Palo Alto-based startup Arraiy is developing methods for automating part of the often-tedious process of producing visual effects for movies, TV shows and video games. “Filmmakers can do this stuff, but they have to do it by hand,” said CTO Gary Bradski, who has worked with tech companies such as Intel and Magic Leap. The Arraiy team, led by Bradski and CEO Ethan Rublee, “are building computer algorithms that can learn design tasks by analyzing years of work by movie effects houses,” reports The New York Times. “That includes systems that learn to ‘rotoscope’ raw camera footage, carefully separating people and objects from their backgrounds so that they can be dropped onto new backgrounds.” Continue reading Startup Using AI to Help Create Effects for Movies, TV, Games

Facial recognition is getting better by leaps and bounds, and some of the examples of how it is being used are disturbing. In Russia, the website FindFace matches submitted photos to VK, that country’s Facebook knock-off. Trolls are using it to identify and harass women who appear in adult videos. China uses cameras with facial recognition to tag jaywalkers, and, in Dubai, police wear Google Glasses to identify people. In the U.S., the government facial recognition system can already identify the faces of half of all American adults. Continue reading Invasive Use of Facial Recognition Tech Already Widespread

CES 2018 is out the gates, and, as expected, artificial intelligence is still very much present in products, conversations and conference panels. Still in its quest to become synonymous with AI, Nvidia did not disappoint at its press event Sunday and its “Autonomous Machines” keynote Tuesday morning. From doubling down on autonomous vehicles to AI-composed music (in partnership with Disney), to a technically impressive foray into intelligent video analytics to power smart cities, the CES darling is still — by far — the biggest AI enthusiast at the show. Continue reading Artificial Intelligence Front But Not Center at CES Trade Show

In a roving two-hour presentation, Nvidia CEO Jensen Huang unveiled a raft of products, partnerships and performance achievements at CES 2018. Focusing mostly on the automotive industry, Huang showed off the GPU giant’s new autonomous driving software stack powered by Xavier, a system-on-chip (SoC) for artificial intelligence-empowered car platforms, and touted partnerships with more than 320 car and truck companies. Huang also showcased a large HDR display for giant-screen, PC gaming and streamed an AI-generated motion picture theme composed in the style of “Star Wars” by John Williams. Continue reading CES: Nvidia Stakes Claim to Automotive and Entertainment AI

In 2012, University of Toronto professor Geoffrey Hinton and two grad students showed off artificial neural networks, a technology that empowered machines to understand images. Google hired Hinton and his grad students six months later; Hinton now splits his time between Google and the university. Although neural networks now underlie speech transcription and many other tasks, Hinton isn’t enthused over the technology he helped launch. Instead, he’s now bullish on an “old” idea that could help reshape artificial intelligence. Continue reading Google’s Geoff Hinton Tests Capsule Networks as AI Solution

Waiting for a video to buffer may become an annoyance of the past. Researchers at MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) are working on streaming algorithms that use AI to improve load rates and, thus, reduce buffering. Dubbed Pensieve, the new technology relies on machine learning to navigate the often-chaotic and ever-changing conditions of networks in real-time, based on a system of rewards (when the video loads smoothly) and penalties (when it’s interrupted). Meanwhile, Netflix is working on its own AI solution to address buffering. Continue reading MIT and Netflix Testing AI-Based Algorithms to Curb Buffering

Intel, Facebook and other tech companies are working together on a chip aimed to power artificial intelligence that will also be direct competition for Nvidia’s chips. The new Intel chip will be built to accelerate deep learning, which, among other tasks, will allow computers to recognize objects in photos and specific words in speech. The chip, dubbed the Nervana Neural Network Processor and based on Intel’s acquisition of startup Nervana Systems, is slated to be released in limited quantities in 2018. Continue reading Intel Turns to Facebook, Other Tech Companies for AI Chip

The new iPhone X offers several new features, but none of them more innovative than the neural engine that is part of Apple’s new A11 Bionic SoC processor. Artificial neural networks, which excel at processing images and speech, are behind the phone’s ability to recognize the user’s face to unlock it, transfer facial expressions onto Animoji (animated emoji), and other, as-of-yet unspecified features. As Apple moves into augmented reality and image recognition, the neural engine will likely be central to these endeavors. Continue reading Apple’s Innovative Chips Ready to Lead in AR, AI, Wearables

Amazon is developing systems based on artificial intelligence algorithms that are aimed at spotting fashion trends and, eventually, shaping them. The effort could boost Amazon’s sales in clothing, perhaps even gaining a dominant position in fashion. The e-commerce giant isn’t alone in making recommendations based on products appearing in social media, and highlighting the resulting trends; Instagram and Pinterest also pinpoint trends and react quickly to them, as does startup subscription service Stitch Fix. Continue reading Amazon Creates AI-Based Tools for Spotting Fashion Trends

At The Reel Thing, an AMIA (Association of Moving Image Archivists) conference, Hollywood technologists and filmmakers gathered to hear presentations on challenges in restoration, remastering and archiving. PurePix Images chief executive Michael Inchalik and University of Georgia mathematics professor Alexander Petukhov looked at how Algosoft is developing software to repair vertical scratches, one of the toughest challenges in digital restoration. “We’re discussing a high-level restoration workflow,” said Inchalik. Continue reading New Software Tackles Scratch Removal for Film Restoration

Microsoft has debuted Brainwave, a system that improves AI hardware performance, enabling machine learning at speeds beyond what’s available today with CPUs or GPUs. At the Hot Chips symposium in Cupertino, California, researchers showed off a Gated Recurrent Unit model running on Intel’s newly released Stratix 10 FPGA (field programmable gate array chip), at a speed of 39.5 teraflops without batching operations. Brainwave currently supports models constructed with Microsoft’s CNTK framework and Google’s TensorFlow framework. Continue reading Microsoft Intros Brainwave, Jumpstarting AI Hardware Speed

Google and MIT scientists have collaborated to explore how computational photography, which uses machine learning and specialized algorithms, can be used to retouch photos in real time. The team trained neural networks via 5,000 images created by Adobe and MIT; five different photographers retouched each image, teaching the software the various ways a photo could be improved. Elsewhere, Nvidia and UC Santa Barbara created a computational zoom for photographers that lets them change a photo’s perspective in post production. Continue reading Researchers Focus on Computational Photography Solutions

Intel just unveiled its Xeon Scalable line, a new generation of 58 processors designed for “secure, agile, multi-cloud data centers.” Priced from $200 to $10,000 each, this array of new chips should serve as a clear message to would-be competitors that Intel plans to continue its dominance in the data-center market segment, which offers better profit margins than chips for PCs. Threatening Intel’s leadership are companies creating specialized chips aimed at maximizing performance of artificial intelligence programs. Continue reading Intel Eyes the Future With New Family of Xeon Server Chips

AI visionary Andrew Ng — co-creator of the Google Brain research project, former chief scientist at Chinese web giant Baidu, and co-founder of online education platform Coursera — has launched a new AI company called deeplearning.ai. While details are scarce at this point, Ng recently promised “more announcements soon” via tweet. The company’s website simply features the tagline “Explore the frontier of AI,” followed by #deeplearniNgAI and “August 2017,” suggesting more information is coming later this summer. Continue reading Andrew Ng Leaves Baidu’s AI Group to Launch New Startup

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