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Comment Re:Yeah, but you're leaving something out (Score 1) 98

You go to college to get an education. You go to a trade school to learn a trade. If you go to college to learn a trade, either you or the college has made a serious mistake.

What is your suggestion?

We used to put effort into training new hires, helping them learn the business and our way of doing things. We didn't expect a kid fresh out of college to be productive on day one. We understood the value of institutional knowledge and knew that even a modest six-month investment in a new hire would more than pay for itself down the road.

The "educated" people coming out of even the best universities

The best minds in any field are the ones who can draw from a wider perspective. I don't want or need someone limited to just their experience working through [worthless industry cert]. I don't care if you can confidently setup [latest industry fad] in a common configuration if you get frightened and confused when you see a little math.

I'll never understand this resistance to education. It's like watching a bunch of blind men insist that sight is overrated.

Comment Re:Translation from corp-speak (Score 1) 98

Tell me again how a trillion dollars worth of college bailout, is just a figment of my imagination

It's a very obviously a figment of your imagination.

along with the reason for it.

It's a figment of your imagination because no such thing happened.

Stay in school, kids. Don't be like geekmux.

Comment Re: So I don't actually know how real this is (Score 1) 95

Here in reality, we recognize that it is extremely difficult to accumulate that much wealth by honest means.

Millionaire status is well-within reach, given careful planning early in your career. To be a billionaire, however, requires legacy, larceny, or a mix of both. If you're a billionaire, odds are good that you're a giant piece of shit that has screwed over too many people to count.

Comment Re:Here's One Technical Opinion (Score 4, Interesting) 95

AI is a marketing term, that's undeniable. I'm not sure why you think 3D and 32-bit fall into the same category, but that hardly matters.

The real trouble is that what AI means to researchers and what AI means to the public are two very different things.

The term itself was coined by John McCarthy for the Dartmouth conference in 1956, though he has said he can't be sure if that no one used it before. We know that there was some controversy over the the term at that time, for obvious reasons, but it's way too late to complain about it now.

The science fiction version of the term, robots with feelings or whatever, came later. The field itself was never about that. The Dartmouth conference proposal comes the closest, defining the term this way: "For the present purpose the artificial intelligence problem is taken to be that of making a machine behave in ways that would be called intelligent if a human were so behaving.". Pamela McCorduck's provocatively titled Machines Who Think has the single best account of the state of things leading up to the conference, the conference itself, and what came out it if you're interested.

The field of AI is surprisingly broad and covers are a lot of things that you would, I suspect, viscerally reject as being AI. Linear regression, for example. What it doesn't cover is silly science fiction nonsense. Anyone claiming to be an AI researcher working on 'the hard problem' or some related thing is an obvious crackpot who should be ridiculed and then ignored.

The current AI hype is driven largely by companies, like the above, deliberately trying to confuse reality with science fiction. In my opinion, it often crosses the line into outright fraud.

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