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4 years ago we had computers "learning" to recognize images better than the best human coding. Before long they will be capable of learning pretty much everything.
"Alex Krizhevsky of the University of Toronto won the 2012 ImageNet computer image recognition competition.(1) Krizhevsky beat — by a huge margin — handcrafted software written by computer vision experts. Krizhevsky and his team wrote no computer vision code. Rather, using deep learning, their computer learned to recognize images by itself. They designed a neural network called AlexNet and trained it with a million example images that required trillions of math operations on NVIDIA GPUs. Krizhevksy’s AlexNet had beaten the best human-coded software."
Not quite sure this article describes a laughing matter.
"There are two important questions, according to White House economists. First, if robots replace existing workers, will workers have enough bargaining power to share in their employers' newfound gains? Second, will the economy create new jobs fast enough to replace the lost ones?"
I think it is pretty obvious that the "bargaining power" of workers is nil. That will effect those $20+/hr jobs as well if jobs become scarce. They may stay employed longer, but should expect pay to decline.
The middle class prosperity that we enjoyed for 150 years was because consumer-capitalism created symbiotic relationship between the oligarchs and the masses. That era will be over soon, and we will instead enter a stage where the masses have no "purpose" at all.
Location: East of Seattle since 1992, 615' Elevation, Zone 8b - originally from SF Bay Area
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It's not limited to $20 jobs. Fast food will become more automated very soon as minimum wage demand increases, and some jobs paying $40-50/hour union (longshore) workers are already being replaced by robotics, which started in Europe but is happening here now.
"Data scientists and AI researchers today spend far too much time on home-brewed high performance computing solutions," Huang said in a press release. "The DGX-1 is easy to deploy and was created for one purpose: to unlock the powers of superhuman capabilities and apply them to problems that were once unsolvable."
For the companies and organizations that'll take advantage of these computers, the pricing is surely not a concern -- and with machine learning and artificial intelligence crucially important from companies like Google and Microsoft as well as the research organizations Huang cited, there's likely a pretty big market for NVIDIA's all-in-one deep learning supercomputer.
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