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And the company keeps the algorithms themselves secret.Unfortunately, still too many people think that the ranking of the results is based on ‘reliability’.Large-scale Machine Learning: Deep, Distributed and Multi-Dimensional: Modern machine learning involves deep neural network architectures which yields state-of-art performance on multiple domains such as computer vision, natural language processing and speech recognition.As the data and models scale, it becomes necessary to have multiple processing units for both training and inference.At Eindhoven University of Technology, where I work, all students (future engineers) have to take courses on ethics, such as engineering ethics.The non-neutrality of technology is an important part of these courses.In particular, she has been spearheading the development and analysis of tensor algorithms.

These functionalities are available in the Tensorly package with MXNet backend interface for large-scale efficient learning.

Pushing the current boundaries of deep learning requires using multiple dimensions and modalities.

These can be encoded into tensors, which are natural extensions of matrices.

The way you as an engineer design a technology influences how users can make use of it: this is just a simple example to illustrate that this is not a neutral process.

With regard to algorithms, there is a plethora of examples that show how human biases slip into them, such as racist profiling in ‘precrime methodology’.

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