2:10 - Using AI to augment and reshape creativity in a modern world. Psychological creativity and story creativity - can an AI model help AI music artists, today, get off their creative blocks?
12:15 - Attempt to define ‘good’ music, using a cognitive music literature background.
17:00 - Are we better or worse off, for AI in audio/music? Is it sustainable for the effort input and cost, impact and efficiency output?
22:35 - ‘Deep Nostalgia” from myheritage initiative, and GPT-J - looking for strengths in the two approaches.
29:25 - The Sound of AI community - a HuggingFace version for audio?
31:15 - Train a DL - CNN sound classifier built with Pytorch and torchaudio on the Urban Sound 8k dataset.
35:00 - Is deep learning a dead end for artificial intelligence?
38:05 - Could someone that is a pure tech profile ever be in such an intersection in sync with the artistic world? Is it a pre-req to be domain savvy to build AI audio solutions?
42:10 - Helping music tech companies with a focus on audio (voice, speech, sound), the experience so far.
49:45 - Hard problems to solve when dealing with AI audio - Top three.
56:50 - First piece of music composed by a machine.
Podden och tillhörande omslagsbild på den här sidan tillhör
Alexandra Petrus. Innehållet i podden är skapat av Alexandra Petrus och inte av,
eller tillsammans med, Poddtoppen.
