NAB 2018: ETC Keynote on the Audience Genomics Revolution

In a keynote address at NAB in Las Vegas, ETC data & analytics project director Yves Bergquist described how the changing economics of media audiences require new measurement methods and metrics. For the first time, he said, the media and entertainment industry can leverage behavioral psychology, computational neuroscience and machine learning to understand the deep cognitive relationship between audiences and content. He pointed to director Alfred Hitchcock’s prescient statement that, “Creation is based on an exact science of audience reactions.” Continue reading NAB 2018: ETC Keynote on the Audience Genomics Revolution

NAB 2018: Analytics Scientists Look at Social Media and Bots

Fabric Media chief executive/founder Jason Damata led a discussion at NAB with two experts in the field of social media intelligence. Dr. Indraneel Mukherjee founded LiftIgniter, which is “a machine learning personalization, recommendation and discovery engine” for websites and apps to have one-on-one conversations with users. Dr. John Kelly is chief executive at Graphika, which turns “network relationships into dynamic maps of social influence, enabling precision targeting and action to drive business results.” Continue reading NAB 2018: Analytics Scientists Look at Social Media and Bots

NAB 2018: IBM Watson on Refining AI for Closed Captioning

Closed captioning isn’t just for the hard-of-hearing anymore. According to Digiday, 85 percent of Facebook video is viewed without sound. That signals a trend of viewers who prefer to watch closed captioning, putting the heat on solutions providers to come up with compliant systems that are also accurate and speedy. With artificial intelligence, says IBM Watson Media senior offering manager David Kulczar, closed captioning can be enhanced to go beyond transcription, and automatically identify background audio descriptions. Continue reading NAB 2018: IBM Watson on Refining AI for Closed Captioning

NAB 2018: Artificial Intelligence Tools for Animation and VFX

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

NAB 2018: AWS Machine-Learning Tools for Content Creation

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

NAB 2018: Machine-Learning Tools to Become Vital for Editing

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

NAB Program to Look at Machine Intelligence, Content Creation

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 Digital Assistant ‘Amelia’ Now Helps Call Center Reps

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.

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ETC@USC to Present Sessions at the NAB Show in Las Vegas

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

NAB Program to Look at Machine Intelligence, Content Creation

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 Takes On Spotify With Debut of Personalized Playlists

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 Claims Brainwave Pushes Bing’s AI 10 Times Faster

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

Startup Using AI to Help Create Effects for Movies, TV, Games

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 Working On AI Software to Assist Its Call Center Reps

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

Machine Learning Used in Detection of Harmful Android Apps

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

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