Target's higher minimum wage aims to attract and retain good staffers. See how much other big retailers are paying. This May 3, 2017, photo shows the Target logo on a store in Upper Saint Clair, Pa. Target is jumping into voice-activated shopping as it deepens its relationship with Google, offering thousands of items found in the store except for perishables like fruit and milk. The move is happening as Google says shopping will be available later in 2017 through Google Assistant on iPhone and Android phones, joining its Google Home device and Android TV.

OK, sure, there are self-driving cars on California roads today. General Motors' Cruise has Chevrolet Bolts zipping around San Francisco; Google self-driving spinoff Waymo has got Chrysler Pacifica motoring about Mountain View; secretive startup Zoox has black Toyota Highlanders mixing it up along San Francisco's Embarcadero. But all these vehicles, however capable, have a decidedly un-futuristic feature: There's a human in the driver's seat, ready to grab control in case the robot goes rogue. California's Department of Motor Vehicles requires that safety driver to be there. But if autonomous technology is ever going to deliver on its promises, the human has got to go.

At MUFG, Mike said "robotics process automation" will handle half of branch operations by the end of the business year to March 2024, or 30 percent of the bank's total. By the time of full installation, the automation would have handled the equivalent of 9,500 employee's workload, he said.

When the Sony Aibo was discontinued in 2006, it was arguably the most sophisticated consumer robot that you could get your hands on. Aibo was smart, cute, fun. Many people who owned Aibos loved their robots (perhaps a bit too much), and even more people wished they'd had one. According to a recent report, Sony is reassembling the Aibo development team with the goal of releasing a new version of the little robot dog. We should note that this information comes from Nikkei Asian Review, not directly from Sony itself, and that the report doesn't directly cite any sources for this news.

Crucial time and tremendous amounts of resources are lost every day in the world's healthcare systems. Misdiagnoses cost unnecessary additional tests, result in delayed treatment plans and diminished survival or remission rates from what would have transpired had it been caught and identified correctly earlier. Trials, treatments and research completed in silos so there's no leveraging the insights across the country or the world. Some healthcare and technology innovators are collaborating and trying to change our current reality by experimenting with artificial intelligence (AI) and machine learning. Computers and the algorithms they run can scrub colossal amounts of data--much faster and more accurately than human scientists or medical professionals--to unearth patterns and predictions to enhance disease diagnosis, inform treatment plans and enhance public health and safety.

SAN FRANCISCO (Reuters) - Microsoft Corp said on Monday it was looking into whether Russians bought U.S. election ads on its Bing search engine or on other Microsoft-owned products and platforms, after rival Google said it had discovered such ads on its products.

"One of these things is not like the others," the television show Sesame Street taught generations of children. Let's move to the next level: "One or more of these things may or may not be like the others, and those variances may or may not represent systems vulnerabilities, failed patches, configuration errors, compliance nightmares, or imminent hardware crashes." Looking through gigabytes of log files and transactions records to spot patterns or anomalies is hard for humans: it's slow, tedious, error-prone, and doesn't scale. Fortunately, it's easy for artificial intelligence (AI) software, such as the machine learning algorithms built into Oracle Management Cloud. What's more, the machine learning algorithms can be used to direct manual or automated remediation efforts to improve security, compliance, and performance.

Even as machines known as "deep neural networks" have learned to converse, drive cars, beat video games and Go champions, dream, paint pictures and help make scientific discoveries, they have also confounded their human creators, who never expected so-called "deep-learning" algorithms to work so well. No underlying principle has guided the design of these learning systems, other than vague inspiration drawn from the architecture of the brain (and no one really understands how that operates either). Original story reprinted with permission from Quanta Magazine, an editorially independent publication of the Simons Foundation whose mission is to enhance public understanding of science by covering research developments and trends in mathematics and the physical and life sciences. Like a brain, a deep neural network has layers of neurons--artificial ones that are figments of computer memory. When a neuron fires, it sends signals to connected neurons in the layer above.

A simple example of Bayesian inference applied to a medical diagnosis problem. Here the problem is diagnosing a rare disease using information from the patient's symptoms and, potentially, the patient's genetic marker measurements, which indicate predisposition (gen pred) to this disease. In this example, all variables are assumed to be binary. The relationships between variables are indicated by directed arrows and the probability of each variable given other variables they directly depend on is also shown. Yellow nodes denote measurable variables, whereas green nodes denote hidden variables.

Four new features that make Google Home a better connected speaker than it was--but it still has growing pains, reports USA TODAY's Jefferson Graham on Talking Tech. SAN FRANCISCO -- In another era, young tech geeks saved their money for a state-of-the-art stereo system: a great turntable, powerful amplifier and an absolute killer set of stereo hi-fi speakers. That went away with the advent of digital and listening to music on computers, then phones and earbuds or tiny, portable speakers. Cut to 2017, and it's the odd return to the loud-speaker wars. Google's Rishi Chandra speaks about the Google Home Max speaker.