The Atlantic


Why Would Anyone Fear a Self-Driving Car?

The Atlantic

"Planes fly roughly 99 percent of the miles that they fly by computer. It's now to the place that it is not safe for humans to fly in a lot of conditions. If you could have a robotic surgeon that makes one mistake in 10,000, or a human that made one mistake in 1,000, are you really going to go under the knife with the human? As a counterpoint, however, there are lots of Americans who choose to drive rather than fly, fearing the latter more despite knowing that it is statistically much safer.


An Artificial Intelligence Developed Its Own Non-Human Language

The Atlantic

In the report, researchers at the Facebook Artificial Intelligence Research lab describe using machine learning to train their "dialog agents" to negotiate. At one point, the researchers write, they had to tweak one of their models because otherwise the bot-to-bot conversation "led to divergence from human language as the agents developed their own language for negotiating." In other words, the model that allowed two bots to have a conversation--and use machine learning to constantly iterate strategies for that conversation along the way--led to those bots communicating in their own non-human language. Already, there's a good deal of guesswork involved in machine learning research, which often involves feeding a neural net a huge pile of data then examining the output to try to understand how the machine thinks.


Beyond the Five Senses

The Atlantic

The world we experience is not the real world. Which raises the question: How would our world change if we had new and different senses? More recently, researchers in the emerging field of "sensory enhancement" have begun developing tools to give people additional senses--ones that imitate those of other animals, or that add capabilities nature never imagined. Researchers are working on other technologies that could restore sight or touch to those who lack it.


When AI Can Transcribe Everything

The Atlantic

Despite the recent emergence of browser-based transcription aids, transcription's an area of drudgery in the modern Western economy where machines can't quite squeeze human beings out of the equation. That is until last year, when Microsoft built one that could. Automatic speech recognition, or ASR, is an area that has gripped the firm's chief speech scientist, Xuedong Huang, since he entered a doctoral program at Scotland's Edinburgh University. Huang and his colleagues used their software to transcribe the NIST 2000 CTS test set, a bundle of recorded conversations that's served as the benchmark for speech recognition work for more than 20 years.


Google's New Product Puts Peer Pressure to a Sunny Use

The Atlantic

It now provides data for 60 million homes across the United States that it has already assessed with its algorithms. For the past two years, Project Sunroof has walked people through all the information-gathering steps of installing solar panels: After you tell it where you live, its algorithms estimate how much solar energy falls on your roof, calculate how much solar panels would reduce your electricity bill, and deliver estimates from local installation firms like Solar City. Google created the data for this feature in-house, training a machine-learning algorithm on the common appearance of rooftop solar panels and then letting it loose on the cities and towns that Project Sunroof already covers. Right now, the company has analyzed installations on about 60 million buildings in the United States; it hopes to get to the remaining 40 million buildings in the next few years.


Travis Kalanick's Uncertain Fate

The Atlantic

Uber didn't immediately respond to The Atlantic's request for comment on Sunday. His termination was tied to a federal lawsuit in which Waymo--the self-driving car company that spun out of Google--is accusing Uber and Levandowski of stealing its design secrets. Uber's request for arbitration would have allowed the ride-sharing giant to defend itself behind closed doors. Instead, Uber will have to go to trial to answer Waymo's accusations in what is sure to be an ugly showdown.


How Apple Sees the Near Future

The Atlantic

Without once saying the words "artificial intelligence," a stream of Apple executives described a vision of the near future in which Siri, the company's AI avatar, stitches together the company's many hardware products. After a strangely dystopian video in which Apple's apps go away and the world plunges into post-apocalyptic violence, Apple CEO Tim Cook led off the company's keynote at its big gathering for coders, the Worldwide Developers Conference, in San Jose. Through the demonstrations and talks, Apple's vision for Siri became clearer: It is an all-purpose stand-in for predictive, helpful intelligence across all Apple devices. "With Siri intelligence, it understands context.


When a Robot Names a New Color of Paint

The Atlantic

Recurrent neural networks "learn" by repeatedly processing the data given to them. Instead of a typical computer program, which runs certain pre-set functions on a large data set, neural networks learn probabilistically what the set "looks" like. As they prepare this model, they spit out new approximations of the data set--data that wasn't included in the original set, but which could be. In the case of the type of program that Shane uses, it learns to model character-by-character: It figures out which character are is most likely for a certain spot, then it moves on to the next, and the next after that.


20 Questions With Google's Assistant and Apple's Siri

The Atlantic

Tuesday, Google made its artificial-intelligence powered Assistant available for the iPhone. The move brings the company's voice interface into direct competition with Apple's own Siri. For the first time, you can now have both assistants on the same phone in your palm. They serve as a platform for promoting the way Google's executives see their company and the world.


The Thinning Line Between Commercial and Government Surveillance

The Atlantic

The data that tracks our behavior feeds into machine-learning algorithms that make judgments about us. Latanya Sweeney, the director of the Data Privacy Lab at Harvard University, found that Google searches for black-sounding names more often resulted in ads for arrest records compared to searches for white-sounding names, likely a result of the algorithm learning to predict what users are likely to click on. And when algorithms learn what we like and feed us more of it, they amplify the notorious filter bubble and deepen political polarization. This means that even if you clear your cookies or log out of a website, your device fingerprint can still give away who you are.