The one what? What is the secret sauce that will distinguish one LLM from another? Is it patentable? What's going to prevent all of the free LLMs from winning the prize? An AI crash seems inevitable.
They want to be the Google in this scenario.
The model can be free, but the infrastructure (data center) ain't.
Currently, the trend is not whether one technology will outpace the other in the "AI" hype-cycle ( https://en.wikipedia.org/wiki/Gartner_hype_cycle ), but it does create perceived asymmetry with skilled-labor pools. That alone is valuable leverage to a corporation, and people are getting fired or ripped off anticipating the rise of real "AI".
https://www.youtube.com/watch?v=_zfN9wnPvU0
One day real "AI" may exist, but a LLM or current reasoning model is unlikely going to make that happen. It is absolutely hilarious there is a cult-like devotion to the AstroTurf marketing.
The question is never whether this is right or wrong... but simply how one may personally capture revenue before the Trough of disillusionment. =3
On paper, whoever gets there first, along with the needed compute to hand over to the AI, wins the race.
The AI, having theoretically the capacity to do anything better than everyone else, will not need support (in resources or otherwise) from any other business except perhaps once to kickstart its exponential growth. If it's guarded, every other company becomes instantly worthless on the long term, and if not anyone with a bootstrap-level of compute will be able to also, do anything ever on a long enough time frame.
It's not a race for ROI, it's to have your name go in the book as one of the guys that first obsoleted the relationship between effort, willpower, intelligence, etc. and the ability to bring arbitrary change to the world.
There’s no guarantee that the singularity makes economic sense for humans.
Are we /confident/ a machine god with `curl` can't gain its own resilient foothold on the world?
Practically, LLMs train on data. Any output of an LLM is a derivative of the training data and can't teach it anything new.
Conceptually, if a stupid AI can build a smart AI, it would mean that the stupid AI is actually smart, otherwise it wouldn't have been able too.
The fact is, there is no law of physics that prevents the existence of a system that can decrease its internal entropy (complexity) on its own, provided you constantly supply it with energy (negative entropy). Evolutionary algorithm (or "life") is an example of such a system. It is conceivable that there is a point when a LLM is smart enough to be useful for improving its own training data, which then can be used to train a slightly smarter version, which can be used to improve the data even more etc... Every time you inference to edit the training data and train, you are supplying a large amount of energy into the system (both inferencing and training consumes a lot of energy). This is where the decrease in entropy (increase in internal model complexity and intelligence) can come from.