Welcome to the AI & Automation Academy! This is a six-week course that will introduce you to the world of generative AI, how we're approaching it at Hearst Newspapers and how you can use it in your work.
- AI & Automation Academy
Module 1: Introduction ⤴️
In this introductory module, we'll take a 30,000-foot view of the generative AI landscape, how we're approaching generative AI, what we'll be going over in future modules and more. No programming knowledge is required for this module.
- What do I mean by "AI" and "Automation"?
- What's the value proposition of generative AI?
- What has the Central Devhub built so far?
- How have LLMs come to be? What are their limitations?
- Our guidelines for using generative AI?
- Course outlook.
- What are capstone projects?
- Sign up for OpenAI account: We're going to begin working with OpenAI's playground and API next week. When you sign up, you'll receive $5 in OpenAI bucks to use for when we're experimenting.
- Sign up for Github Copilot ✨on Monday✨: We're also going to touch on Github Copilot next week. But don't sign up until the day before. Copilot's free trial is time-based, and I want to maximize the amount of time you have it during this course.
- Post in the AI and Automation Academy Slack channel with what you're interested in learning in the context of the next module — so anything to do with prompting, OpenAI, Github Copilot and the like.
- Post one interesting use of generative (not predictive) AI in the wild in the course's Slack channel. It doesn't have to be from a media outlet. It doesn't have to be something good. It could be something that went terribly wrong.
- Beginner’s prompt handbook: ChatGPT for local news publishers | Joe Amditis x Center for Cooperative Media: Skim this. You don't need to read all of it. You might even get by with just reading the headers. I just don't want y'all to come in completely cold next week. We'll be covering much of what's here.
- AI-enhanced development makes me more ambitious with my projects | Simon Willison: I just want you to read the intro. It echoes how I feel when I'm using generative AI to accomplish a task I've never done before.
- What OpenAI Really Wants | Steven Levy x WIRED: This is totally optional because I know not everyone wants to read a 9,400-word profile, but I'm telling y'all, it's an excellent encapsulation of OpenAI's history and what they've become.
- Generative AI: What journalists need to know about ChatGPT and other tools | Knight Center: This is also optional because I know not everyone wants to watch/listen to an hour-long conversation about generative AI.
Where does Ryan go to stay up to date with the rapidly evolving world of generative AI? Here's a list of information sources in no particular order:
- The New York Times: My favorite writers that cover AI at the NYT are Cade Metz and Kevin Roose. Roose also co-hosts the Times' Hard Fork podcast with Platformer's Casey Newton where they frequently discuss generative AI topics.
- WIRED magazine: WIRED also does a top notch job at covering the big ideas that are swirling this subject. Steven Levy is my favorite writer there.
- OpenAI's Blog: It's good to hear what's new from OpenAI straight from the horse's mouth.
- Simon Willison's blog: Simon's blog is way more technical than other sources. I admire the ambitious projects he takes on using LLMs and adjacent technologies. It feels like he's always pushing the envelope.
- Newsroom Robots | Nikita Roy: A podcast? About AI use inside of newsrooms around the world? What else could you ask for!
- One Useful Thing | Ethan Mollick: A lovely newsletter by Ethan Mollick, a professor at the University of Pennsylvania’s Wharton School. His thinking has had an impact on my thinking.
- AI Snake Oil | Arvind Narayanan, Sayash Kapoor: There's a ton of hype around AI — specifically generative AI — these days. Arvind and Sayash aim to "dispel hype, remove misconceptions, and clarify the limits of AI." It's vital to be realistic with what these technologies are capable of.
- Hacker News: Hacker news encompasses a lot, so you'll have to hunt out links relevant to generative AI. But when you do, the ideas and discussions are incredibly valuable.
- Emergent Mind: This link aggregator is all about AI.
- Reddit: Specifically /r/openai and /r/chatgpt.
- OpenAI Discord: I prefer the structured nature of Reddit's threads, but you can find valuable discussion and inspiration on OpenAI's official Discord.
✨Quick aside:✨ You might see this list and think "Ryan, there are too many sources to keep up with! I'm not going to check every site every damn day". Let me us this opportunity to recommend using an RSS reader. RSS is often forgotten about, but not by me. It's an insanely powerful tool in processing a deluge of news. With the exception of OpenAI's Discord, all of the listed information sources can be loaded into an RSS reader. I personally use Feedbin, but a solid free option is Feedly.
OK, back to business.
