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Comment Re: Copyright (Score 1) 121

Getting stuff done quickly is always going to win over getting stuff done slower due to arbitrary constraints.

I've demonstrated the principle on a few open source projects where issues remained unaddressed for months, or where I was told "it can't be done". All done in a matter of days or hours.

I've hardly written a line of code for a year now. I don't expect AI to do things flawlessly, but I have a 5 digit slashdot ID and therefore the experience to know where a clever but naive unseasoned developer is likely to screw up.

Comment Re:Big AI's business scheme (Score 3, Insightful) 38

The problem is that AI is rapidly being commoditized. If you're selling razor blades, the factory to produce them is a one-time cost.. Pioneering AI companies are left to differentiate themselves from the masses of AI blossoming out there, and they really can't.

However, the companies building data centers are going to make a killing.

Comment "And then they came for me..." (Score 4, Insightful) 26

When the "anything for a profit" motivations of modern capitalism steamrolled over laborers of all stripes, it was "Don't worry--we'll retrain them and they'll get better jobs."

Now the white collar workers are next. Why don't they learn a manual trade, or move to where the work is? Lazy bastards. /s

Comment Sounds familiar (Score 3, Informative) 12

That is a classic corporate "vanity project" trap. Itâ(TM)s a common mistake: a company mistakes its captive audience (employees) for a test market, forgetting that internal tools need to solve a problem, not create a new chore.

I worked at a company that tried to force an internal social media site on us. The catch? They weren't a social media company. It never took off. It was a textbook example of why you should stick to your core competencies.

Comment Re: it's a tool (Score 1) 150

"I do not see where AI can come up with original problems to solve"

A lot of original ideas arise from fuzzy (or even erroneous) thinking...starting with a bad/incoherent hypothesis and then iteratively correcting and refining it until you get a solid result (or give up).

I think AI is going to struggle with that approach, though I see glimmerings of it when it tries to debug code.

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