Creating, Discovering, and Listening to Audio with Artificial Intelligence


What does it mean to be human? Many would argue that it’s our ability to create artistically. Yet we've seen computers do just that -- to create catchy songs that we can't tell the difference of. So what does it mean for us humans?

This week, we're exploring the intersection of music, creativity and artificial intelligence with experts from Spotify, Amper and Audioburst. We'll learn how companies use machine learning to generate music, help us discover our favorite songs (Spotify Discover Weekly anyone?) and even listen to music.

To get inspired, listen to this catchy pop song ( Taryn Southern created with Amper technology or just turn on your Spotify Discovery weekly.

**NOTE to register, you must also RSVP on Eventbrite. ( We will use Eventbrite registrations for check-ins.**


6:00pm - Networking and Pizza

6:30pm - Kickoff and Sponsors (ThoughtWorks, IBM)

6:40pm - Talk #1: Drew Silverstein, Amper Music: How to Create Music with AI

7:10pm - Talk #2: Gal Klein, Audioburst: Building the Google of Audio Discovery

7:40pm - Talk #3: Eric Humphrey, Spotify: Teaching Machines to Listen to Music

8:10pm - Extended Q&A and Open Member Discussion

Talk #1: How to Create Music with AI

What if you could create music without any musical experience? Hollywood film composer Drew Silverstein founded Amper Music to enable anyone to do just this. Amper music is an artificial intelligence composer, performer, and producer that enables anyone to create unique music tailored to any content in seconds. Learn how self-crafted sound can save you from the headaches of music search and licensing fees while also elevating the quality of your creative content.

Bio: Drew Silverstein is the CEO and a founder of Amper Music. Previously, Drew was an award-winning composer, producer, and songwriter for film, television, and video games in Los Angeles at Sonic Fuel Studios. Drew graduated from Vanderbilt University's Blair School of Music, where he studied Music Composition and Italian, and holds an MBA from Columbia Business School.

Talk #2: Building the Google of Audio Discovery

The growing popularity of podcasts, smart home devices and voice-based apps are creating a massive opportunity for spoken-word audio content. Today, 24% of Americans listen to podcasts monthly and 70% of smart speaker owners say they listen to more audio at home since acquiring their device. The culmination of podcast and smart home device popularity is creating new demand for audio search.

Using AI, Audioburst transforms audio content into short searchable bursts, allowing users to filter through millions of minutes of radio, podcasts, videos and other spoken-word media in real-time by questions, keywords, categories and more. By enabling consumers to find audio clips and sounds bytes the same way we search for news articles, Audioburst is creating an entirely new listening experience.

Bio: Gal Klein ( is an expert in turning dreams into robust, cutting edge technologies. Before founding Audioburst, Gal held c-suite roles at PLYmedia, a performance-based ad exchange for ad networks, mBox, a leading music aggregator, and Goash, a software company specializing in various solutions for the entertainment industry. Gal has also served as a project manager for the Israeli Air Force, responsible for developing automated technical publications for the F-16 and Galaxy aircraft.

Talk #3: Teaching Machines to Listen to Music

Bio: Eric J. Humphrey ( is a research scientist at Spotify, and acting Secretary on the board of the International Society for Music Information Retrieval (ISMIR). Previously, he has worked or consulted in a research capacity for various companies, notably THX and MuseAmi, and is a contributing organizer of a monthly Music Hackathon series in NYC. He earned his Ph.D. at New York University in Steinhardt's Music Technology Department under the direction of Juan Pablo Bello, Yann LeCun, and Panayotis Mavromatis, exploring the application of deep learning to the domains of audio signal processing and music informatics. When not trying to help machines understand music, you can find him running the streets of Brooklyn or hiding out in his music studio.