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Comment Re:See, this is the real problem (Score 1) 81

People seem to only have memory that goes back two years.

We went to war with Iraq due to faulty intel. No AI was involved at all, at least not in the modern sense of the term. Just a human expert hallucinating a bioweapons lab from a blurry photo.

Russia almost nuked us due to a faulty machine sending a false positive about a nuclear attack. Definitely not AI.

Comment Re:Good luck with that (Score 1) 98

> That feels like an odd thing to be frightened of. It's not Mars where there are minutes of latency. Why would the Philippines - specifically - be any more (or less) concerning than if the drivers were in a building a kilometer away from the vehicle?

Half-way across the world and thus more prone to latency spikes. Not something you want when you need to be able to react quickly. Or have you never played a game on a server on the other side of the pacific?

Comment Wrong assumption in the article (Score 5, Interesting) 83

I, Steve Wozniak, did not participate in the theft of the BASIC. It was funny to me to see others enjoying doing this. I had never used BASIC myself, at that time, only the more-scientific languages like Fortran, Algol, and PL-1, and several assembly languages. I sniffed the air and sensed that you needed BASIC to sell computers into homes, because of the book 101 Games in BASIC. I loved games and saw games as the key. It was the [MS] BASIC that inspired me to write a BASIC interpreter for my 6502 processor, in order to have a more useful computer.

Comment Very misleading title (Score 1) 32

The title is more aimed at being clickbait than attempting to be informative.
The only thing in the underlying article is that specific neural networks are good and efficient at producing approximate solutions to large sparse systems of linear equations. Nothing else.

Such big systems of equations result when you try to solve partial differential equations on a finite-element mesh by substituting a lot of base functions.

There are broadly 2 ways of solving such systems: direct (e.g. using the sweep method) or iteratieve. The neural networks are just a way of implementing the iterative method. The only thing interesting is that the specific neural networks proposed to do this can be calculated efficiently (also energy-efficiently) on specific hardware optimised specifically for that flacour of neural network.

The OP post tries to link 'math' and 'AI' here because, well, partial diffferential equations count as 'math', and neural networks are a form of 'AI', right? And that's how the OP 'justifies' its title.

Sorry folks, but his is a highly technical development which in no way merits the hoo-hah the OP throws at it.

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