AI & I How an AI Researcher Uses ChatGPT and Notion AI - Ep. 3 with Linus Lee
Dec 13, 2023
Linus Lee, a research engineer on Notion's AI team, discusses how AI can enhance human creativity. He shares his philosophy that language models should augment our agency, not replace it. Linus dives into effective prompting techniques, demonstrating creative tools like an AI chatbot and Varna, a system for mixing image styles. He stresses the importance of providing context for better AI responses and explores the nuances of prompt engineering versus scripting. Join him as he illustrates how AI tools can shape our creative outputs.
01:14:19
Models As Probability Functions
- Linus Lee views language models primarily as mathematical functions that predict probability distributions rather than agents with will.
- That perspective shapes building interfaces that preserve human agency instead of replacing it.
Struggling To Make An Ugly Image
- Linus tried to generate an intentionally ugly image but found image models biased toward aesthetic outputs, which reduced his control.
- That experience showed how tool design can unintentionally remove user agency.
Think Of Embeddings As Coordinates
- Embeddings map text or images to high-dimensional coordinates that cluster similar semantics close together.
- Thinking spatially about embeddings enables mathematical manipulation of concepts for precise control.
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Intro
00:00 • 1min
Linus' agency-first AI philosophy
01:04 • 3min
How tools shape creative agency
04:07 • 3min
Embeddings as spatial controls
07:10 • 7min
Varna demo: sliders for image concepts
14:35 • 6min
Thought calculator vs human simulacrum
20:55 • 6min
Personal chatbot demo and design tradeoffs
26:47 • 6min
Prompting: scripting vs prompt engineering
32:50 • 6min
Use ChatGPT iteratively for ideas
38:27 • 2min
ChatGPT for programming and research help
40:05 • 4min
Provide context and goals for better answers
44:08 • 44sec
Custom instructions and personal preferences
44:52 • 6min
Continue writing and 'vibe' checks
50:52 • 3min
Book-recommendation workflow in Notion
53:46 • 6min
When Notion AI outperforms generic chat
59:20 • 3min
Q&A bots for teams and knowledge search
01:02:41 • 3min
Advanced prompt techniques and chain of density
01:06:10 • 3min
GPT-4 Turbo behavior and prompting quirks
01:09:24 • 5min
Outro
01:14:10 • 0sec
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TL;DR: Today we’re releasing a new episode of our podcast How Do You Use ChatGPT? I go in-depth with Notion research engineer Linus Lee on how he uses ChatGPT and Notion AI to maximize creative control. Watch on X, YouTube, or Spotify.
You might think that being an AI researcher would mostly involve solving complicated programming problems and thinking through mathematical equations. Instead, a big part of the job is rewriting parts of your prompts in ALL CAPS in order to make sure the AI model you’re working with follows your directions. “All caps works!” Linus Lee told me in this interview. “If you look at OpenAI's system prompts for a lot of their tools, all caps works.”
Linus is a research engineer at Notion who works on its AI team, prototyping new experiences, like a Q&A chatbot. He is a deep thinker who is obsessed with building AI that enables human creativity and agency. He came on the show to talk about how AI might augment our thinking, how he thinks about prompting to get the best results, and how he uses ChatGPT and Notion AI in his work and life.
I first interviewed him a year ago, when he showed off dozens of AI prototypes he’d been building to try to understand the future of this technology. Our latest interview is a mixture of theory and practice. Linus talks about how the tools we use shape the work we can create and what the future of AI-driven interfaces might be. We watch him demo personal tools he’s built, like an AI chatbot that he communicates with over iMessage. And we peek over his shoulder to see his chats with ChatGPT to understand how he talks to it to get the best results.
Here’s a taste of what we talk about. Read on for more analysis from me at the bottom.
- Using AI to maximize agency. Linus talks a lot about the ways our tools shape our agency as thinkers and creatives—and how AI might be used to enhance rather than reduce our agency.
- AI as a “thought calculator.” Linus borrows a phrase from the popular tech blogger Simon Willison to illustrate dueling points of view on the ultimate goal of AI: is it meant to be a simulacrum of humans or a “thought calculator,” a way to enhance human imagination and creativity?
- Personal prototypes he’s built. Linus regularly experiments with AI on the weekend. He shows us a chatbot he built that works over iMessage, and a new interface for image generators that gives him much better control over their output.
- Better prompting. We go over simple yet powerful techniques for getting the best answer out of AI models—like starting with general queries first, and repeatedly asking the model to answer the same question.
- Using AI for vibe checks. AI is great for reflecting the vibes of books, people, places—and even files on your computer. Linus talks about how he uses ChatGPT to get quick vibe checks that allow him to make decisions.
- Book recommendations. We pit ChatGPT head-to-head against Notion AI to see which can best capture our reading taste. And just when ChatGPT seems like it’s coming out on top, Linus makes a convincing case for Notion AI’s special skill set as an organizational tool that already knows how its users work.
What do you use ChatGPT for? Have you found any interesting or surprising use cases? We want to hear from you—and we might even interview you. Reply here to talk to me!
Miss an episode? Catch up on my recent conversations with writer Nat Eliason and Gumroad CEO Sahil Lavingia and learn how they use ChatGPT.