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523 points noperator | 2 comments | | HN request time: 0.001s | source
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jackdawed ◴[] No.44492832[source]
I've noticed a lot of people are converging on this idea of using AI to analyze your own data, the same way the companies do it to your data and serve you super targeted content.

Recently, I was inspired to do this on my entire browsing history, after reading https://labs.rs/en/browsing-histories/ I also did the same from ChatGPT/Claude conversation history. The most terrifying thing I did was having an LLM look at my Reddit comment history.

The challenges are primarily with having a context window large enough and tracking context from various data sources. One approach I am exploring is using a knowledge graph to keep track of a user's profile. You're able to compress behavioral patterns into queryable structures, though the graph construction itself becomes a computational challenge. Recently most of the AI startups I've worked with have just boiled down to "give an LLM access to a vector DB and knowledge graph constructed from a bunch of text documents". The text docs could be invoices, legal docs, tax docs, daily reports, meeting transcripts, code.

I'm hoping we see an AI personal content recommendation or profiling system pop up. The economic incentives are inverted from big tech's model. Instead of optimizing for engagement and ad revenue, these systems are optimized for user utility. During the RSS reader era, I was exposed to a lot of curated tech and design content and it helped me really develop taste and knowledge in these areas. It also helped me connect with cool, interesting people.

There's an app I like https://www.dimensional.me/ but the MBTI and personality testing approach could be more rigorous. Instead of personality testing, imagine if you could feed a system everything you consume, write, and do on digital devices, and construct a knowledge graph about yourself, constantly updating.

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nottorp ◴[] No.44492917[source]
> Instead of optimizing for engagement and ad revenue, these systems are optimized for user utility.

Are they, or instead they will help keeping you in your comfort cage?

Comfort cage is better than engagement cage ofc, but maybe we should step out of it once in a while.

> During the RSS reader era, I was exposed to a lot of curated tech and design content and it helped me really develop taste and knowledge in these areas.

Curated by humans with which you didn't always agree, right?

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janalsncm ◴[] No.44495817[source]
> Are they, or instead they will help keeping you in your comfort cage?

I’ve been paying close attention to what YouTube shorts/tiktok do. They don’t just show you the same genre or topic or even set of topics. They are constantly in an explore-exploit pattern. Constantly trying to figure out the next thing that’ll keep your attention, show you a bunch of that content, then on to the next thing. Each interest cluster builds towards a peak then tapers off.

So it’s not like if you see baking videos it’ll keep you in that comfort zone forever.

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nottorp ◴[] No.44501854[source]
But you're describing the engagement cage, while I'm just pointing that you need to be careful not to escape from it just to get trapped inside the comfort cage.
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1. Karrot_Kream ◴[] No.44503867[source]
Is there a rigorous definition of "engagement cage" or is the term just HN-tuned engagement bait? (:

Fundamentally content discovery is always an explore-exploit loop. What you tune the loop with is what makes it useful for any given purpose.

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2. nottorp ◴[] No.44520585[source]
> Fundamentally content discovery is always an explore-exploit loop

Is it? Or only when you do it for profit?