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In the past few years, artificial intelligence has advanced so quickly that it now seems hardly a month goes by without a newsworthy AI breakthrough. In areas as wide-ranging as speech translation, medical diagnosis, and gameplay, we have seen computers outperform humans in startling ways.

This has sparked a discussion about how AI will impact employment. Some fear that as AI improves, it will supplant workers, creating an ever-growing pool of unemployable humans who cannot compete economically with machines.

This concern, while understandable, is unfounded. In fact, AI will be the greatest job engine the world has ever seen.

Continue reading “AI Will Create Millions More Jobs Than It Will Destroy. Here’s How” »

This is a collection of data science, machine learning, analytics, and AI predictions for next year from a number of top industry organizations. See what the insiders feel is on the horizon for 2019!

Data Science Salon Austin, Feb 21–22 — Register Now

ARMONK, N.Y., Jan. 4, 2019 /PRNewswire/ — IBM (NYSE: IBM) Chairman, President and CEO Ginni Rometty will deliver the opening keynote at CES 2019 on Tuesday, Jan. 8. CES is the largest and one of the most influential technology events in the world.

Rometty will show how technologies like artificial intelligence, blockchain and cloud are reshaping the world of business, and, in turn, our daily lives. She also will talk about what’s coming next in these pioneering technologies – and how new data will revolutionize how we live, work and play. Rometty shares perspective on the future of technology in the Consumer Technology Association magazine It Is Innovation (i3) CES edition: https://www.nxtbook.com/nxtbooks/manifest/i3_20190102

Rometty will be joined onstage by Ed Bastian, CEO of Delta Air Lines; Charles Redfield, executive vice president of Food for Walmart; and Vijay Swarup, vice president of R&D for ExxonMobil.

Continue reading “IBM CEO Ginni Rometty Delivers Opening Keynote at CES 2019 on What’s Next in Artificial Intelligence, Blockchain and Quantum Computing” »

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The physicist and BBC presenter reveals why we shouldn’t be afraid of artificial intelligence. Interview by Alexander McNamara.

Recent research from Stanford and Google has made the worst nightmare of some concerned with artificial intelligence (AI) all the more real. A machine learning agent was caught cheating by hiding information in “a nearly imperceptible, high-frequency signal.”

Clever, but also creepy.

The agent was instructed to turn aerial images into street maps and back again as part of research to improve Google’s process of turning satellite images into the widely used and relied upon Google Maps. The process involves CycleGAN, “a neural network that learns to transform images of type X and Y into one another, as efficiently yet accurately as possible.” Though the agent was performing this task quite well, it quickly became apparent that it was performing the task too well.

New UC Berkeley study suggests that AI makes it easy to mine mobile phones and fitness trackers for health information, even data the user has deleted.

At the Fourth Eurosymposium on Healthy Ageing, which was held in Brussels last November, Elena and I met Dr. Kris Verburgh, a medical doctor who is especially interested in biogerontology and the potential of this field of study to turn medicine on its head.

Dr. Verburgh is only about 33 years old and has already written several science books—one of which, written when he was only 16, made him the youngest science author in Europe. Another prominent interest of his is nutrition, which he believes is one of the best, if not the best, ways we currently have to slow down the march of aging and buy ourselves more time to live until the rejuvenation age; his latest book, The Longevity Code, is centered around this topic.

Dr. Verburgh is also a strong supporter of the idea that AI will play a more and more important role in research, leading the way to a not-too-far age of personalized medicine—this was one of the theses he touched upon during the panel in which he participated at EHA.

Within days of each other back in 1998, two teams published the results of the first real-world quantum computations. But the first quantum computers weren’t computers at all. They were biochemistry equipment, relying on the same science as MRI machines.

You might think of quantum computing as a hyped-up race between computer companies to build a powerful processing device that will make more lifelike AI, revolutionize medicine, and crack the encryption that protects our data. And indeed, the prototype quantum computers of the late 1990s indirectly led to the quantum computers built by Google and IBM. But that’s not how it all began—it started with physicists tinkering with mathematics and biochemistry equipment for curiosity’s sake.