Music Information Retrieval at Spotify and the Future of ML Tooling with Andreas Jansson of Replicate - Machine Learning Engineered

Episode 17

Music Information Retrieval at Spotify and the Future of ML Tooling with Andreas Jansson of Replicate

Andreas Jansson is the co-founder of Replicate, a version control tool for machine learning. He holds a PhD from City University of London in Music Informatics and was previously a machine learning engineer at Spotify, researching and applying algorithms for music information retrieval.

Learn more about Andreas:

https://replicate.ai/

https://www.linkedin.com/in/janssonandreas/

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Timestamps:

02:30 Andreas Jansson

07:30 Overview of music information retrieval (MIR)

13:30 Why use spectrograms and not raw audio?

19:55 The potential for transformers in MIR

22:45 Most exciting applications for ML in MIR

29:20 Challenges in putting ML into production

36:45 What Andreas imagines for the future of ML tools

41:45 Why he's building a tool for ML version control (http://replicate.ai/)

52:55 What Replicate enables via integration or as a platform

01:02:55 Learnings from doing customer discovery for Replicate

01:14:10 "Github for ML models and data"

01:22:30 Rapid fire questions


Links:

WaveNet: a generative model for raw audio

Singing Voice Separation with Deep U-Net CNNs

Joint Singing Voice Separation and F0 Estimation with Deep U-Net Architectures

arXiv Vanity

Replicate

Replicate's Discord

About the Podcast

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Machine Learning Engineered
Helping you bring ML out of the lab and into products that people love.

About your host

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Charlie You

Charlie currently works as a Machine Learning Engineer at Workday. He graduated from RPI with a B.S. in Computer Science and taught himself ML through online courses and projects. In his free time, Charlie enjoys investing and trading, playing poker, and training Brazilian Jiu-Jitsu.