Hacker News Board Hacker News, browsed like a classic message board
Live data from Hacker News

Overcoming the limits of current LLMs

seanpedersen.github.io

Post reply on HN
Print view View original

61–70 of 111 posts

Re: Overcoming the limits of current LLMs

#61

Post by dang »

totetsu wrote: post #12
RodgerTheGreat wrote: post #3

One of the main factors that makes LLMs popular today is that scaling up the models is a simple and (relatively) inexpensive matter of buying compute capacity and scraping together more raw text to train them. Without large and highly diverse training datasets to construct base models, LLMs cannot produce even the superficial appearance of good results. Manually curating "tidy", properly-licensed and verified dataset…

It’s not unethical if people in positions of privilege and power do it to maintain their rightful position of privilege and power.

Please don't post in the flamewar style to HN. It degrades discussion and we're trying to go in the opposite direction here, to the extent that is possible on the internet.

https://news.ycombinator.com/newsguidelines.html

Re: Overcoming the limits of current LLMs

#62

Post by mitthrowaway2 »

LLMs don't only hallucinate because of mistaken statements in their training data. It just comes hand-in-hand with the model's ability to remix, interpolate, and extrapolate answers to other questions that aren't directly answered in the dataset. For example if I ask ChatGPT a legal question, it might cite as precedent a case that doesn't exist at all (but which seems plausible, being interpolated from cases that do exist). It's not necessarily because it drew that case from a TV episode. It works the same way that GPT-3 wrote news releases that sounded convincing, matching the structure and flow of real articles.

Training only on factual data won't solve this.

Anyway, I can't help but feel saddened sometimes to see our talented people and investment resources being drawn in to developing these AI chatbots. These problems are solvable, but are we really making a better world by solving them?

Re: Overcoming the limits of current LLMs

#63

Post by CamperBob2 »

mitthrowaway2 wrote: post #62

LLMs don't only hallucinate because of mistaken statements in their training data. It just comes hand-in-hand with the model's ability to remix, interpolate, and extrapolate answers to other questions that aren't directly answered in the dataset. For example if I ask ChatGPT a legal question, it might cite as precedent a case that doesn't exist at all (but which seems plausible, being interpolated from cases that do…

These problems are solvable, but are we really making a better world by solving them?

When you ask yourself that question -- and you do ask yourself that, right? -- what's your answer?

Re: Overcoming the limits of current LLMs

#66

Post by pessimizer »

wkat4242 wrote: post #26
linguistbreaker wrote: post #9

Earlier quoted context omitted.

I appreciated a post on here recently that likened AI hallucination to 'bullshitting'. It's coherent, even plausible output without any regard for the truth.

While I have absolutely no issues with the word "shit" in popular terms, I'd normally like to reserve it for situations where there's actually intended malice like in "enshittification". Rather than just an imperfect technology as we have here. Many people object to the term enshittification for foul-mouthing reasons but I think it covers it very well because the principle it covers is itself so very nasty. But that'…

"Bullshitting" isn't a new piece of jargon, it's a common English word of many decades vintage, and is being used in its dictionary sense here.

Re: Overcoming the limits of current LLMs

#67

Post by gessha »

piva00 wrote: post #47
threeseed wrote: post #46

Earlier quoted context omitted.

> properly-licensed and verified datasets is immensely more difficult, expensive Arguably the bigger problem is that many of those datasets e.g. WSJ articles are proprietary and can be exclusively licensed like we've seen recently with OpenAI. So we end up with in a situation where competition is simply not possible.

> Arguably the bigger problem is that many of those datasets e.g. WSJ articles are proprietary and can be exclusively licensed like we've seen recently with OpenAI. > So we end up with in a situation where competition is simply not possible. Exactly, and Technofeudalism advances a little more into a new feud. OpenAI is trying to create its moat by shoring up training data, probably attempting to not allow competitors…

It's landmines no matter how you approach the problem.

If you treat the web as a free-for-all and you scrape freely, you get sued by the content platforms for copyright or term of service violation.

If you license the content, you let the highest bidder get the content.

No matter what happens, capital wins.

Re: Overcoming the limits of current LLMs

#68

Post by dgs_sgd »

darby_nine wrote: post #4

Man it seems like the ship has sailed on "hallucination" but it's such a terrible name for the phenomenon we see. It is a major mistake to imply the issue is with perception rather than structural incompetence. Why not just say "incoherent output"? It's actually descriptive and doesn't require bastardizing a word we already find meaningful to mean something completely different.

I think calling it hallucination is because of our tendency to anthropomorphize things.

Humans hallucinate. Programs have bugs.

Re: Overcoming the limits of current LLMs

#69

Post by TeaBrain »

linguistbreaker wrote: post #57
exmadscientist wrote: post #18

Earlier quoted context omitted.

"Hallucinations" implies that someone isn't of sound mental state. We can argue forever about what that means for a LLM and whether that's appropriate, but I think it's absolutely the right attitude and approach to be taking toward these things. They simply do not behave like humans of sound minds, and "hallucinations" conveys that in a way that "confabulations" or even "bullshit" does not. (Though "bullshit" isn't b…

How about "dream-reality confusion (DRC)" ?

There is no dream-reality separation in an LLM, or really any conception of dreams or reality, so I don't think the term makes sense. Hallucination works fine to describe the phenomenon. LLMs work by coalescing textual information. LLM hallucinations occur due to faulty or inappropriate coalescence of information, which is similar to what occurs with actual hallucinations.

Re: Overcoming the limits of current LLMs

#70

Post by TeaBrain »

darby_nine wrote: post #4

Man it seems like the ship has sailed on "hallucination" but it's such a terrible name for the phenomenon we see. It is a major mistake to imply the issue is with perception rather than structural incompetence. Why not just say "incoherent output"? It's actually descriptive and doesn't require bastardizing a word we already find meaningful to mean something completely different.

The problem with "incoherent output" is that it isn't describing the phenomenon at all. There have been cases where LLM output has been incoherent, but modern LLM hallucinations are usually coherent and well-contructed, just completely fabricated.
Post reply on HN