Re: AI…. To do what???
It strikes me that LLM AI trained on text is really a rather poor aspect of AI to concentrate on.
What AI can do, and where it should be deployed, is in self learning (training) on things other than text. It is this self-training that will be it's benefit, not the training data itself.
If we have a 'real' AI solution, we should be able to point it at any data set, and give it some goals (such as 'these are examples of what we're looking for'), and let it loose.
Examples which may be good or bad include:
Identification of potential cancers from X-rays and other scans (good)
Tracking people from multiple video feeds (good and bad)
Spotting trends in weather formations, ice loss, floods etc (good?)
Analysing seismic data to spot potential earthquakes and tsunamis (good)
Accurate condensing of large datasets to allow rapid identification of information (be it legal, scientific or other data) (generally good but could be put to bad use)
The problem is that I don't believe we have such a thing as a general AI model which can take any data set. We have ones that can learn text, and some that do language, image and music processing, together with some tools that can take the condensed data and generate something similar to it's input data. But this is really not the bit of AI that we need, even if these are things that grab attention.
But even if we could have a real general AI, one of the problems is, and will remain to be, is initial trust in what is produced. For the initial deployment, we will want to check the results to identify things that should be spotted but aren't, and also false positives and 'hallucinations'. And once we get past this stage, we will need to have an "explain your decision" function, so that it does not look like the AI has just had a 'hunch'.
Unfortunately, businesses and governments are being jumped into building something that can do what we see today, and are suffering from FOMO about not getting on the band-wagon.
We should be looking at what we want to do tomorrow, or next year or next decade, but so few people have a vision that can look beyond today.