Technical Disruptions Emerging in 2020

This year a broad range of emerging technologies will become a tangible part of the broader IT and business dialogue. Here we’ll take a look at long-term disruptions that will be real enough to matter in thinking through the future but possibly not real enough yet to change the market immediately. What all of these share are the potential to dramatically change IT system and industry thinking as well as the world’s technical capability. The “vacuum tube” era of Quantum computing begins. While we are still many years away from a viable quantum computer, 2020 is … READ MORE


Noise warfare

In his 5th century treatise on war, Sun Tzu famously proclaimed “If you know your enemy and you know yourself, you will be victorious in numerous battles.” Of course, Sun Tzu was fighting with swords and arrows, not keystrokes and algorithms, but the principle is just as applicable to cyber warfare as it was to ancient Chinese battlefields.

Among the most vulnerable targets in cyberwarfare are deep neural networks. These deep-learning machines are vital for computer vision — including in autonomous vehicles — speech recognition, robotics and more.

“Since people started to get really enthusiastic about the possibilities of deep learning, there has been a race to the bottom to find ways to fool the machine learning algorithms,” said Yaron Singer, Assistant Professor of Computer Science at the Harvard John A. Paulson School of Engineering and Applied Sciences (SEAS).

The most effective way to fool a machine learning algorithm is to introduce noise — additional data that disrupts or skews information the algorithm has already learned. Imagine an algorithm is learning the difference between a stop sign and a mailbox. Once the algorithm has “seen” enough images and collected enough data points, it can develop a classifying line that separates stop signs from mailboxes. This classifier is unique for every dataset.

To trick the machine, all you need is basic information about the classifier and you can tailor noise specifically to confuse it. This so-called adversarial noise could wreak havoc on autonomous vehicles or facial recognition software and, right now, there is no effective protection against it. The only recourse is to recalibrate the classifier. Of course, the adversary then develops new noise to attack the new classifier and the battle continues.

So-called adversarial noise, mostly undetectable to human eyes, causes machine learning algorithms to confuse simple objects. Above, adversarial noise causes an algorithm to confuse a panda with a gibbon. Below, adversarial noise causes an algorithm to confuse a school bus with an ostrich.

So-called adversarial noise, mostly undetectable to human eyes, causes machine learning algorithms to confuse simple objects. Above, adversarial noise causes an algorithm to confuse a panda with a gibbon. Below, adversarial noise causes an algorithm to confuse a school bus with an ostrich.

But what if, as Sun Tzu suggests, your classifier could truly know all the types of noise that could be used against it and be prepared for each attack?

That’s what Singer and his team set out to do.

“We developed noise-robust classifiers that are prepared against the worst case of noise,” Singer said. “Our algorithms have a guaranteed performance across a range of different example cases of noise and perform well in practice.”

Singer, with co-authors Robert Chen, Brendan Lucier, and Vasilis Syrgkanis, recently presented the research at the prestigious Neural Information Processing Systems conference in California.

“Our work provides new theoretical insights into how to optimize functions under uncertainty,” said Robert Chen, co-author of the research and former SEAS undergraduate. “Those functions could be measuring any number of things, however, and so the framework accommodates a wide range of problems and has a wide range of potential applications, from autonomous driving to computational biology and theoretical computer science.”

Next, the researchers hope to use this framework to tackle other problems in machine learning, such as understanding the spread of epidemics in social media.


Why Aren’t There More Smart Americans?

As research for his latest novel, The Quantum Spy, Washington Post reporter David Ignatius spoke with some of the world’s leading experts on quantum computing, which led him to believe that we may see a working quantum computer in the next five years.

“Initially what I would hear back from technologists was, ‘it’s fascinating if it works,’ and I hear more now ‘fascinating when it works,’” Ignatius says in Episode 291 of the Geek’s Guide to the Galaxy podcast. “There’s a sense that these problems probably can be solved.”

The downside is that a quantum computer would be the cyber warfare equivalent of a nuclear bomb, which means the US government is often reluctant to let foreign scientists work on the most promising research. It’s a system that can slow down progress due the lack of ‘smart Americans,’ as one character in the book puts it.

“The number of American citizens who can do very high-end research who also can easily get security clearances is limited,” Ignatius says. “The ability of our schools to produce American students at a world-class level, that’s an important national challenge.”

He says that one reason the US lags behind other countries is a political culture in Washington in which too many leaders are ignorant of and hostile to basic science. Though he believes that recent events like the March for Science are a promising development.

“When adherents of the fact-based, reason-based, educated-and-proud-of-it world begin to fight back and say, ‘No, wait a minute. We’re not going to throw climate science or any other aspect of our fact-based tradition overboard,’ that’s going in the right direction,” Ignatius says.

He believes that one thing the US does have going for it is that the country still produces a disproportionately high number of creative and risk-taking individuals, and that it’s important not to lose that edge moving forward. “The sweet spot for us is somehow to be rigorous enough in giving people the basics, but also loose enough in letting people experiment and be creative,” he says. “But the basic math/science education, the US has got to get better at it, no question about it.”

Listen to the complete interview with David Ignatius in Episode 291 of Geek’s Guide to the Galaxy (above). And check out some highlights from the discussion below.

David Ignatius on quantum computing:

“I got interested in a company called D-Wave, which claims that it’s already built a quantum computer. There’s a lively debate that’s been going on for a decade about whether D-Wave’s computer really is a quantum computer or is instead a ‘quantum annealer,’ using annealing technology to, in effect, solve optimization problems. … Some companies have bought D-Wave machines and are using them for optimization-type problems, and trying to tune the D-Wave computer, which has got a lot of qubits—they’re selling machines that have more than 2,000 qubits operating—to do this approach. And from what I read—and again your listeners need to say whether they think this is right or not—the evidence is growing stronger that there are quantum effects in the annealing approach.”

David Ignatius on secrecy:

“The first person who has a computer that can apply Shor’s algorithm—which posits that you can factor any number and decrypt any encryption scheme—the first person who gets that is going to be able to essentially go through every secret message, not to mention payments transaction, and for a time have mastery of that and then operate with that knowledge, so I get why people are anxious about it. But I think in the long run it’s hard—I want to say impossible—to imagine the secret of quantum computing remaining the province of one set of wizards, one country exclusively, for very long.”

David Ignatius on Futurism:

“The Futurists were a wonderful Italian movement. Many of the sculptors whose work we see in the galleries were from that period, and they were just in love with the future, with speed. There’s a famous quote in a manifesto attributed to one of these Futurist theorists: ‘A roaring automobile is more beautiful than the Victory of Samothrace’—the ‘Winged Victory’ that you see at the Louvre. I mean, what an amazing statement. The idea was speed, power, dynamism—that’s the art of the future, that’s the beauty of the future. And sorry, we live in a world of roaring automobiles, I want to go to the Louvre. I want to see the Victory of Samothrace.”

David Ignatius on Agents of Innocence:

“My first novel, Agents of Innocence, had a weird life as something that CIA officers often would give out to people—whether they were new recruits or people who were expressing interest—to say, ‘This is what we actually do. This is pretty much what we think our job is.’ And I’ve had people come up to me when I was traveling around the world, they kind of shuffle up to you and say, ‘I can’t say who I am, I’m not allowed to identify myself, but I just wanted to say, when I had to tell my mom and dad what I did, I gave them your book.’ And that pleases me, because it says that these people who are actually doing these jobs out in the remote reaches say, ‘You basically got it right. This is what I do.’”

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