IMHO (as a AI researcher) 'multi-modality, multi-task, multi-language, multi-memory' may take longer than you think. Doing multi modal learning is quite hard due to lack of labeled data, a lot of tasks either don't offer clean plentiful datasets or require RL / human in the loop learning and not just supervised or self supervised learning, and on and on. Certainly a lot of progress will be made and partial automation is likely to speed up (as has happened with Copilot), but full automation seems to be a good while away.

Plug - I expand on this a bit in this blog post 'The Inherent Limitations of GPT-3' (which was on front page of HN a few weeks back and led to a good deal of discussion ) https://lastweekin.ai/p/the-inherent-limitations-of-gpt-3

The sad part is that we are all helping to train the futures AI but who will own it and make money on it?

> who will own it and make money on it?

The nice part about it is that everyone will have access to great models for direct use, fine-tuning and adaptation. But if people don't take this freedom and are content with simply consuming applications, then they depend on those who deploy the apps.

You can have ownership in companies that do machine learning. It's called "shares". Creating your own business is an option too.

The complaint was that it's the people who own the equipment (or shares in it), and not the people who do the work, who are reaping the profit.

When the working class had this problem a couple centuries ago, it was solved by building guillotines. I hope we can do better this time.

You’re conflating two things. Feudalism is like slavery: taking credit for someone else’s labor. Automation removes the need for labor. Automation has almost universally led to quality of life improvements, not revolution.

To start an AI company you generally don't need much. A few thousands in GPUs and you are good to go. If AI researchers feel they are underpaid there is literally nothing stopping them from starting a company themselves.

that is absolutely not true. I'm not sure where you are getting your information, but read anything from an angel investor. most AI start ups fail because they go into huge debt getting correct data and training models, which end up bankrupting them in the process with nothing to show for it

If you need to collect date then you are not only an AI company. And in that case a large company is indeed needed.

I don't see any problem with it, stock market is open for everyone.

Nowadays startups often delay going to the stock market, and remain private while they're growing fast. It's only when they are growing more slowly and the VCs want to get out that they go public.

This way, the average investor usually does not reap outsized benefits from the ride.