Instead of filtering keywords this ranks the content using Pangram. But it's also pretty effective at filtering content about AI. Turns out that a lot of LLM tooling projects have LLM written project descriptions/blog posts.
It's amazing to see how many of the "AI hurts my brain" posts are apparently written by an LLM.
Great point. I think the key is differentiating between "prompt generated" content vs "AI as a Topic" content and then being able to toggle them at will.
I am not averse to prompt-generated content, but it should be marked and quoted as such, just like any other reference. If it's not, it's like the author is double-cheating.
In fact there are no shortage of comments here on HN, especially open-ended questions that could've been plugged into a bot for an answer. Avoiding LLMs altogether is foolhardy. It's a matter of balance, and being able to write a good prompt is a skill - no mental atrophy there. Content derived from non-English sources using English-based LLMs is also an interesting area. [1]
It's possible to obtain AIaaT from https://aibriefs.news/ and then prune it elsewhere if need be. But the best aggregators like that may be machine-generated with a lot of human moderation. I wonder if that is 100% machine generated.
Nice! I was considering doing this but the Pangram API is very expensive. Then I considered training my own model and I fortunately stopped at the edge of that rabbit hole.
Yea very expensive (hence me siphoning another page haha).
Im trying to get something cheaper to work, Pangram has some nice docs on how to build something like their service https://github.com/pangramlabs/EditLens, they even have training data online.
The harm a missclassification carries is much lower for a hn post than a masters thesis, so we might be fine with a worse model.
Yeah agree, Pangram puts out interesting material. I recently came across their v4 technical report and they shared a lot more than I would have expected them to.
But see, here I am back at the edge of the rabbit hole, and you're trying to pull me in. I refuse!
If you do end up training a model, send me an email and maybe I can tie it into the site.
Will do, thanks for hcker.news btw, has been my main mobile client for couple of months. Of all things i like the changelog most, its nice to have a quick view about new stuff, especially if the website changes somewhat faster than usual.
If you really wanted to optimize something involving living consciousness beings like a machine, at least you should consider things like the need to take a piss as a hard constraint and design the system around it.
Don't get me wrong I love factorio like the next guy and understand the idea behind your thinking, but there should be limits to that thinking in the real world. And if that doesn't convince you consider the efficiency loss of a depressed worker with a urinary tract infection.
Honestly - and I don't mean that as an insult - I hope for you to experience (just once) the loss of dignity that not being able to visit the restroom on your own decision will give you. Might make you realize the hell this kind of thinking leads to.
// Honestly - and I don't mean that as an insult - I hope for you to experience (just once) the loss of dignity that not being able to visit the restroom on your own decision will give you. Might make you realize the hell this kind of thinking leads to.
I am not insulated and I think my post was received stronger than I intended, with my point being simply that there are jobs where physical presence at a given moment is more significant than in knowledge work for example (say whatever you want, bus drivers and others defacto hold it in if possible to avoid disruptions at least here in NYC)
And to be frank even at my job which is very removed from bus driving or warehouse work there are moments where I would feel self-pressure to hold it in short of a dire emergency.
(Eg, I am on stage at a speaker panel or something like that where my absence would be visible and disruptive)
Maybe... if run locally with full transparency into the prompts (including system etc) and independent benchmarks for the models (i.e. tests on how eager they are about selling me stuff)
But even in this hypothetical world I would still have a hard time teaching an LLM what I find important in a product. Not everything can be captured in easy to compare numbers. "Does the device creak under pressure?", "What's the one weirdly unergonomic thing about it you only notice after weeks of using?"... Stuff like that. Things which are easy to miss even if the model ingests all relevant reviews about the product, because it might not stand out, but might be important for me.
Here is a detailed explanation from Pangram how their scoring works https://www.pangram.com/research/how-it-works
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