Comment by MattRogish
8 hours ago
I'd have to imagine there are wildly diminishing marginal returns to additional SFT/post-training passes.
There are a bounded number of (useful) derivations/combinations of Duff's device.
If Frontier Labs wish to reduce hallucinations on factual things, they will have to hire people (or the data providers will need to) to do fundamental research above and beyond what is available in extant literature and the web. IE if the LLMs want to lower precision error, they need to go out and actually find more expertise. If the wikipedia page for Pompey lacks data, where are they going to get it from? How would they even _identify_ that the page has holes?
Yes, they can digitize more books but that is untrustworthy data - if there were enough eyeballs on a particular work, it would be in the internet. If it's not, they'd need to hire the experts themselves. They need expert reviewers in virtually every interesting topic, which fundamentally is an intractable problem, especially since things change all the time. Maybe even uninteresting topics, too?
I dunno, it doesn't seem to me "more data" is the magic bullet here. Yeah, it will "help" but we're already on the flat part of the S shaped curve.
My take from trying to understand this stuff is some sort of algorithmic improvement is necessary to get another step change in how well LLMs perform in this area. I could be wrong!
As a side gig, I write novel software that solves problems no existing software does, that existing LLMs have difficulty reproducing, purely for the purpose of existing as LLM training data.
There are journalists being hired to write Atlantic-worthy articles that exist only as LLM training data, because they're getting paid more than the Atlantic would pay them for it.
It's insane.
Yes, they are hiring the experts themselves. To create new knowledge above and beyond what's on the internet. To be locked away as LLM training data.
The largest characteristic of all of this new data is it is targeted at LLM's weak points.
It's not just more data, it's custom tutorials built for what LLMs struggle at.
I'm not saying they are not trying - I'm saying we're inventing new problems faster than any Lab can:
1) Identify the gaps
2) Determine how to fix them
3) Implement a fix (especially if that fix is: identify and find experts)
4) And judge the result
How do they know [person] is an expert in [some field]? How do they find that person? How many experts are necessary to give the right information? How do we evaluate the results, especially if it's novel?
You can find a lot of people who disagree on many topics, and those turtles go all the way down.
I'm not in disagreement that your work will help reduce hallucinations and improve model performance! It is.
I predict (I hope I'm wrong!) that we're going to hit some asymptote that is not at 0% hallucinations (and I would even put a substantial nonzero probability that "overall" hallucination rate bottoms out at some minimum and then slowly grows because we just can't keep up with the new garbage we throw at it).
> How do they know [person] is an expert in [some field]? How do they find that person?
You just stumbled upon billion dollar businesses: Mercor, micro1, Scale AI, Surge AI, etc
> How do they know [person] is an expert in [some field]? How do they find that person?
They have a PhD from a top school, they are a licensed attorney, they are a licensed physician, a board certified cardiologist, etc.
They are constantly recruiting from these populations with well-paying side gigs.
> 4) And judge the result
That's what they pay the experts for. And to have experts review the other experts with peer review.
> You can find a lot of people who disagree on many topics, and those turtles go all the way down.
Which is why everything has to be well-calibrated and not just a hot take - a well reasoned opinion any expert would find fair.
Noone is really caring about hallucinations on point facts these days though, it is much more about complex reasoning tasks. Can they move the bar on the complexity of software LLMs do on their own? Can they get to a point where LLMs can begin to replace physicians? Financial advisors? Actuaries? etc.
13 replies →
1. How did you land the side gig? Mercor or a lessor known brand?
2. What criteria do such vendors typically require?
I've done Mercor and other brands - the contracts move around, since the labs want the vendors to know they're just vendors and have to compete with each other. It seemed to be roughly resume and interview similar to getting hired at a senior role at FAANG or adjacent.
What kind of programs? Can you give an example of the tasks?
I cannot give examples.
For the more interesting contracts, I create examples from whole cloth.
jmalicki says many things, among them being
"As a side gig, I write novel software that solves problems no existing software does,"
and
"Yes, they are hiring the experts themselves. To create new knowledge above and beyond what's on the internet. To be locked away as LLM training data."
More likely you're joking and/or paranoid!8-))
> I write novel software that solves problems no existing software does
This is actually really easy to do if you step out of web/gui/crud and into something where you won't find public code, most ever, because it's trade secret. For example, manufacturing.
2 replies →
I wish our actual world wasn't an implausible scifi novel!
>> They need expert reviewers in virtually every interesting topic, which fundamentally is an intractable problem, especially since things change all the time.
How odd. It's Expert Systems and the Knowledge Acquisition Bottleneck all over again.