Hearst has it's own set of policies regarding generative AI, but I think it's useful to see how other media outlets are handling the technology:
- Standards around generative AI | The Associated Press: I'm a huge fan of the following line when it comes to communicating with your peers about the outputs of generative AI: "Any output from a generative AI tool should be treated as unvetted source material. AP staff must apply their editorial judgment and AP’s sourcing standards when considering any information for publication."
- Data and AI ethics principles | Reuters:
- The Guardian’s approach to generative AI | The Guardian:
Each module I'm going try to share with you a quirky, weird, off-the-wall link to something that uses or touches on generative AI — just to keep things fun. This week, I direct your attention to pepperoni hug spot from Pizza Later.
Module 2: OpenAI and prompt engineering ⤴️
Today, we're diving deeper into what OpenAI has to offer, specifically the features and functionalities of the OpenAI playground. My aim is to demystify the technical jargon, guide you through best practices, and set you up to smoothly transition into the programming aspects of this technology. By the end, you'll have a strong foundation for building simple LLM-powered applications.
- Why use OpenAI's playground over chatGPT?
- How to navigate the playground interface.
- How does OpenAI charge for their API?
- Vocab lesson: Tokens, context window, temperature, stop sequences, Top P, frequency penalty, presence penalty.
- What are the different models? And how can they change over time?
- What are fine-tuned models?
- What are legacy models? (Quickly touch on the token probabilities feature)
- Breakdown of what roles are.
- High-level overview of prompting best practices. Everything based on "GPT best practices" from OpenAI.
- Submitting a prompt and receiving a response.
- How to work with OpenAI's moderations endpoint.
- Introduction to OpenAI's Cookbook.
- Capstone project discussion.
- If we have time: chatGPT Advanced Data Analysis plugin
- I would like for each of you to post a specific example of when you struggled with a prompt in the past by EOD Monday in the AI and Automation Academy Slack channel. If you don’t have a specific example, then post a specific prompting concept you’re unclear about.
- GPT best practices | OpenAI: I don't know if I'm going to go over every little thing covered in this document. You should read through it from top to bottom if you want to become better at prompting.
- Prompt Engineering vs. Blind Prompting | Mitchell Hashimoto: Some extra reading on prompt engineering.
- Pragmatic techniques to get the most out of GitHub Copilot | Microsoft: I don't know if we're going to have enough time to go over Copilot in this module, but I still want y'all to learn Copilot best practices. Allison Weins and Burke Holland go over how to use Copilot effectively — probably better than I would.
- Building an app in 18 minutes with Github Copilot Chat: Again, not sure if I'm going to be able to do Copilot justice today. But I want y'all to see as many example of the power of copilot. In this clip, Github's CEO builds a complete snake game relying only on Github Copilot and Copilot Chat. Think of the chat functionality as if VS Code had a built-version of chatGPT. You still have to go on a waitlist if you want access to it, but I'm sure you'll want to get on it as soon as you can after watching this clip.
- 35 Ways Real People Are Using A.I. Right Now | Francesca Paris and Larry Buchanan, NYT: See how a bunch of folks with a wide-variety of backgrounds are using generative AI in their daily lives. Just some light inspiration.
- [Optional] Interested in learning how AI learns? Watch this animated video from CGP Grey.
- Check out this conversation I had with chatGPT a few weeks ago. It demonstrates how I go about interacting with chatGPT, including how I format my messages, how I provide chatGPT with reference material and how I collaborate with chatGPT to ultimately come to a solution.
Module 3: Prompting & Github Copilot ⤴️
Link to Github Copilot slideshow
- Using OpenAI's Playground interface, create one prompt that serves a practical purpose for something in your role. Share it in the academy Slack channel. To do this from the playground, click "Share" in the upper right hand corner. Name your prompt. Copy the link and paste it into the channel. When you share your link, please share what best practice(s) you used.
- Lurk OpenAI's Cookbook repo. There are lots of examples and resources in that repo — many of which I'm going to highlight in this course.
- Try to use Github Copilot in your own projects!
Module 4: Embeddings ⤴️
A high-level overview of what embeddings are, how they can be used on their own, how they complement LLMs and more.
Brainstorm a project that uses embeddings. It can be a project that uses embeddings on their own or in conjunction with LLMs. Share your idea in the academy Slack channel.
Module 5: LangChain ⤴️
Coming soon!
Module 6: Slack bots ⤴️
Coming soon!