Technology

I can believe that it won't happen in 2024.

I am pretty confident that in the long run, pretty much everyone is gonna wind up there, though. Like, part of the time spent searching is identifying information on the page and combining from multiple sources. Having the computer do that is gonna be faster than a human.

There are gonna be problems, like attributability of the original source, poisoning AIs via getting malicious information into their training data, citing the material yourself, and so forth. But I don't think that those are gonna be insurmountable.

It's actually kind of interesting how much using something like an LLM looks like Project Babel in the cyberpunk novel Snow Crash. The AI there was very explicit that it didn't have reasoning capability, could just take natural-language queries, find information, combine it, and produce a human-format answer. But it couldn't make judgement calls or do independent reasoning, and regularly rejected queries that required that.

Though that was intended as an academic tool, not something for the masses, and it was excellent at citing sources, which the existing LLM-based systems are awful at.

but LLMs, a very specific and especially inscrutable class of AI which has been designed for "sounding convincing", without care for correctness or truthfulness.

I think that I'd put it in a slightly less-loaded way, and say that an LLM just produces content that has similar properties to its training content.

The problem is real. Frankly, while I think that there are a lot of things that existing LLM systems are surprisingly good at, I am not at all sure that replacing search engines will be it (though I am confident that in the long run, some form of AI system will be).

What you can't do with systems like the ones today is to take one data source and another data source that have conflicting information and then have the LLM-using AI create a "deep understanding" of each and then evaluate which is more-likely truthful in the context of other things that have been accepted as true. Humans do something like that (and the human approach isn't infallible either, though I'd call it a lot more capable).

But that doesn't mean that you can't use heuristics for estimating the accuracy of data and that might be enough to solve a lot of problems. Like, I might decide that 4Chan should maybe have less-weight as a solution, or text that ranks highly on a "sarcastic" sentiment analysis program should have less weight. And I can train the AI to learn such weightings based on human scoring of the text that it generates.

Also, I'm pretty sure that an LLM-based system could attach a "confidence rating" to text it outputs, and that might also solve a lot of issues.

I'm currently wondering what their plans are for updating these LLMs.

Who wants to create the content to feed these machines without a recognition, retribution or a perceived act of 'good'? If I were to maintain a blog with a particular midly but important obscure topic, would I devote the time to have ChatGPT or Copilot make a summary?

Now, the LLMs need to ingest a lot more than 'one blog'... If someome knows, please let me know.

I doubt this crazy effort with such resource consumption is to create a snapshot of what the internet was in the 2020s.