>Ergo, it is also very expensive to run
Wether thats too expensive depends on what you are doing, and how much what you are doing creates value.More disturbingly is that the whole approach seems to scale linearly in quality based on the amount of training. This implies that the NLP market at least, will not be conquored by start-ups from somebody's garage, but will be owned by whoever already had a shit load of money. Whoever gets more funding will have the best model. Not arguing that people involved don't have a lot of skill, but within this space, its funding (not skill) that
will determine who wins the market.
So, unless you can get more funding than the other guys, don't even try the NLP space.
>If this is true, those calling for OpenAI to not monetize intermittent progress are essentially preventing next generation discovery, unless they have alternative monetization ideas to generate 8 figures for research
I suspect they will share the models directly with select customers (with too much money), because the negotation position of these counterparties will be different. The results are easy to replicate with a lot of money. So if you have enough money to do so, your price negotation with them would be more like 'ill pay you 1/3 of that price to liscense your model and save me the time'.
If you dont have enough money to pay the electricity bill to train this much data, however, you can be forced to comply with this bussiness model. Obviously, there will be competitors. Obviously the big boys will likely try to replicate these results (and be succesfull at it). The hope is one of them just open-sources a 'good-enough' model.
Its a bit like Colombus 'discovering America'. Once you know its there the risk/reward of trying to go there drastically changes.