NYC Media Lab’s projects and programs in AI, machine learning, natural language processing, computer vision, voice, data visualization and more.
Recent Experiments with corporate members
Viacom is building rich metadata around its content assets using a large text corpora composed of closed caption files.
Hearst is developing partnerships with universities and startups that will expose its data science team to new ideas emerging in data disciplines, including machine learning and artificial intelligence.
NYC Media Lab presented the NBCUniversal Blockchain Prototyping Fellowship: Content Monetization to explore new pricing models for the media industry.
In a hackathon organized by NBCUniversal and NYC Media Lab, over 2 dozen teams worked across 2 prototyping tracks to help design technology solutions for real-world problems. By supporting nonprofits, social entrepreneurs, and community organizations, and by using the power of media and technology to benefit the communities we serve, we can help solve important social issues.
With the goal of improving the Audible customer experience, Audible collaborated with a computer science team from Columbia University to experiment with open-source natural language processing tools.
In connection with Bloomberg LP’s annual Data for Good Exchange conference, Bloomberg LP and NYC Media Lab launched an awards program for faculty from New York City and beyond to apply for impact grants to advance their research focusing on data for social good.
In collaboration with NYU Courant and NYU Center for Data Science, Hearst is exploring the promise of automation by using new tools, ranging from natural language processing to artificial intelligence to computer vision techniques and automatic image annotation.
To explore the world of audio storytelling using the all-new Audible API, Audible partnered with NYC Media Lab to present the Future of Listening Hackathon. The event was held on April 15–16, 2016 at New York City’s Civic Hall.
For the Press Play project, ESPN sought out a team of researchers that could evaluate and deliver prototypes aimed at improving the mobile experience for watching ESPN videos on ESPN.com, with the ultimate goal of getting sports fans to “press play.
Vonage and NYC Media Lab convened a team from NYU’s Tandon School of Engineering to examine IoT products to develop a perspective on what’s possible with machine learning platforms and algorithms, and to determine which algorithms would be best suited for the various types of learning that would be required in the IoT field.
ESPN came to NYC Media Lab with a desire to explore possible ways to connect with the next generation of sports fans, with particular attention to millennials. ESPN was interested in working with those who could provide the best insight into the generation’s preferences and behaviors—millennials themselves.
Driving user engagement is a core objective for media companies, even if there is less agreement on the best metrics with which to measure it. As companies begin to capture more available data, and further develop the sophistication to wield it, the opportunity to drive engagement through personalization bears more and more promise...
This project, executed by NYU Tandon, focused on building models to study the likely future bandwidth use of four different emerging trends that may potentially be disruptive to Internet bandwidth. In conjunction with Charter Spectrum, NYU Tandon conducted a five-month pilot study of these issues to build initial bandwidth models for these trends.
This project was a study on the measurement and analysis of adaptive streaming over HTTP. Researchers at NYU Tandon, working with experimental data from adaptive streaming systems like Netflix and Redbox Instant, measured their performance in typical user networking environments, such as residential access networks and campus networks.