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The End of O rganizing

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Summary

This article discusses how AI models such as GPT-3 can be used to organize notes and unlock the value of them. These models can automatically tag and link notes, write research reports, and resurface key information from previous notes. This makes searching through old notes unnecessary, and helps to create an intimate thought partner that uses everything you’ve ever written to make you smarter as you type. AI models can truly turn notes into a second brain.

Q&As

What is GPT-3 and how will it help with note-taking?
GPT-3 is a large language model (LLM) that can automatically tag and link notes together with no manual work required, enrich notes as they are written, and resurface key information from previous notes into a CoPilot-like experience for note-taking.

What makes organizing notes so difficult?
Organizing notes is difficult because we don't know what we'll use them for in the future. We put things into notes because we could eventually use them in many different ways, so it is hard to find a single organizing system for them. Additionally, looking at old notes is cognitively expensive and not rewarding enough, as they are often hard to understand and take a while to parse.

How can AI models help solve the note organizing problem?
AI models can automatically tag and link notes together with no manual work required, enrich notes as they are written, and resurface key information from previous notes into a CoPilot-like experience for note-taking.

What kinds of automated taxonomies can AI models create?
AI models can create automated taxonomies of notes that make it easier to navigate them, such as an automatically updating list of every book read in a year. They can also create taxonomies on the fly for new projects, so as needs change, notes can reorganize themselves into new views.

How can large language models help synthesize and present notes at the right time and in the right format?
Large language models can help synthesize and present notes at the right time and in the right format by automatically writing and presenting a report outlining key quotes and ideas from books relevant to the task at hand. They can also create an autocomplete experience that uses the note archive to try to fill in whatever is being written, suggesting quotes, evidence, and meeting notes to help make a point.

AI Comments

👍 I think this article is great and it offers excellent insights on the potential of AI models to revolutionize the way we take notes and organize them.

👎 This article is overly optimistic and fails to address the potential pitfalls of relying on AI models to manage our notes.

AI Discussion

Me: It talks about how large language models like GPT-3 could make organizing our notes easier. It suggests that AI models can automatically tag and link notes together and even synthesize notes into research reports. It also suggests an autocomplete experience where our note archive can help us make better decisions and write better emails.

Friend: That's really interesting! It sounds like these AI models could really revolutionize the way we organize our notes. Do you think they could really replace manual organizing?

Me: It's hard to say. AI models can certainly make organizing easier, but manual organizing has its benefits. For example, the act of organizing can help reinforce understanding and open up creative solutions. So, I think AI models can be helpful, but it's important to recognize the value of manual organizing as well.

Action items

Research and explore AI models like GPT-3 to see how they can be used to automatically tag and link notes.
Experiment with creating automated taxonomies of notes to make them easier to navigate.
Try out tools like Mem.ai to see how they can be used to create a CoPilot-like experience for note-taking.

Technical terms

GPT-3: Generative Pre-trained Transformer 3, a large language model developed by OpenAI.
Entity Recognition: A type of natural language processing (NLP) task that identifies and classifies named entities in text into predefined categories such as the names of persons, organizations, locations, expressions of times, quantities, monetary values, percentages, etc.
Rube Goldberg Machine: A complex contraption in which a series of devices that perform simple tasks are linked together to produce a domino effect in which activating one device triggers the next device in the sequence.
Taxonomies: A hierarchical system of organizing and classifying things.
LLM: Large Language Model.
CoPilot: A feature of GitHub that helps developers write code faster by suggesting code snippets and providing contextual information.
AI: Artificial Intelligence.