Peter Wittek, a roving adventurer between machine intelligence and quantum physics
Peter Wittek and I met more than a decade ago while he was an exchange student in Singapore. I consider him one of the most interesting people I’ve met and an inspiration to us all.
Currently, he is a research scientist working on quantum machine learning, an emergent field halfway between data science and quantum information processing. Peter also has a long history in machine learning on supercomputers and large-scale simulations of quantum systems. As a former digital nomad, Peter has been to over a hundred countries, he is currently based in Barcelona where, outside work hours, he focuses on dancing salsa, running long distances, and advising startups.
S: Remind me again, what’s your background?
P: Thanks, Sriram. I graduated with a masters in mathematics in Budapest, then I graduated from the National University of Singapore with a PhD in machine learning. Since then, I worked on a number of topics ranging from designing learning algorithms for massively parallel architectures to quantum physics simulations. Currently I am in a group of quantum information theory in ICFO-The Institute of Photonic Sciences in Barcelona and I am also affiliated with the University of Borås in Sweden. We work a lot on quantum non-locality, and when I have time, I work on my pet topic, which is quantum machine learning.
S: I’ve heard of machine learning. What is quantum machine learning?
P: It is an emergent field in the intersection of quantum information processing and artificial intelligence. Basically the fundamental question is this: can we build a smarter AI if we have quantum resources? This is, of course, a simplification, but my bet is that the next major application of quantum technologies will be machine learning. We have already seen some fascinating demonstrations on actual data sets. I believe that generalizing classical statistical learning theory —> Read More