The sprawling warehouse, which looks big enough to double as an airport hangar, is unofficially known as the "robot highway." Inside Amazon's Denver, Colo., "sortation center," an army of orange robots –– each one about the size of a large suitcase with a small conveyor belt on top –– glides across the concrete floor, picking up and then delivering packages to one of hundreds of chutes that organize each item by Zip code before they're shipped to customers. Though largely unknown to the outside world, the robots, known as Pegasus, have already logged more than 1.5 million miles of driving, according to an Amazon blog post describing work inside the warehouse. Amazon unveiled Pegasus during the keynote session at its first-ever re:MARS conference in Las Vegas this week, devoted to, in Amazon's words, "Machine Learning, Automation, Robotics, and Space." It was there that Amazon revealed that the company already has 200,000 robots working at dozens of distribution facilities around the world.

These days, nearly all the artificial intelligence-based products in our lives rely on "deep neural networks" that automatically learn to process labeled data. For most organizations and individuals, though, deep learning is tough to break into. To learn well, neural networks normally have to be quite large and need massive datasets. This training process usually requires multiple days of training and expensive graphics processing units (GPUs) -- and sometimes even custom-designed hardware. But what if they don't actually have to be all that big, after all?

Automated facial recognition poses one of the greatest threats to individual freedom and should be banned from use in public spaces, according to the director of the campaign group Liberty. Martha Spurrier, a human rights lawyer, said the technology had such fundamental problems that, despite police enthusiasm for the equipment, its use on the streets should not be permitted. She said: "I don't think it should ever be used. It is one of, if not the, greatest threats to individual freedom, partly because of the intimacy of the information it takes and hands to the state without your consent, and without even your knowledge, and partly because you don't know what is done with that information." Police in England and Wales have used automated facial recognition (AFR) to scan crowds for suspected criminals in trials in city centres, at music festivals, sports events and elsewhere.

Google plans to launch a video game streaming platform called Stadia, positioning itself to take on traditional video game business. Video games are following data and video into the cloud. Google, which has already announced its Stadia game streaming service will be available in November, will be showing that off at his year's Electronic Entertainment Expo (E3), which begins Saturday in Los Angeles. Microsoft is expected Sunday to reveal more about its own xCloud game platform, also being developed to deliver games via the cloud. Sony is partnering with Microsoft to augment its own cloud gaming strategy.

If you make a purchase by clicking one of our links, we may earn a small share of the revenue. However, our picks and opinions are independent from USA Today's newsroom and any business incentives. I'm here to tell you all about a sale that might just make your weekend. It's the kind of deal that only comes along once in a blue moon, like finding a diamond in the rough. Right now, the first generation Sonos One speaker, which typically retails for $199, is available on Amazon for just $149.99.

Machine learning, Big Data, and automation are revolutionizing global industry – and the energy sector is no exception. Innovation is driving technological progress, boosting economic efficiency, creating smarter business operations, and leading to more resilient infrastructure. It's why businesses and governments around the world are making advanced technology – including artificial intelligence – a top economic and national security priority. Energy companies are implementation big data and AI in versatile ways – and the sector is growing. The market for AI software in the oil and gas industry is expected to reach a whopping $2.85 billion by 2022.

A tiny crack in a nuclear reactor, skyscraper, bridge or dam can cause catastrophic consequences. The Minneapolis bridge collapse, which killed 13 people in 2007, is just one example of what can happen when structural integrity is compromised. Unidentified or under-identified structural damage in nuclear reactors can be cataclysmic. Inspection of critical systems such as nuclear reactors is complicated and time-consuming. Videos captured by an automatic crack detection system can easily misidentify small scratches or welds as cracks, so technicians must review videos frame by frame.

Diego Caicedo is the Co-Founder and CEO of OmniBnk, a neobank that provides financial services to small businesses in Latin America. Artificial intelligence and machine learning are said to revolutionize the financial world, changing the banking experience for the better. The implications of the technology are vast, though most banks are still in the early stages of adopting AI technologies. A survey by Narrative Science and the National Business Research Institute found that 32% of financial services executives confirmed that they are already using AI technologies such as predictive analytics, recommendation engines, and voice recognition. One major hindrance to AI adoption is legacy systems.

Native palms, such as the Sabal palmetto, play an important role in maintaining the ecological balance in Florida. As a potential side-effect of modern globalization, new phytopathogens like Texas Phoenix Palm Decline (TPPD) have been introduced into forest systems that threaten native palms. This presents new challenges for forestry managers and geographers. Advances in remote sensing have assisted the practice of forestry by providing spatial metrics regarding the type, quantity, location, and the state of health for trees for many years. Spatial details regarding the general palm decline in Florida were elucidated by using the tools found in Hexagon's ERDAS IMAGINE software in conjunction with R classification programing packages.

For its inaugural re:Mars conference, Amazon invited attendees it calls "dreamers and builders" -- business leaders, scientists and others who are making contributions to the field of artificial intelligence and machine learning. During the Wednesday keynote at the Las Vegas event, Amazon brandished its own AI credentials, making the case to its potential customers and partners that its teams -- across the business -- are pushing forward the stat of the art. Across every step of its e-commerce operations, AI is at work: Amazon shared the way it uses AI to power e-commerce forecasting, and it showcased StyleSnap, an AI-powered feature that lets shoppers in the Amazon app takes a picture of a piece of clothing and find similar items for sale. Amazon also revealed newest fulfillment center robots, called Pegasus and Xanthus, as well as a new drone that Amazon says will start commercial deliveries within months. For in-store shopping, Amazon revealed new details about the technology that drives its Amazon Go stores.