Thanks for tagging me. Basically, overall the bot is very well received, so I think the consensus is that it’s more useful than not.
As for the sometimes not-ideal summaries, unlike tools with similar purpose, this does not use an AI LLM which makes things up all the time, but instead does an analysis of most used keywords, extracts the sentences around and puts them together.
This has one (in my opinion) very important advantage: If something is wrong in the summary (like the “she tells NPR” out of nowhere), you immediately know, while you generally have no way to know when something is wrong with an AI generated answer, because it blends wrong info with the correct one seamlessly.
I don’t watch my bot anymore, but in the first two months I read every summary and found only one case where it put the sentences in such an order that something different than what the article was talking about was said in the summary (this is generally statistically improbable). There were quite a few less-than-useful summaries, but overall I was satisfied in about 80% of cases, which was good enough for me.
I always viewed it exactly as @Kissaki@beehaw.org said:
When reading the summary with it in mind, that it’s a bot summary, not a human summary, it’s acceptable and still useful. Text is not necessarily coherent. And when it isn’t, it can indicate other content.
Tagging @theangriestbird@beehaw.org so that he gets notified about the answer.
@rikudou@lemmings.world is the contact point for this bot - you could reach out if they don’t respond to being tagged
Thanks for tagging me. Basically, overall the bot is very well received, so I think the consensus is that it’s more useful than not.
As for the sometimes not-ideal summaries, unlike tools with similar purpose, this does not use an AI LLM which makes things up all the time, but instead does an analysis of most used keywords, extracts the sentences around and puts them together.
This has one (in my opinion) very important advantage: If something is wrong in the summary (like the “she tells NPR” out of nowhere), you immediately know, while you generally have no way to know when something is wrong with an AI generated answer, because it blends wrong info with the correct one seamlessly.
I don’t watch my bot anymore, but in the first two months I read every summary and found only one case where it put the sentences in such an order that something different than what the article was talking about was said in the summary (this is generally statistically improbable). There were quite a few less-than-useful summaries, but overall I was satisfied in about 80% of cases, which was good enough for me.
I always viewed it exactly as @Kissaki@beehaw.org said:
Tagging @theangriestbird@beehaw.org so that he gets notified about the answer.