Music Information Retrieval at Spotify and the Future of ML Tooling with Andreas Jansson of Replicate
Publisher |
Charlie You
Media Type |
audio
Categories Via RSS |
Business
Careers
Science
Technology
Publication Date |
Dec 15, 2020
Episode Duration |
01:33:39

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/

Every Thursday I send out the most useful things I’ve learned, curated specifically for the busy machine learning engineer. Sign up here: http://bitly.com/mle-newsletter

Follow Charlie on Twitter: https://twitter.com/CharlieYouAI

Subscribe to ML Engineered: https://mlengineered.com/listen

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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

vanity.com/">arXiv Vanity

Replicate

Replicate's Discord

Andreas discusses the state of ML research for music information retrieval, the future of tools for data science and ML engineering, and Replicate, his recent project aiming to solve version control for ML models.

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/

Every Thursday I send out the most useful things I’ve learned, curated specifically for the busy machine learning engineer. Sign up here: http://bitly.com/mle-newsletter

Follow Charlie on Twitter: https://twitter.com/CharlieYouAI

Subscribe to ML Engineered: https://mlengineered.com/listen

Comments? Questions? Submit them here: http://bit.ly/mle-survey

Take the Giving What We Can Pledge: https://www.givingwhatwecan.org/

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

vanity.com/">arXiv Vanity

Replicate

Replicate's Discord

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