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First ZHAW Datalab Meetup on the topic of Quantum Machine Learning

The first ZHAW Datalab Meetup focussed on the topic of quantum machine learning - from theory to practical application.

Participants of the first ZHAW Datalab Meetup on Quantum Machine Learning.
Participants of the first ZHAW Datalab Meetup on Quantum Machine Learning.

Students from various Bachelor's, Master's and doctoral programmes at the ZHAW Zurich University of Applied Sciences as well as lecturers and professors from different institutes came together for the first ZHAW Datalab Meetup.

Pavel Sulimov took us on a journey through the world of quantum computing. We learnt about the fundamental differences between the classical world and quantum computing in terms of how information is represented and how these differences can be used to solve certain problems more efficiently. So will quantum computers crack our passwords in the near future? There is no cause for concern at the moment - but the mathematical details have been postponed to an upcoming lecture.

In terms of machine learning, hybrid approaches that combine classical and quantum computing seem to be the most promising. So could quantum machine learning be the next big thing after large-scale deep learning models? Pavel remains cautiously optimistic. Scaling current approaches, minimising quantum errors and tackling decoherence are key challenges that need to be overcome before this technology reaches its full potential.

What is particularly exciting for students and researchers today is that quantum computers no longer exist only in theory. There are frameworks that can be used to simulate a quantum computer, and companies such as IBM offer public access to real quantum hardware. During the practical part of the meetup, Pavel therefore also introduced the QisKit Python package and showed how to interact with the IBM quantum platform.

During the course of the evening, there was also the opportunity to discuss "Life, the universe and everything" over pizza and drinks - entangled in the fascination for technology and engineering work.