this post was submitted on 14 Jun 2026
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I don't really run into a lot of the issues I have heard of people having with AI since I primarily use DeepSeek as an actual search engine. It's odd actually, I am "pro-AI" but have never generated a single image with AI. I just never felt like it, ever. I insulated myself from places Instagram slop reposts can find me, long ago, for completely non-AI reasons lol. It's like I don't care about anything other than text, and I want to handle it all myself, so AI just acts as a targeting reticule. I didn't even notice DeepSeek is text-only for months.
Tried adding AI summaries to articles I post, but I just didn't see the point after a day-and-a-half. I still read them all anyways and would proofread the summaries. Do people just slap those on because they can? Journalistic writing already has a pyramidal structure, summaries summarize the summary at the start, & then you read... the second summary. Why?
Using Kimi to edit entire Orgmode (task management) notebooks is pretty dope. It's too scary though, what if it loses something? Generating scripts is cool too, but I need to learn the scripting languages, it's not hard for what I need to do, so why put myself in a position of being unable to debug? Will save work later though. Barely scratched the surface of this, a few weeks of random stabs at it when I have spare time.
I have a lot of projects in mind for local + metered + talking to phone (apps like Tasker + OffGrid) stuff, been feeling it out. I just want to be able to find book quotes without the precise phrasing, to extract key points from books people send me to find where they detail things related to whatever supporting arguments I was presented with, meta-analysis of citations (did this book primarily cite western news articles and high-falutin (yes this is a gabe rockhill reference nobody else says that) academies?)
Deepseek is very useful for projects like "hey how do I avoid reinventing the wheel with my homelab setup, i want to experiment with Deepseek" π€£
So, not a ton. The robotics and computational engineering models are much more impressive, no?
For this, agentic would be able to make scripts that test the data integrity and make sure nothing is missing in various ways. Simple enough to run Python
That sounds good, I'll give it a go in a separate note space before considering merging still π
I find by themselves the models, especially current-gen ones, are pretty bad at editing text. They still don't really grasp what it entails lol, because they are not aware of their limitations. And it seems that current models are trained mainly for technical (coding) tasks over anything else, so I feel it's only going to get worse in those applications.
But I've had some success using a test suite afterwards to confirm data integrity. Counting lines is one such method: you just compare the number of lines between the before and after and it gives you an idea of how much was cut off, but it's basic. An LLM in agentic can set up a full test suite to really understand what changed or not statistically, and then is able to bring back stuff from the older revision to ensure integrity and that it didn't do too much. There's a lot of other things it can use to test the data, and you can ask it for cross-tests too: two different tests that test the same thing, but do it in two completely different ways (like calculating "x*x" and then "x^2").