While it can take some time for machines to be "trained" on data and for useful algorithms to arise, once this has happened, machines excel at data analysis.
Once that happens, machines will be able to process huge amounts of data -- including books, medical studies, social media status updates and facial cues as seen by a robot's camera eyeballs -- in hopes of advancing the human experience.
The bulk of innovation and heavy lifting is happening via machine learning and data structuring rather than figuring out how to position a few elements on a web page or an app.
Things are happening with machine-gun rapidity: Brexit, the Turkish coup, Islamist massacres in France, the surrounding of Aleppo, the nomination of Donald Trump.
Then something truly radical happened: the machine's hegemony was vanquished by actual machines, whose servers brought the last towering male monoliths down to JPEG size.
For this to happen, the machine must somehow interact with another electronic device.
He says that same kind of transformation is going to happen with machine learning.
When that happens, the machine will pause briefly and send out a puff of compressed air to separate the sticking pages.
But a funny thing happens when machine learning models comb over videos, pictures and text — new information gets created!
What happens when machines — and not just quick number-crunching machines like I.B.M.'s chess-playing Deep Blue, which beat the grand master Garry Kasparov in 1997, but actual learning machines — become superior at skills that we think demand creativity, insight, and uniquely human intuition?
We have no idea what happens when machines use models to communicate with other machines.
