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Wednesday, January 03, 2018

It’s Amazing To See Just How Much Seems To Have Happened In A.I. in Twelve Months

This appeared last week

It Was a Big Year for A.I.

AlphaGo beat the world's best Go player in May. A few months later, a new version beat the human-defeating version 100 to 0.
2017 has been a booming year for the field of artificial intelligence. While A.I. and data-focused machine learning have been around for decades, the algorithmic technologies have made their presence known in a variety of industries and contexts this year.
Microsoft UK’s chief envisioning officer Dave Coplin has called A.I. “the most important technology that anybody on the planet is working on today,” and Silicon Valley companies seem to have taken that to heart: They’ve been hiring A.I. experts right and left, and with those in short supply, they’ve started teaching employees the fundamentals of A.I. themselves.
Not every A.I. achievement has been met with admiration and applause, though. Some are worried about the human prejudices that are being introduced into A.I. systems. ProPublica found in 2016, for example, that the software algorithms used to predict future criminals were heavily biased against black defendants. And earlier this year, Facebook came under fire for the algorithmically generated categories advertisers could use to target users, which included hateful groups and topics such as “Jew hater.” Situations like these have prompted experts to urge companies and developers to be more transparent about how their A.I. systems work. However, in many other cases—especially of late—A.I. has been used to good end: To make discoveries, to better itself, and to help us expand beyond the limits of our human brains.
A.I. Spotted An Eight-Planet Solar System
Successful astronomical discoveries often center around studying data—lots and lots of data—and that is something A.I. and machine learning are exceedingly good at handling. In fact, astronomers used artificial intelligence to sift through years of data obtained by the Kepler telescope to identify a distant eight-planet solar system earlier this month. This solar system now ties our own for the most known planets circling its star, in this case Kepler-90, located more than 2,500 light years away.
From 2009 to 2013, the Kepler telescope’s photometer snapped 10 pixel images of 200,000 different stars every half hour in search of changes in star brightness. If a star dimmed and brightened in a regular, repeating pattern, that could be an indication that it has planets orbiting. (You can also use that information to estimate the size and length of orbit of a planet circling a particular star.) University of Texas at Austin astronomer Andrew Vanderburg and Google software engineer Christopher Shallue developed the neural network that made the discovery using 15,000 known exoplanet indicators. They zeroed in on 670 stars with known exoplanets, but focused specifically on weak signals—smaller exoplanets previous researchers may have missed. The planet the duo discovered, dubbed Kepler-90i, appears to be the third planet orbiting its star, much like our own Earth.
Beat The World Champion Go Player
Google’s DeepMind researchers developed an A.I. that plays the ancient, complex Chinese strategy game of Go. The initial version defeated the world’s best Go player in May, but that wasn’t enough. A few months later, Google developed a new version of this AlphaGo A.I.: AlphaGo Zero. This A.I. achieved a superhuman-level Go-playing performance—it beat the original AlphaGo A.I. 100 to 0.*
Lots more here:
Well worth a browse – there is a lot going on!


Enrico Coiera said...

For all the good news about AI, the level of AI hype far exceeds the genuine AI progress made over the last 12 months. As ever it is this surfeit of enthusiasm that leads to eventual disappointment, not the underlying technology which make steady and impressive progress.

As a counter point, my US colleague Gary Markus today posted this critical appraisal of what deep learning can and cannot do on Arxiv. Expect to hear more about this paper in the weeks to come. https://arxiv.org/abs/1801.00631

Anonymous said...

I find this a challenging dilemma - Some are worried about the human prejudices that are being introduced into A.I. systems.

How would this be resolved without artificially introducing biases? Real or perceived?