Author: Tristan Greene / Source: The Next Web
Some of Google’s top scientists today discussed the future of artificial intelligence and the message was one of tempered expectations – something we hadn’t seen much of at the Google I/O event.
The field of artificial intelligence exists in two states which, upon first glance, appear diametrically opposed.
In one, here in 2018, we have computers that can usually figure out what a cat looks like with only a few hints – something most toddlers can get right with near-perfect accuracy. Yet in the other state, fully autonomous vehicles and superhuman AI-powered diagnostic tools for doctors are functionally available now.Figuring out what’s possible today, when it comes to artificial intelligence, is a full-time job in and of itself. Which is why it’s important to start with a fundamental question.
Fei Fei Li, Chief Scientist of Machine Learning and Artificial Intelligence for Google Cloud, says that question is:
Can machines think?
The answer today, according to Google, is a resounding no. When asked if solving image recognition was enough for her to believe we’re on the way to machines that truly think, Li simply says “No, that’s not enough.”
It seems we’re nowhere near artificial general intelligence (AGI), or machines that equal or surpass humans in our ability to think, process, predict, examine, and learn.
Greg Corrado, Principle Scientist at Google and co-founder of the Google Brain program, was asked if we’re close to AGI, and his response sums up what many in the community are thinking:
I really don’t think so. My feeling is: okay we finally got artificial neural networks to be able to recognize cats, and we’ve solved this holy grail problem of image recognition, but that’s only one small sliver, a tiny sliver, of what goes into something like intelligence.
We haven’t even scratched the surface. So to me, it’s really just a leap too far to imagine that, having finally cracked pattern recognition after decades…
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