One of the major tasks in training machine learning (if not the major-task) is preparing the training data. This is a tedious task that requires people who like repetitive work. Though it is tedious, it is (in our opinion) even more important than knowing which model to use, what software to write to train the system.
The last few days, we were training our Keras2-based WaveNet on samples from Chopin. The samples are just two pieces by Frederic Chopin, recorded very long ago and thus out-of-copyright. We still have a long way to go (and also figure out why we had a dead-lock during Multi-GPU-training). Because of that deadlock, we are[…]
At Munich Artificial Intelligence Laboratories (M-AILABS), we experiment with a lot of technologies and methods. We also look for novel ways of doing things in the area of ML & AI.
One of my personal dreams is to have an AI-based solution that can “compose” music. And of course, it has to be music like the great Ludwig van. So, we started looking for some papers.
In 2018 the M3-Conference (Minds Mastering Machines) is held in Cologne between April 25th-26th.
Munich Artificial Intelligence Laboratories (M-AILABS) will be talking about “ML & AI: From algorithms to practical implementation” about the challenges, pitfalls and tasks from the moment of deciding to employ ML/AI until it can actually be trained (and hopefully deployed).