[ARandumGuy]

> It took ~5 years from when people in the NLP literature noticed BERT and knew the powerful applications that were coming, until the public at large was aware of the developments via ChatGPT. It may take another 5 before the public sees the developments happening now in the literature hit something in a companies web UI.

It also may take 10, 20, 50, or 100 years. Or it may never actually happen. Or it may happen next month.

The issue with predicting technological advances is that no one knows how long it'll take to solve a problem until it's actually solved. The tech world is full of seemingly promising technologies that never actually materialized.

Which isn't to say that generative AI won't improve. It probably will. But until those improvements actually arrive, we don't know what those improvements will be, or how long it'll take. Which ultimately means that we can only judge generative AI based on what's actually available. Anything else is just guesswork.

[ChatGTP]

I'm concerned that until they do improve, we're in a weird place. For example, if you were 16, would you go an invest a bunch of time and money to study law with the prospect of this hanging of your future? Same for radiology, would you go study that now Geoffrey Hinton has proclaimed the death of radiologists in 3 years or whatever? Photography and filmography ?

My concern is we're going to get to a place where we think the machines can just take over all important professions, but they're not quite there yet, however people don't bother learning those professions because they're a career dead end and then we just end up with a skill shortage and mediocre services, when something goes wrong, you just have to trust "the machine" was correct.

How do we avoid this? Almost like we need government funded "career insurance" or something like this.