It was a wonderful week for us – learning about data science, computer simulations, and use of artificial intelligence in Astronomy. We have been creating space projects and undertaking science outreach events for last 4 years reaching out to thousands of children, teachers, and families. We regularly give demonstrations of our projects at Maker Festivals, NASA Space Apps Events, Ontario Science Centre, Toronto International Film Festival, School Fairs, hackathons, and libraries.
It means we have to keep learning to come up with new ideas for upcoming projects. This would be possible without the science communication and outreach carried out by several Canadian and International organizations and institutions where they share their scientific research with the general public. We acknowledged this role of science outreach and communication at the opening address given by Artash Nath (We progress when we keep asking “Why”) at the Science March Toronto on 14th April 2018.
The Perimeter Insitute Public Lecture: Artificial Intelligence and the Complexity Frontier
On May 2, 2018 the Perimeter Institute for Theoretical Physics in Waterloo broadcasted its public lecture “Artificial Intelligence and the Complexity Frontier” by Roger Melko (Associate Faculty, Perimeter Institute and University of Waterloo). It was a very insightful lecture on quantum computing, machine learning, artificial intelligence (A.I), and fundamental physics and delivered in an easy to understand, jargon-free manner, full of examples and illustrations. It brilliantly communicated the research being done by Roger and his team at the Perimeter Institute and its application to the general public.
We watched it twice as we were impressed by how far and how fast artificial intelligence, deep learning, and neural networks have evolved. Watch his lecture here.
Roger explained how physical limits to computing would prevent us from conducting large-scale simulations using brute computing force – simply because there are not enough particles in the whole universe (the upper limit is the limit is 10 to the power of 80) to simulate all the scenarios.
Increasing the use of artificial intelligence algorithms and self-learning networks is one way to overcome the physical computing limit and accelerate new scientific discoveries through simulations. Deep learning networks are able to accurately classify and interpret images (sometimes even better than humans) and even human expressions. (eg: the Amazon Rekognition Service). When combined with computer vision, language translation, and autonomous robotic actions, they are altering the human-machine interface and skills sets needed for employment and economic growth. Incidentally, an important event relating to it: FutureWorld 2018 on the rise of Robots, Artificial Intelligence, and Smart Machines is coming up in Toronto on 9th June. More details at http://fitc.ca/event/futureworld2018/schedule/
The part of his talk that we enjoyed the most was – how thoughts of this deep learning network would be different than ours? For instance, how does a deep learning system visualize a tree or a human? This is also called the Deep Dreaming and the results are stunning. It made us question are we already approaching the human-machine singularity?
University of Toronto Public Lecture: Simulating the Universe
Against this backdrop of new knowledge from the Perimeter Institute, we enjoyed the exhaustive public programming offered by the University of Toronto’s Department of Astronomy and Astrophysics, and the David Dunlap Institute under it monthly AstroTour on May 3, 2018. The University offers Free Astronomy Public Tours on the first Thursday of almost every month and includes a free public talk, telescope observing, and planetarium shows – an amazing initiative to bridge research and outreach efforts by engaging with the general public – young and adults.
The evening started with a lecture by George Stein on “Simulating the Universe“. George is a fourth-year Ph.D. student in the Department of Astronomy & Astrophysics at the University of Toronto and works at the Canadian Institute for Theoretical Astrophysics (CITA). Check out his amazing website on Computational Cosmology at http://cita.utoronto.ca/~gstein
George’s talk focused on simulations of the universe – on the evolution of a single galaxy to galaxy clusters, the role of dark matter and dark energy – being carried out using some of the largest supercomputers. The data for these simulations was obtained by standing on the shoulders of giant and heroic telescopes and observatories, including the Sloan Digital Sky Survey (SDSS), the Hubble Space Telescope, the Planck Space Observatory and others. These simulations are extremely complicated and yet extremely important as they are able to model developments happening at macroscopic time frame (millions of years) and spatial scale (millions of light years) and further our understanding of the Universe.
The part of his talk we enjoyed the most was how cosmic simulations have evolved. They were carried out by doing calculations by hand in 1951, to the use of computers in 1961, and then by clusters of computers and supercomputers – to creating virtual reality models.
Bridging the Learnings: Perimeter Institute and the University of Toronto
It was interesting to note how the simulations have become more complex using ever more computing power and data… bringing us closer to the physical limits of computing as mentioned by Roger Melko in his public lecture.
So Artash asked the first question of the evening to George Stein on the possibilities of using A.I, Deep Learning and Deep Dreaming algorithms for cosmic simulation and if they would provide more accurate results. George agreed that this approach has a lot of potential and they have started to use artificial intelligence algorithms in their cosmic simulation models. He directed us to his research partner Phil who is incorporating artificial intelligence into simulations using Python.
Post-lecture we had a rich discussion with Phil and he elaborated upon the tools they are using including Tensor Flow and Kares installed through Python. Interestingly we were familiar with these tools as we had used some of the tools in our previous project: Space-REX for predicting the risk of asteroid collision using Artificial Intelligence. He shared several resources with us including http://scikit-learn.org/stable/ which we plan to incorporate into our upcoming projects and outreach activities.
The evening was not yet over – a number of activities were organized by the University of Toronto’s AstroTour. There was a virtual reality pod where immersive cosmic simulations explained earlier by George Stein on the formation of galaxies and galaxy clusters could be experienced.
It was followed by a visit to the dome where the big telescopes are housed and we learned more about research projects they are being used in, and how they are controlled using computers.
We were impressed by the number of Graduate Students from the Department of Astronomy and Astrophysics who were on hand to explain different aspects of Astronomy and answer all our questions.
On exoplanets (Ryan Cloutier), on Habitability of exoplanets and 3D models of Space Telescopes (Adiv Paradise), Open and globular clusters (Rachel Simone), and many others who explained to us about Cosmic Microwave Background and simulation models.
Sharing our learning: Kids teach kids!
We thank the University of Toronto and the Perimeter Institute for these public events which inspire the general public and creates a virtuous link between Research, Outreach, and Curiosity. Curiosity feeds research and outcomes of research should become the next generation curious.
We will be playing our part in communicating what we have learned from the public lectures at the Perimeter Institute and the University of Toronto by creating new space projects and demoing our existing projects (including the TRAPPIST1 and the Cosmic Dance Puppets) to curious children, parents, teachers, and the general public at upcoming events. These include the Science Rendezvous/ SciArt Gallery at the University of Toronto) on May 12, the Maker Expo (Kitchener) on June 2-3, FutureWorld 2018: The rise of Robots, Artificial Intelligence, and Smart Machines, Toronto June 9, the Royal Astronomical Society of Canada Toronto public meeting at the Ontario Science Centre on June 20, and several others.
