortable with github, this is a really good repo / course on generative AI for beginners. (and check out these other repositories here, too). This here on the importance of responsible AI. and here’s a step by step guide to using generative AI in your business, here.

Prompts and Prompt Engineering: if you want some guidance on how best to write prompts as you work with gen AI, I recommend this, this, this, this, this, this, this, and this.

Finally:  Here’s the associated press AI guidelines for journalists. This here’s a piece on how the  Globe and Mail is using AI in the newsroom. Here’s a how-to on using AI for photo editing. Also, here’s some advice on writing better ChatGPT prompts. How Kevin Kelly is using  AI as an intern, as told to Austin Kleon. A good guide on  how to use AI to do practical stuff.

Note: AI (artificial intelligence) is a big field incorporating everything from vision recognition to game playing to machine learning and more. Generative AI is a part of that field. However nowadays when we talk of AI people usually mean gen AI. A few years ago it was machine learning and before that it was expert systems. Just something to keep in mind as you learn more about AI and gen AI in particular.