GitHub/quartz
1
0
Fork 2
mirror of https://github.com/jackyzha0/quartz.git synced 2025-12-21 03:44:05 -06:00
Code Issues Actions Packages Projects Releases Wiki Activity

Honcho Primer Typos

Browse Source
This commit is contained in:
Vineeth Voruganti 2024-04-22 12:20:43 -07:00
parent 8e5da25b81
commit 0bf35412ea
1 changed files with 2 additions and 2 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

4
content/blog/A Simple Honcho Primer.md
View File

@ -31,7 +31,7 @@ If you've heard of [Retrieval Augmented Generation](https://en.wikipedia.org/wik
Behind the scenes, Honcho learns about users as people--[[User State is State of the Art|richly modeling identity]]. It seeks to understand their beliefs, hopes, dreams, history, interests, and preferences. Behind the scenes, Honcho learns about users as people--[[User State is State of the Art|richly modeling identity]]. It seeks to understand their beliefs, hopes, dreams, history, interests, and preferences.
It then acts as [[Introducing Honcho's Dialectic API|an oracle to each user]], allowing apps ask for any personal context they need to improve UX and giving them access to a social cognition layer. It then acts as [[Introducing Honcho's Dialectic API|an oracle to each user]], allowing apps to ask for any personal context they need to improve UX and giving them access to a social cognition layer.
## Why We Built Honcho ## Why We Built Honcho
^x125da ^x125da
@ -49,7 +49,7 @@ But it's not intuitive for a few reasons:
- AI app builders are [[Machine learning is fixated on task performance|still focused on]] just getting general tasks to work - AI app builders are [[Machine learning is fixated on task performance|still focused on]] just getting general tasks to work
- LLMs' [[LLMs excel at theory of mind because they read|potential to personalize]] is still under-appreciated - LLMs' [[LLMs excel at theory of mind because they read|potential to personalize]] is still under-appreciated
- Historic examples of personalized apps usually just leverage our activity & engagement data - Historic examples of personalized apps usually just leverage our activity & engagement data
- Those examples tend target only base user desire, lead to addictive behavior, & have poor privacy records - Those examples tend to target only base user desire, lead to addictive behavior, & have poor privacy records
Still, when interacting with an AI app, there's a sense that it *should* be getting to know us. In fact, we're often surprised when we realize it's not learning about us over time. And probably annoyed at having to start over. Still, when interacting with an AI app, there's a sense that it *should* be getting to know us. In fact, we're often surprised when we realize it's not learning about us over time. And probably annoyed at having to start over.