[cujic9]

Firstly, the human brain is not vastly superior. There are already tasks such that a reasonably competent developer can build and train a deep learning model that beats human perception on commodity hardware with open source software.

Secondly, the number of jobs requiring thinking in an ill-defined framework these days is shrinking rapidly.

This is not specifically caused by machine learning, but rather by the desire for predictable timelines / cost savings / metrics gathering. But it has set the stage for AI automation.

Take law and health care, for example:

* Law firms are consolidating, and lawyers can now spend their entire career working on one small, specialized aspect of a field.

* Primary care physicians barely are allotted just enough time to refer you to a specialist. The specialist has just enough time to order tests.

[robot197]

Yeah, on the ImageNet data set, where all the images are pretty unclear, low res and cropped weirdly leaving out context, deep learning "beats" human vision system.

Human brain beats everything for now. It is a much more generic system.

I don't know enough about the specific fields you talked about to comment.

Deep learning is an incredibly powerful tool, but we should differentiate between its actual merit and the huge hype around it, mostly done for PR and misleading investors/financial analyst.

[cujic9]

You are moving the goalposts.

If we're talking about doing a specific task within a well-defined framework, computers are already proving to be superhuman. That includes image recognition beyond ImageNet, as well as games like Go.

But yes, if we're talking about a generic system, then humans are better. And I think they will be for a long time.

And yes, I agree, there is a lot of noise and sizzle around AI (but there is also quite a bit of steak there too.)