Researchers from Adobe, the Indian Institute of Technology and Stanford University teamed up to create SieveNet, an AI-powered technology that allows a user to virtually try on clothing. The “image-based virtual try-on” maps the item to the virtual body, retaining its characteristics without creating blurry or bleeding textures. According to banking company Klarna, 29 percent of shoppers want to virtually try on apparel, accessories and cosmetics and 49 percent would like solutions that take their measurements into account. Continue reading AI-Powered App Enables Improved Virtual Apparel Try-Ons

When your smart home takes stock of who’s there before turning the heat on to their favored temperature, that’s anticipatory technology. CNET editor-at-large Brian Cooley and CBS Interactive Tech Sites senior vice president, content strategy Lindsey Turrentine led a CES discussion on how data including location, human behavior, facial recognition and object recognition can help smart homes and smart devices anticipate human needs. “Some things will get better,” said Cooley. “And others might be unnerving.” Continue reading CES 2020: Smart Devices Enter an Anticipatory Tech World

Pinterest is now promoting itself as a “visual discovery engine,” where its 300 million global monthly active users can not only browse billions of images but also purchase the items they find there. For most of its users, Pinterest is a go-to place for home décor, gardening and personal style, allowing users to “pin” or post photos to create inspiration boards. According to Pinterest, its AI technology can accurately pinpoint 2.5+ billion objects in photos, millions of which can be purchased by clicking on the item. Continue reading Pinterest Becomes a Visual Discovery Engine for Shopping

Google is forming the Advanced Technology External Advisory Council (ATEAC), an external eight-member advisory group to “consider some of the most complex challenges [in AI],” such as facial recognition and fairness. The move comes about a year after Google issued a charter stating its AI principles, and months after Google said it would not provide “general-purpose facial recognition APIs” before the ATEAC addresses relevant policy issues. The advisory group will hold four meetings in 2019, starting in April. Continue reading Google Establishes Advisory Panel to Examine AI Fairness

Niantic, the company that released “Pokémon Go,” just acquired Matrix Mill, a U.K.-based computer vision/machine learning startup, with the goal of expanding its augmented reality capabilities. Niantic chief executive John Hanke also stated that the company this year will release a “major update” to its “Ingress” game as well as a new AR game, “Harry Potter: Wizards Unite,” and reveal additional games in the next few weeks. At an event, developers and journalists were able to try out the platform powering these games. Continue reading Niantic Acquires Matrix Mill to Advance AR Gaming Features

The American Civil Liberties Union (ACLU), leading more than 24 other civil rights organizations, has asked Amazon to stop selling Rekognition, its facial/object recognition system, to law enforcement. Amazon introduced this online service in late 2016, offering Rekognition at a low cost through Amazon Web Services. Pitching it to law enforcement with the idea it could be used to assist in criminal investigations, Amazon signed on the Orlando Police Department in Florida and Washington County Sheriff’s Office in Oregon. Continue reading ACLU Has Concerns Regarding AWS Facial Recognition Tool

Although using AI and machine learning tools in production may remain a lofty goal for some, such tools are already in use in some video workflows, from dailies through mastering. Moderated by Netflix coordinator, production technologies Kylee Peña, a panel discussion described the tools available and how they’re being used in real world applications. Google senior cloud solutions architect Adrian Graham described his company’s now-open sourced TensorFlow technology, and how it’s being used by the M&E industry. Continue reading NAB 2018: Machine Intelligence Toolsets in Video Workflows

Chinese startup Ryze Tech is debuting its smartwatch-sized, 80g toy drone in Las Vegas this week. Featuring vision-processing tech from Intel and flight stabilization from DJI, the $99 Tello will launch in China later this month and be available in the U.S. after March. The drone is aimed at younger users, with an emphasis on safety and ease-of-use, and features an HD camera for capturing 5-megapixel photos, 360-degree video, and live-streaming to a mobile device or third-party VR headset. The Tello is capable of flying for 13 minutes at a time and is controlled from a mobile app connected via Wi-Fi. Continue reading Startup Debuts Watch-Sized $99 Intelligent Toy Drone at CES

In May, research project Google Brain debuted its AutoML artificial intelligence system that can generate its own AIs. Now, Google has unveiled an AutoML project to automate the design of machine learning models using so-called reinforcement learning. In this system, AutoML is a controller neural network that develops a “child” AI network for a specific task. The near-term goal is that AutoML would be able to create a child that outperforms human versions. Down the line, AutoML could improve vision for autonomous vehicles and AI robots. Continue reading Google Intends to Advance Machine Learning With its AutoML

On November 29 at the AWS re:Invent conference, Amazon Web Services introduced its AWS DeepLens, a video camera whose main purpose is to teach developers how to program AI functions. The camera comes loaded with different AI infrastructures and AWS infrastructure such as AWS Greengrass Core and a version of MXNet. Developers can also add their own frameworks like TensorFlow. The 4-megapixel camera can shoot 1080p HD video and offers a 2D microphone system for recording sound, in the form factor of an action camera on top of an external hard drive. Continue reading Amazon Debuts Intel-Powered DeepLens Camera to Teach AI

Developers digging through the firmware of Apple’s upcoming smart speaker, HomePod, found evidence that the company’s iPhone camera may soon use machine learning to recognize objects and scenes and adjust settings to create the best photo, all in real-time. That’s the information made public in a HomePod firmware leak. Unclear is whether that feature will be introduced with the iPhone 8 this fall, although developer Guilherme Rambo has discovered details that suggest it will debut as “SmartCam” capability. Continue reading Leaks Point to SmartCam Debut in Upcoming Apple iPhones

As another example of the significant advances we have been following in artificial intelligence and deep learning, Chinese search giant Baidu has introduced Deep Voice 2, the second iteration of its compelling text-to-speech system. The company introduced Deep Voice just three months ago, with the ability to produce speech “in near real time” that was “nearly indistinguishable from an actual human voice,” according to The Verge. While the first system was limited to learning one voice at a time, “and required many hours of audio or more from which to build a sample,” the updated version “can learn the nuances of a person’s voice with just half an hour of audio, and a single system can learn to imitate hundreds of different speakers.” Continue reading Text-to-Speech System Quickly Mimics Hundreds of Accents

Next month, Snapchat will introduce Memories, a new feature designed to let users save favorite photos and videos, re-edit them by adding filters and text and then re-share the latest versions. Included is a search function that lets the user search Memories by date, location or keywords. Prior to Memories, a Snapchat user could save a photo or video by downloading it to her smartphone, but couldn’t view it in the app or share it. Memories still does not allow a Snapchat user to save a photo/video sent by someone else. Continue reading Snapchat to Debut Memories to Save, Tweak, Re-Share Snaps

The ONAGOfly drone fits in the palm of your hand, but it comes with built-in features that are comparable with bigger and more expensive drones. The $259 flying camera system captures 1080p HD video and has smile-recognition technology and auto-follow technology to help operators capture the perfect shot. As far as safety, the ONAGOfly has obstacle avoidance sensors and can withstand wind speeds of up to 3.3 m/s. The drone is so small that it doesn’t even need to be registered with the FAA. Continue reading Smart Nano Drone Packs Big Features into Tiny Flying Machine

Baidu, a Chinese company best known for its Internet search engine, has entered the competition with other Internet companies and automobile manufacturers to create an autonomous vehicle. The company has already invested heavily in artificial intelligence and developed software called the Baidu AutoBrain System, which automatically records 3D road data and recognizes objects and road lanes. This expertise may help Baidu gain an edge over Google, General Motors, Tesla and Ford. Continue reading Baidu Joins the Race to Get Self-Driving Vehicles on the Road