In order to introduce ML/AI in your organization, Process Analysis must be the first step. Which processes can be automated? Where are the highest gains? What are the business impacts? We help you in all these preliminary steps…
OD Strategy for ML/AI
What is the organizational impact of employing ML/AI in your company? What do you need to consider? What are the risks to your organization? We help you identify all these and plan accordingly…
Software & Tools
We provide tools & software to kick-start your own ML/AI-projects. These tools, including Neural Network Models, allow you to jump-start your activities without a lot of upfront work.
We help you setup your in-house ML/AI-team in order to continue owning your business. This includes providing you with profiles, performing interviews with candidates, and much more…
We are a team of people enthusiastic about the possibilities that machine learning and artificial intelligence open up. We are especially aware of not only the possibilities but also of the risks that come along with such a revolutionary and disrupting technology. We have decades of experience in employing software to not only make business processes more efficient but also to empower people. Thus, we offer a full-range of services in the area of using ML/AI but also planning ahead on all matters of organizational change & disruption that comes with it.
The M-AILABS Speech Dataset is the first large dataset that we are providing free-of-charge, freely usable as training data for speech recognition and speech synthesis. Most of the data is based on LibriVox and Project Gutenberg. The training data consist of nearly thousand hours of audio and the text-files in prepared format. A transcription is provided[…]
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.
Our DNN (Keras2-based WaveNet) is now training on Ludwig van Beethoven, specifically the piano sonatas. You can find the complete works on Amazon* (no affiliate :-). Artist is Yukio Yokoyama (also, Amazon-Link).
We have some mixed results, but mainly lots of learnings…
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.