Comment by jmalicki
10 hours ago
I find these internet arguments talking about LLMs as if they are trained by reading the internet to be wild.
Yes, pretraining still exists. But for the past few years, pretraining by reading the internet is just the initial bootstrapping of LLM training. The RL training they get from bespoke training data, with very very different characteristics than what these armchair analyses claim, dominates these days.
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).
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1. How did you land the side gig? Mercor or a lessor known brand?
2. What criteria do such vendors typically require?
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What kind of programs? Can you give an example of the tasks?
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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-))
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>> 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.
Outside of games and coding generating enough valid examples and counter-examples to harness the power of RL is cost prohibitive.
Which is why rubrics as rewards are used.
still cost prohibitive.
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Where do they get the bespoke training data from? And how much? I don’t really know anything about this.
> And how much?
Mercor, one of the larger vendors for contracting with experts to create bespoke data, says on their webpage they're paying $3M/day to their contractors for data.
So well into the billions of dollars a year for bespoke training data.
That's also ignoring the RLVR data labs can get from software - they can use the vibe coding sessions as training data as well without paying more.
They are just one of many.
Companies like Mercor sell data from human experts
Offhand, do you know what format that data is in? Is it a question and then a human answering that question? Mostly just curious at to what the training data consists of.
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meta has reallocated a significant protion of their staff to genrating this
Meta also reportedly took a 49% nonvoting stake in Scale AI in June 2025 for about $14.3–$14.8 billion.
let me take down armchair analysis with my armchair analysis