I think we'll find that that asymptote only holds for cases where the end user is not really an active participant in creating the next model:

- take your data

- make a model

- sell it back to you

Eventually all of the available data will have been squeezed for all it's worth the only way to differentiate oneself as an AI company will be to propel your users to new heights so that there's new stuff to learn. That growth will be slower, but I think it'll bear more meaningful fruit.

I'm not sure if today's investors are patient enough to see us through to that phase in any kind of a controlled manner, so I expect a bumpy ride in the interim.

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conartist6 5 hours ago | parent [-]

Yeah except that models don't propel communities towards new heights. They drive towards the averages. They take from the best to give to the worst, so that as much value is destroyed as created. There's no virtuous cycle there...

	▲	__MatrixMan__ 5 hours ago \| parent [-]
		Is that constraint fundamental to what they are? Or are they just reflecting the behavior of markets when there's low hanging fruit around? When you look at models that were built for a specific purpose, closely intertwined with experts who care about that purpose, they absolutely propel communities to new heights. Consider the impact of alphafold, it won a Nobel prize, proteomics is forever changed. The issue is that that's not currently the business model that's aimed at most of us. We have to have a race to the bottom first. We can have nice things later, if we're lucky, once a certain sort of investor goes broke and a different sort takes the helm. It's stupid, but its a stupidity that predates AI by a long shot.