![]() Of the Haiku command, shown in the screenshot above, Daniel says “For some odd reason, this prompt often achieves levels of compression exceeding more explicit prompts such as ‘summarize’ or ‘tl dr’. This Twitter thread from Readwise cofounder Daniel Doyon offers a thorough overview of each of the commands, the thought process behind it, and what they’ve found it’s particularly good for. ![]() Joined by Simon Eskildsen for the quarter as a sort of reader-and-hacker-in-residence, the Readwise team came up with a command palette of 10 GPT-3-powered actions that use highlighted text as a springboard. Their plunge into generative is particularly thrilling for me because this is a pragmatic team, not a hype-driven one-so you know it’s got to be useful (or at least truly fun) to meet their standards. With Explainpaper, GPT-3 knows enough about the domain and is good enough at summarization that I can get a solid definition (in this case, of “English constituency parsing”) without breaking focus.Īs a Readwise user and fan for the past half-decade, I’ve been watching the development of Readwise Reader with great interest. I especially appreciate how highlighting keeps me in context: the technical terms in question are domain-specific, so generally when I would open a new browser tab to look them up, I’d end up on a blog post rather than a dictionary entry-and soon enough, my browser window would be full of tiny tabs. Having recently attempted the manual version of making myself look up every single unfamiliar-to-me term in a machine learning paper abstract as a way of deepening my own context before diving in to the paper itself, this is definitely a better experience. I can select text almost absentmindedly-as with the “+++” command in Lex, this saves me from the pain of “admitting” that I’m stuck-and then a few seconds later the righthand pane fills up with helpful explanatory text. Explainpaper and Readwise Reader are two products that take highlights to the next level as a springboard for generative action.Įxplainpaper is delightful in its straightforward utility. ![]() (Thank you to Nathan for the Lex invite!) Highlight as springboardĪ summoning spell works great when you have a text insertion point to work with, but what about when you don’t? When reading text on a device, highlighting is a natural springboard to action: it’s how we select words to copy into another context, identify the text span in Google Docs that we’re planning to add a comment to, or simply augment the text with a formatting shift-italics, bold, underline, or a colorful highlight. So why not type a few pluses and see what happens? Definitely a why-didn’t-I-think-of-that moment. You’re stuck, you want to get unstuck, but the frustration is just below your consciousness-not something you’re ready to admit. etc.,” “dot dot dot” expression that feels totally natural in context. (Try typing in Google Docs and it’ll bring up a menu of people you can mention, docs you can reference, and “building blocks” you can add in.) Typing “+++” in Lex is a sort of a “blah blah blah,” “etc. You see this in slash commands in Notion and similar products, and in inline insertion-a now-common pattern we helped introduce through Quip. When typing is the main user action in an application, there’s power in letting people stay in the flow and do more at the text insertion point. Lex’s product insight has the ring of truth based on all that I know about word processors from working on one for five years. Some people are close, but my intuition is they tend to make it too complicated.” The core AI-powered interaction happens at the text insertion point: “The AI wasn’t quite right at first, but we refined it to the simplest possible experience: just type +++, and GPT-3 will give you a few sentences it thinks might come next.” But nobody yet has an interface that’s a familiar full-featured word processor. ![]() That’s it!” Further, “If you want to use GPT-3 there are plenty of places to do it, including on OpenAI’s website directly. ![]() In Nathan Baschez’s recounting of “ How Lex Happened,” he shares “What I realized was special about Lex-and this realization only came gradually, over the course of a few weeks-was that it embodied a simple idea that somehow no one has exactly nailed yet: online word processing + gpt-3. Lex is “a word processor with artificial intelligence baked in,” built by the team behind Every. ![]()
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |