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Comment by disgruntledphd2 | Hacker News Reader

I'm not really convinced that there's much secret sauce here, all the methods and data are public, the only real difference is how much compute it takes.

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All the methods and data are not public. We don't know what unpublished methods they're using. You can get most of the pre-training data publicly but they've probably spent a ton of money curating it and are now doing things like buying rare books. The RL training data is all (/mostly) proprietary though, and that's the real secret sauce part.

All the RL data are exactly public. There are huge amount of distilled data freely available, and that amount is more than enough to train a ~10T model.

> All the RL data are exactly public.

Nope, because the big AI companies are paying billions for it. They wouldn't pay anything for public data.

There are 'transfer stations' and that's how exactly I use GPT and Claude in China. OpenAI and Anthropic do not sell in China, so we use their AI with a much lower price like 1% of the official API price. The largest transfer stations have TBs of traffic every day, and the traffic is eventually possessed by the open source community.

Subscription engineering is a deep field. Neither OpenAI nor Anthropic have any technical advantage in this field.

everybody do be cooking with water. Chinese Labs provided pretty good, primarily cost-reducing techniques, like the sparse attention patterns recently. I'd bet OpenAI and Anthropic use their variants of those too, so they can get greater margin on their tokens - not something they'd really want to / need to self-report.

This is obviously false. There is "secret sauce" because in fact not all the methods and data are public.

Where does the secret sauce show up in the outputs, then?

Like, (apart from tone), I find it hard to distinguish between the outputs of GPT/Claude/Kimi/GLM recently (I use cursor, and have been giving them the same prompt and comparing).

If anything, I found that the non-Claude models were better in many cases, which definitely doesn't map to their pricing.

> in fact not all the methods and data are public

Probably not, but unless you work at a lab, I'm not sure that anyone can say (and if you do work at a lab, you should not be replying on this thread).

> Where does the secret sauce show up in the outputs, then?

In benchmarks, revenue, and comments from a lot of people on Hacker News.

> revenue

Maybe, I'm not sure this will continue.

> In benchmarks

All published benchmarks are useless, unfortunately.

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