9 ms·

It's really easy to get an LLM to hallucinate by asking an open ended question - the type typically answered by a Google search or checking Wikiedpia. However,

It's really easy to get an LLM to hallucinate by asking an open ended question - the type typically answered by a Google search or checking Wikiedpia. However, this is not the best application of LLMs. This criticism is getting old. LLMs are great at: - Text synthesis given all of the facts in a prompt (expand these bullet points) - Summarization (condense this text) - Data extraction (fit this data into this schema) - Fiction (virtual characters, scripts, etc.) They will dramatically change these industries.

morelisp 3y ago
> However, this is not the best application of LLMs It is, however, the commercial application everyone - including search engines! - is implementing.
- iamjackg 3y ago
  To be fair, the ones I've seen use a form of point 1 (giving all facts in the prompt) by allowing for searching the web, which becomes a version of point 2 (summarization).
- substation13 3y ago
  I can see LLMs as a novel front-end for a traditional search engine.
  - morelisp 3y ago
    However, this is not the best application of LLMs.
soperj 3y ago
> - Fiction (virtual characters, scripts, etc.) I've found it bad for this, does not generate something I'd actually read.
- vidarh 3y ago
  It seems to do ok at coming up with starting points or give you options if you're stuck. But the quality of the prose it comes up with is indeed awful. It gets a bit better if you ask it to write in the style of a specific author, but marginally so. I guess maybe it gets to mediocre fan fiction level. That's still pretty impressive, but not very usable for creative writing yet.
  - sharemywin 3y ago
    Don't most create writers have a process? I wonder if there's a series of steps(prompts) that could be used to get it to out put something much better. I know I've used it to write something I would have never even attempted let alone tried to write on my own. It came out ok, but better than I could have done on my own.
    - vidarh 3y ago
      Some do. Others will just sit down and write. But the problem isn't so much that it can't handle plot. That is amenable to process - there are huge numbers of different processes, and one that might work well for GPT is something called the Snowflake method, which is basically iterative refinement. E.g. start with a one line description, expand it to a paragraph, expand each paragraph to a paragraph, then to a page or a few, and eventually to a list of scenes, and write out the scenes. Oversimplified (there's some steps with character sheets etc. too). For that it might well be useful, because you could do one iteration at a time, edit the output to keep/reject ideas and do the next step. But the challenge is that while it might not be "easy", it's the less time consuming part of a novel (certainly has been for me). The time consuming part is writing out the scenes, and the part GPT so far is awful at is the prose. So even if you manage to get it to produce a coherent script setting out what should happen, you still (so far) will have to expect to rewrite the entire thing anyway. That may or may not be useful to you. For my part I suspect I'd write faster from scratch than trying to edit and keep it consistent. That said, given how far it's gotten I wouldn't at all be surprised if it can get to reasonable prose in another couple of versions.
- 3y ago
iforgotpassword 3y ago
Regarding the last point: What I still find the most entertaining is how easily you can change its personality, especially via the system prompt. You can get it to be rather snarky, even sometimes insulting, which makes for hilarious IRC bots.
- EMM_386 3y ago
  In less then 20 tokens, you can get ChatGPT simply via the web interface to become snarky and swearing like a drunken sailor. And it is indeed hilarious at times.
jhp123 3y ago
LLMs also hallucinate during summarization tasks, adding topics that were not in the original
- mediaman 3y ago
  I've built internal systems that do summarization based on knowledge retrieval systems for specific nonpublic corporate information. With GPT-4, I find very little hallucinating. It very rarely deviates from the source material. Every time I've found something unexpected, there was a problem in the source material provided to the model.
  - hammyhavoc 3y ago
    "very little" is still an unacceptable amount for most fields. Quantify "very little" over what time period, variations of use, fail states, sample size.

morelisp 3y ago

> However, this is not the best application of LLMs It is, however, the commercial application everyone - including search engines! - is implementing.

iamjackg 3y ago
To be fair, the ones I've seen use a form of point 1 (giving all facts in the prompt) by allowing for searching the web, which becomes a version of point 2 (summarization).
substation13 3y ago
I can see LLMs as a novel front-end for a traditional search engine.
- morelisp 3y ago
  However, this is not the best application of LLMs.

soperj 3y ago

> - Fiction (virtual characters, scripts, etc.) I've found it bad for this, does not generate something I'd actually read.

vidarh 3y ago
It seems to do ok at coming up with starting points or give you options if you're stuck. But the quality of the prose it comes up with is indeed awful. It gets a bit better if you ask it to write in the style of a specific author, but marginally so. I guess maybe it gets to mediocre fan fiction level. That's still pretty impressive, but not very usable for creative writing yet.
- sharemywin 3y ago
  Don't most create writers have a process? I wonder if there's a series of steps(prompts) that could be used to get it to out put something much better. I know I've used it to write something I would have never even attempted let alone tried to write on my own. It came out ok, but better than I could have done on my own.
  - vidarh 3y ago
    Some do. Others will just sit down and write. But the problem isn't so much that it can't handle plot. That is amenable to process - there are huge numbers of different processes, and one that might work well for GPT is something called the Snowflake method, which is basically iterative refinement. E.g. start with a one line description, expand it to a paragraph, expand each paragraph to a paragraph, then to a page or a few, and eventually to a list of scenes, and write out the scenes. Oversimplified (there's some steps with character sheets etc. too). For that it might well be useful, because you could do one iteration at a time, edit the output to keep/reject ideas and do the next step. But the challenge is that while it might not be "easy", it's the less time consuming part of a novel (certainly has been for me). The time consuming part is writing out the scenes, and the part GPT so far is awful at is the prose. So even if you manage to get it to produce a coherent script setting out what should happen, you still (so far) will have to expect to rewrite the entire thing anyway. That may or may not be useful to you. For my part I suspect I'd write faster from scratch than trying to edit and keep it consistent. That said, given how far it's gotten I wouldn't at all be surprised if it can get to reasonable prose in another couple of versions.
3y ago

iforgotpassword 3y ago

Regarding the last point: What I still find the most entertaining is how easily you can change its personality, especially via the system prompt. You can get it to be rather snarky, even sometimes insulting, which makes for hilarious IRC bots.

EMM_386 3y ago
In less then 20 tokens, you can get ChatGPT simply via the web interface to become snarky and swearing like a drunken sailor. And it is indeed hilarious at times.

jhp123 3y ago

LLMs also hallucinate during summarization tasks, adding topics that were not in the original

mediaman 3y ago
I've built internal systems that do summarization based on knowledge retrieval systems for specific nonpublic corporate information. With GPT-4, I find very little hallucinating. It very rarely deviates from the source material. Every time I've found something unexpected, there was a problem in the source material provided to the model.
- hammyhavoc 3y ago
  "very little" is still an unacceptable amount for most fields. Quantify "very little" over what time period, variations of use, fail states, sample size.