In this episode, I talk with Mateusz Modrzejewski, a professional musician and AI researcher and assistant professor at the Warsaw University of Technology, about AI-generated music: how it works, what artists think about it, the big copyright questions, and where AI tools can genuinely support the creative process instead of replacing it.

Outline

00:00 Episode highlights and introduction

00:49 Thoughts on AI-generated music

02:09 The good sides of AI

03:40 The bad sides of AI

04:43 How do professional musicians feel?

08:03 The data scraping problem and data poisoning research

11:33 How AI music generation actually works

15:04 How to start experimenting with AI music

18:26 Future of the music industry

25:22 The AI song contest

29:15 Resources to learn more

🎙️ This episode was recorded live at the Venture café at PyWaw in Warsaw.

Episode links

• AI song contest: https://www.aisongcontest.com/
• Librosa library: https://github.com/librosa/librosa
• Pedalboard library: https://github.com/spotify/pedalboard
• Intelligent Instruments Lab: https://iil.is/
• PanGenerator: https://pangenerator.com/
• Pyo library: https://github.com/belangeo/pyo
• ISMIR tutorials: https://ismir.net/resources/tutorials/
• Beyond supervised learning book: https://music-classification.github.io/tutorial/landing-page.html
• Fundamentals of Music Processing book: https://www.researchgate.net/publication/288774112_Fundamentals_of_Music_Processing
• NIME conference: https://www.nime.org/
• ZAiKS Lab https://www.zaikslab.tech
• ⁠Warsaw University of Technology https://www.pw.edu.pl

AI-generated music is on the rise, but what does that mean from a technical and creative perspective? In this upcoming episode, I talk with Mateusz Modrzejewski, a professional musician and AI researcher, about AI-generated music: how it works, what artists think about it, the big copyright questions, and where AI tools can genuinely support the creative process instead of replacing it.

In this episode, I’m chatting with Thibaud Colas — Product Lead & Engineering Manager at Torchbox, Wagtail product lead, and current President of the Django Software Foundation. We talk about digital sustainability: why the internet’s energy use matters, how to measure it, why performance is important for emissions, whether rewriting everything in Rust is the only solution, and why we should keep AI businesses more accountable.

Outline

0:00 — Episode highlights

0:58 — Guest intro

1:21 — Is carbon footprint a popular topic among developers?

3:44 — What’s the carbon impact of the web and software in general?

5:35 — How can we measure a website’s carbon footprint?

8:26 — What are Django’s and Wagtail’s plans to reduce their footprint?

9:35 — Does the programming language we use (e.g., Python or Rust) make a difference?

11:42 — What practical steps can developers take to lower their software’s impact?

12:25 — How do we raise awareness and make sustainability a mainstream topic in tech?

15:34 — Should businesses be accountable for their software’s footprint?

16:59 — What should AI companies and cloud providers be more transparent about?

Episode links

– Sustainable Web Design (methodology): https://sustainablewebdesign.org/

– Wagtail CMS (Torchbox): https://wagtail.org/

– Django Software Foundation: https://www.djangoproject.com/foundation/

– Climate Action Tech community: https://climateaction.tech/

– W3C work on web sustainability: https://w3c.github.io/sustainableweb-wsg/