ML Business & Strategy


Three Key Considerations When Implementing AI

For some time now, artificial intelligence that allows an image to be generated from a text input, has been more or less freely available. Well-known examples are OpenAI's DALL-E and Google's Imagen. Not too long ago, Stability.ai's DreamStudio.ai was released, which, unlike the other AIs, is completely open source.

4 arguments to convince your boss

You can't see the forest for the trees anymore, and you need new inspirations urgently? Then ML Conference is the place to be. Connect with like-minded people, widen your horizon while gaining deep insights and practical knowledge of the latest trends and technologies.

The Ethics of AI – dealing with difficult choices in a non-binary world

In the field of machine learning, many ethical questions are taking on new meaning: On what basis does artificial intelligence make decisions? How can we avoid the transfer of social prejudices to machine learning models? What responsibility do developers have for the results of their algorithms? In his keynote from the Machine Learning Conference 2019, Eric Reiss examines dark patterns in the ethics of machine learning and looks for a better answer than "My company won’t let me do that."

Keynote http://commodity.ai

How can AI be turned into a commodity – a cheap, easily available product, that is used by everyone? Will it even be possible to turn AI into a commodity at all? Dr. Pieter Buteneers (Robovision) adresses these questions in this keynote from ML Conference 2018 in Berlin.

AI as a smart services for everyone

If you cannot or do not want to build an AI project from scratch, you have countless choices of ready-made services. But what can you do if the finished services do not fit the project? Customizable AI and ML models in the cloud, which you can train with your own data, provide a remedy.

Behind the Tracks