Tools powered by artificial intelligence and machine learning can also be used in animation and visual effects. Nvidia senior solutions architect Rick Grandy noted that the benefit of such tools is that artists don’t have to replicate their own work. That includes deep learning used for realistic character motion created in real-time via game engines and AI, as well as a phase-functioned neural network for character control, whereby the network can be trained by motion capture or animation. Continue reading NAB 2018: Artificial Intelligence Tools for Animation and VFX

At a conference track on machine learning during the NAB Show in Las Vegas, Amazon Web Services M&E worldwide technical leader Usman Shakeel described his company’s toolsets. Shakeel addressed up front the question of whether machine learning can replace human creativity. “Can content ever create itself?” he asked. He emphasized that, in today’s world, machine-learning (ML) tools are being used to create efficient workflows, and curate and extract massive amounts of metadata. Continue reading NAB 2018: AWS Machine-Learning Tools for Content Creation

USC School of Cinematic Arts professor and editor Norman Hollyn spoke at a conference on machine learning about ML tools available today and those that are imminent for editing film/TV content. Underlying the growing importance of ML-powered tools for editors, Hollyn pointed out that editors who resisted the advent of digital nonlinear editing in the 1990s exited the industry. “AI is bringing things into the post production world and if we don’t start to look at and embrace them, we’ll be ex-editors,” he said. Continue reading NAB 2018: Machine-Learning Tools to Become Vital for Editing

As part of the Next-Generation Media Technologies education track at the upcoming NAB Show in Las Vegas, a half-day conference produced by Rochelle Winters will examine the latest trends in Machine Intelligence and Content Creation (Tuesday, April 10, 9:00 am – 12:00 pm). The program will examine how studios, creative service companies and filmmakers are using machine learning, deep learning and artificial intelligence to help produce content. Leading technologists, production execs and content creators will share the latest research and case studies involving machine intelligence. Continue reading NAB Program to Look at Machine Intelligence, Content Creation

Allstate’s AI-powered chatbot, Amelia, continues helping the insurance company’s call center employees solve customer service issues efficiently. Since her original deployment in September, she’s already helped these employees with more than 3 million client conversations, answering questions through an instant messaging platform on employee desktops. In January alone, Amelia helped on 250,000 calls. Allstate and other insurance companies are turning to chatbots to stay ahead of insurance-focused startups looking to compete.

Continue reading Allstate’s Digital Assistant ‘Amelia’ Now Helps Call Center Reps

ETC is participating in a restructured/streamlined NAB Show schedule (April 7-12, Las Vegas Convention Center). ETC directors Yves Bergquist (data & analytics), Phil Lelyveld (immersive media) and Seth Levenson (adaptive production) have programmed sessions for the Next-Generation Media Technologies education track, focusing on AI and machine learning, immersive media and cloud technology. The sessions are scheduled for Monday-Wednesday in North Hall 257. In addition, ETC will present Future of Cinema sessions in South Hall 222/223 on Sunday, April 8, prior to Monday’s official NAB Show floor opening. Continue reading ETC@USC to Present Sessions at the NAB Show in Las Vegas

As part of the Next-Generation Media Technologies education track at the upcoming NAB Show in Las Vegas, a half-day conference produced by Rochelle Winters will examine the latest trends in Machine Intelligence and Content Creation (Tuesday, April 10, 9:00 am – 12:00 pm). The program will examine how studios, creative service companies and filmmakers are using machine learning, deep learning and artificial intelligence to help produce content. Leading technologists, production execs and content creators will share the latest research and case studies involving machine intelligence. Continue reading NAB Program to Look at Machine Intelligence, Content Creation

Pandora believes it can out-playlist Spotify. The music streaming service has released new personalized playlist options for users, catering to moods, activities and genres. The feature is powered by Pandora’s Music Genome, an information database that “has been in development for over a decade and is capable of classifying music at the song level across 450 different attributes — ‘genes’ that can be as specific as what types of strings are on the guitar,” reports TechCrunch. Pandora’s new feature arrives on the eve of Spotify’s public debut, slated for early April (as a direct listing rather than IPO).

Continue reading Pandora Takes On Spotify With Debut of Personalized Playlists

Microsoft’s Brainwave system, which is “specialized hardware for AI computation,” was able to “get more than 10 times faster performance for a machine learning model that powers functionality of its Bing search engine,” reports VentureBeat. Brainwave is designed to run trained neural networks as quickly as possible with minimal latency and with the goal of providing “roughly real-time artificial intelligence predictions for applications like new Bing features.” This news was shared with a handful of Bing updates announced Monday.

Continue reading Microsoft Claims Brainwave Pushes Bing’s AI 10 Times Faster

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

Sprint is currently developing AI-powered software to help call center representatives better handle customer service. Sprint plans to use data related to customer calls to create “interaction assistants” that provide employees with best next steps. This effort is part of the company’s digital transformation project, which involves a partnership with Adobe Systems Inc. “Our focus has been about evolving and really becoming a digital company across all facets,” said Sprint CIO Scott Rice. Data has “become core across all our infrastructure and we really are changing our mindset.”

Continue reading Sprint Working On AI Software to Assist Its Call Center Reps

The Google Play Protect detection service, which scans Android apps for malicious activity, is enabled on more than 2 billion devices and detected 60.3 percent of Potentially Harmful Apps (PHAs) in 2017 using machine learning, according to Google’s Android Security 2017 Year in Review report. Google removed over 700,000 apps for violating its policies last year. While Play Protect uses a variety of tactics, machine learning is highly effective for catching PHAs, detecting things like inappropriate content, impersonation, and malware.

Continue reading Machine Learning Used in Detection of Harmful Android Apps

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

Google and the Department of Defense are exploring the use of artificial intelligence to identify objects in drone footage. The tech giant has been working with the Pentagon’s Project Maven, an initiative focused on big data and machine learning. According to sources, when the pilot project became an object of discussion at Google, some employees were angry that the company was working with the military on surveillance tech for drone operations. Google’s Eric Schmidt admitted that the tech community is concerned that the military-industrial complex will use Google’s research to kill innocent people. Continue reading Google, Government Partner on AI to Analyze Drone Footage

The marriage of cameras and artificial intelligence opens the doors to all kinds of interesting capabilities. For now, however, Google is introducing its Clips wireless smart camera with the pitch that AI will enable it to take better pictures than a dumb camera. While the $249 Clips uses machine learning to automatically capture short clips (motion photos without audio) of people and pets, Apple’s latest iPhone relies on face recognition to unlock, and now startup Lighthouse AI plans to add intelligence to a security camera to analyze the results. Continue reading Google Clips Camera Relies on AI to Capture Familiar Faces