After five years at the Music Technology Group, I’m pretty excited to announce that I have accepted a full-time position as a researcher at Dolby Laboratories in Barcelona!Continue reading
Which is the outtake of Artificial Intelligence (AI)? This is a recurrent conversation topic among AI practitioners, specialized journalists, and brave politicians. Although some simple concepts are clearly conveyed to the general audience, there are some others that are not so widely known. In this
Since AI is impacting our lives through products available in the marketplace, the goal of this post is to analyze what’s up with AI systems when consumed via the free market. In other words, AI is developed and consumed in a market-driven fashion and I would like to better understand which are the consequences of that. Hence, I’ll be focusing on the economic side of AI to show that for encouraging the main AI actors to behave ethically we better (directly) act over the market.Continue reading
In this series of posts I have written a couple of articles discussing the pros & cons of spectrogram-based VGG architectures, to think about which is the role of the computer vision deep learning architectures in the audio field. Now is time to discuss what’s up with waveform-based VGGs!
- Post I: Why do spectrogram-based VGGs suck?
- Post II: Why do spectrogram-based VGGs rock?
- Post III: What’s up with waveform-based VGGs? [this post]
Me: VGGs suck because they are computationally inefficient, and because they are a naive adoption of a computer vision architecture.
Random person on Internet: Jordi, you might be wrong. People use VGGs a lot!Continue reading
Me: VGGs suck because they are computationally inefficient and because they are a naive adoption of a computer vision architecture.
Random person on Internet: Jordi, you might be wrong. People use VGGs a lot!