4. Dialog with long documents.

Searching via keywords is fraught because sometimes you can’t remember the exact term you used, even if the meaning is roughly the same.

Personalized LLMs that live on your hard drive and access your existing data may be a valuable application.

Summaries are another area where LLMs seem to excel.

Good summaries, especially those fine-tuned to your particular needs, might be a good way of navigating the large information loads we often face in knowledge work.

Many readers found benefits in using LLMs to figure out jargon and terms used within a particular community in a way that dictionary definitions often fail to elucidate.

• A major difficulty in following expert thinking is that most expert-level text is written for other experts.

Concepts are unexplained, context is lacking and jargon abounds.

This means that most people must rely on translators, such as general-market nonfiction or science...

• By far, the most common use readers reported was using an LLM as a personal tutor.
• Asking ChatGPT to explain tricky concepts, unfamiliar code or problems seems like an area where LLMs might do alright.
• Challenge explanations that don’t jive with what you’ve read in the book ...

The author doesn't seem to be sure to use LLM's here for making study plan if you are already an expert or have enough experience.

He suggests that ChatGTP might be useful when you are going to learn a completely new subject and when you no idea of how to break the curriculum.

The next most common way people used LLMs to learn better was as a language tutor. This seems like a task LLMs are well-equipped for. Whatever their other flaws, they can produce grammatically correct text.

The place LLMs seem to work really well is at the fringes of a programmer’s expertise.

Many programmers said that they found AI helpful in getting starting hints in unfamiliar languages or tools.

Their base of programming experience allowed them to make sense of and implement the o...