In early 2014, Srikanth Thirumalai met with Amazon CEO Jeff Bezos. Thirumalai, a computer scientist who'd left IBM in 2005 to head Amazon's recommendations team, had come to propose a sweeping new plan for incorporating the latest advances in artificial intelligence into his division. He arrived armed with a "six-pager." Bezos had long ago decreed that products and services proposed to him must be limited to that length, and include a speculative press release describing the finished product, service, or initiative. Now Bezos was leaning on his deputies to transform the company into an AI powerhouse. Amazon's product recommendations had been infused with AI since the company's very early days, as had areas as disparate as its shipping schedules and the robots zipping around its warehouses. But in recent years, there has been a revolution in the field; machine learning has become much more effective, especially in a supercharged form known as deep learning. It has led to dramatic gains in computer vision, speech, and natural language processing. In the early part of this decade, Amazon had yet to significantly tap these advances, but it recognized the need was urgent. This era's most critical competition would be in AI--Google, Facebook, Apple, and Microsoft were betting their companies on it--and Amazon was falling behind.

The woman in the photo seems familiar. She looks like Jennifer Aniston, the "Friends" actress, or Selena Gomez, the child star turned pop singer. But not exactly. She appears to be a celebrity, one of the beautiful people photographed outside a movie premiere or an awards show. And yet, you cannot...

Who will deliver our packages in the future -- drones, or self-driving robots? Amazon has an entire division devoted to developing drones that can carry them over the air to our doorsteps, but it also recently filed a patent on a ground-based, driverless-delivery vehicle. In so doing it joins a handful of startups and companies who are working on similarly small, self driving robots that will carry goods via the sidewalk. They're much slower than drones and they get in the way of pedestrians, but developers at thyssenkrupp Elevator think the wheeled couriers will catch on quicker than drones. Torsten Scholl, who invented the TeleRetail robot with thyssenkrupp and displayed it at the Washington Auto Show last week, says he recently took the gadget to a small village in the Swiss mountains, hoping to film it in action with a drone. Soon after he sent the drones up in the air, passers-by in the village approached him to complain, saying they "didn't want drones around here," and that the devices weren't allowed.

On Monday, a Tesla Model S slammed into the back of a stopped firetruck on the 405 freeway in Los Angeles County. The driver apparently told the fire department the car was in Autopilot mode at the time. The crash highlighted the shortcomings of the increasingly common semi-autonomous systems that l...

When Singapore decided that they needed a new smart water assessment network to track pollution in their reservoirs, they obviously went with a robot, because otherwise you wouldn't be reading about it here. They also decided that the robot had to be "aesthetically pleasing" in order to "promote urban livability." The answer came from researchers at the National University of Singapore (NUS), who proposed developing a Smart Water Assessment Network: Yes, that's right, a SWAN. The researchers, from NUS Environmental Research Institute and Tropical Marine Science Institute, had developed and tested a version of the swanbots back in 2016. Now they've decided to deploy them full time across five different reservoirs in Singapore, where water is a particularly precious resource.

There are a lot of things that chatbots have yet to master and high on the list is small talk. But researchers at Facebook think the best way to make software prattle away is to give it a personality. Workers were asked to chat in pairs and to give statements describing themselves, including their likes and dislikes. The crowdworkers' chatter was linked to these description statements and used to train the chatbots.

By default, both iOS and Android let you access their digital assistants--Siri and Google Assistant, respectively--right from the lock screen (unless the phone owner has disabled the feature). To pull up the assistant on an iPhone other than the X, press and hold the Home button (for the iPhone X, press and hold the Power button instead). On Android, tap and hold in the bottom left corner of the display (where the microphone icon apppears) and then drag your finger up to the middle of the screen. Once you've accessed Siri or Google Assistant, try saying "Call mom," "Call home," or another command that might access one of the phone's owner's contacts. Siri also has a trick that Google Assistant doesn't: Ask "Whose phone is this?" to bring up contact details for the owner.

Criminal recidivism is when a released criminal goes back to crime. From charging crimes through probation, the criminal justice system is constantly looking for ways to better predict which criminals are more likely to remain legal on release and who is a risk of recidivism. Bias can create inaccuracies through weighing variables incorrectly, and machine learning might provide a way of limiting bias and improving recidivism predictions. A recent study by Julia Dressel and Hany Farid, published in Science Advances, points to the limitations of deterministic algorithms with fixed parameters for the task of such predictions. The study analyzes the Correctional Offender Management Profiling for Alternative Sanctions (COMPAS) software, a package used by court systems to predict the likelihood of recidivism in criminal defendants. The lessons learned lead me to a discussion about the promise of machine learning (ML) systems – specifically, deep learning.

One day after an American drone strike killed a leader of the militant Haqqani network in northwestern Pakistan, United States officials on Thursday rejected a claim by Pakistan that the strike had targeted an Afghan refugee camp. There were also conflicting accounts of the location of the drone strike and the number of people killed. A statement by Pakistan's Ministry of Foreign Affairs on Wednesday condemned the strike and maintained that it had "targeted an Afghan refugee camp in Kurram Agency" -- an assertion that the United States rejected on Thursday. "The claim in an M.F.A. statement yesterday that U.S. forces struck an Afghan refugee camp in Kurram Agency yesterday is false," said Richard W. Snelsire, the United States Embassy spokesman in Islamabad, Pakistan's capital. American officials said that there were no Afghan refugee camps in Kurram, a remote tribal region straddling the border with Afghanistan, where they said Wednesday's drone strike had taken place.

Passively mobile communicating machines that use restricted space.