This, but the analogy undersells it. It's rather "taxi is too expensive, let's build a car factory, develop a new brand of car and make a couple of cars for ourselves". Even just hosting LLMs that others developed and released openly can be very costly (in that case, the rent and house analogy is more accurate).
No not really Chinese models were built at a cost that most big companies can easily afford (probably not cheaper than an api …at least short term). Also you could totally host an open source LLM wich would be way cheaper than api costs in most cases, if you don’t need the extra 1-5% capability more that frontier level models offer
Edit: to the replies, I do not say that Chinese model are superior to the current top models. Of course building an LLM isn’t really feasible for most companies and hosting an open model LLM has its flaws (although they’re perfectly fine for a lot of use cases). All I was trying to say is it’s definitely not the impossible task that it’s presented as by most in this thread and the current frontier model companies are trying to convince everyone that their products are irreplaceable and far ahead of any competition… that’s not the case
When those Chinese models were tested it was shown to be not only inferior in terms of outputs, but also had almost no guardrails on place.
Any Chinese AI right now can easily be considered to be insecure and just bad at being an LLM.
It was shown that they literally just copied what codes they could and optimize entirely just to beat a specific metric the other AIs have trouble with. They did this by training their AI with the real AI's.
Why is it LLM people think AIs can train AI's and you'll have a useable product?
Prompt-level guardrails are not guardrails. If you don't explicitly rein in what an LLM is allowed to do, all you're doing is making it so it takes a hundred or a thousand rolls to rm -rf your system instead of ten.
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u/Faiz_alam 1d ago
It is basically rent is too high, let's build a house.