AI writes daily research notes: how to select chunks

AI writes daily research notes: how to select chunks

2023-08-11

There are a number of options for how to select chunks

A: Random

B: Recently updated chunks

C: Chunk of recently created new pages

D: The older the update date/time, the lower the probability

E: Vector search on previous note

I think A or D would be appropriate under the condition that it be done automatically once a day.

In B and C, we see things from the same perspective as humans.

The need for "AI to see and develop what humans are seeing now."

If that's what you're looking for, don't wait for a once-a-day opportunity to make an explicit request to the AI.

E is "AI reads and thinks about Scrapbox in its own interest, independent of humans".

This is not a bad streak.

The problem is that naive implementation is where you read the same thing over and over again.

Need an implementation that remembers "what you've read in the past" and leaves it out.

On the other hand, "Do I really have to read something once and never again?" I mean, well, that's not true.

Well, maybe the last 100 or so.

Added on 8/14/2023

You could decide based on the amount of notes you had last time.

0 means random

If there are a lot of them, it's unlikely that they are derived from a single existing chunk, so using the results of a vector search won't result in "all the same ones".

If the previous note has N tokens, there will be zero additional chunks to begin with.

I'd love to put one in at random.

Added on 2023-08-18

If there are a lot of them, it's unlikely that they are derived from a single existing chunk, so using the results of a vector search won't result in "all the same ones".

It never happened.

I could abstract the word here and get out of it.

A is the easiest to implement, so I experimented with this implementation.

As a result, Hatena Diary became a hit, which worked rather well for me!

It's imported because it's worth zero if it's not a search hit.

but there are no Scrapbox-like links, so there are no Scrapbox-like suggestions.

This has resulted in a situation in which the product is contained but underutilized.

I don't want to parse Hatena notation and change it to Scrapbox notation because it's too much trouble.

AI will interpret this in natural language and make summary notes, a good "dig back".

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