Even though the buzz around neural networks, artificial intelligence, and machine learning has been relatively recent, as many know, there is nothing new about any of these methods. …
“Machine learning connects supercomputing to consumers; its impact will be felt everywhere.” …
If one were to look at the approximate results from various deep learning tasks; from image classification to speech recognition and beyond, the stand-by quote from Bayesian statistics that “probability is orderly opinion, and that inference from data is nothing other than the revision of such opinion in the light of relevant new information,” takes on added weight. …
Deep learning algorithms have pushed image recognition and classification to new heights over the last few years, and those same approaches are now being moved into more complex image classification areas, including satellite imagery. …
Explaining the process of how any of us might have arrived to a particular conclusion or decision by verbally detailing the variables, weights, and conditions that our brains navigate through to arrive at an answer can be complex enough. …
There are few more interesting trends in infrastructure right now than the pairing between high performance computing hardware and the software tapestries of deep neural networks. …
If you think that Hewlett-Packard is disappointed about the delays in getting the memristor to market, so is a tenacious inventor who has been working at the confluence of electronics and machine learning. …
A lead deep learning expert at Microsoft Research thinks the low-hanging fruit for progress in deep neural networks has been picked and that for the next couple of years, refinement of neural networks and deep learning algorithms will be isolated and incremental. …
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