We got our current revolution for three major contributors:
* Big data. Lots of big data. Mostly unstructured and unqueryable driving demand for...
* Innovations in machine learning. "Deep learning" enabled by big data and algorithmic approaches that previously wouldn't have been possible without...
* Ubiquitous access to high-performance compute power, and in particular GPUs, which are optimized for the sort of math needed to train big neural networks powered by big data.
So GPU-powered compute is one of three mutually dependent things that got us here.
Most deep learning algorithms were discovered decades ago, so it's debatable that it was a driving factor behind the 2010s revolution. Backpropagation dates from 1986, convolutional neural nets from 1989 (neocognitrons), LSTMs from the late 90s...
* Big data. Lots of big data. Mostly unstructured and unqueryable driving demand for...
* Innovations in machine learning. "Deep learning" enabled by big data and algorithmic approaches that previously wouldn't have been possible without...
* Ubiquitous access to high-performance compute power, and in particular GPUs, which are optimized for the sort of math needed to train big neural networks powered by big data.
So GPU-powered compute is one of three mutually dependent things that got us here.