A New Era of Superhuman Scientific Discoveries.
“My goal is simple. It is a complete understanding of the universe, why it is as it is and why it exists at all.“ — Stephen Hawking
A Legendary History | How It All Began — Learn the source of an exceptional legacy :
- Vincent Boucher | … un cerveau de l’aérospatial! — Le journal de Montreal
- Shooting Stars | Vincent Boucher — The Canadian Space Agency Employee Newsletter
- Vincent Boucher | Un (jeune) homme d’exception — Nathalie Petrowski, La Presse
AI + Aerospace | Physics | Robotics
Premium Vision : To be the keystone of the AI Space industry.
“Recognizing that Montreal is a world-class aerospace industry hub and a world leader in artificial intelligence, we’ve created Montréal.AI Space.“ — Vincent Boucher, B. Sc. Physics, M. A. Policy Analysis and M. Sc. Aerospace Engineering (Space Technology), Founding Chairman at Montréal.AI
Montréal.AI Space has a Jewel status in the Montréal.AI Portfolio.
“What I cannot create, I do not understand.“ — Richard Feynman
We are at the verge of a global technological shift.
Montréal.AI Space leverages aerospace engineering, applied artificial intelligence and space science researches for use in spaceflight, satellites, and space exploration on an unprecedented scale.
A new powerful model for a large number of emerging superintelligence giants spreading across a landscape.
“Any Sufficiently Advanced Technology is Indistinguishable from Magic.“ — Arthur C. Clarke
We are living in a period of unprecedented breakthroughs in science. Near future advances at the intersection of aerospace engineering and artificial intelligence hold out extraordinary prospects for the future of Mankind.
“Artificial Intelligence is about recognising patterns, Artificial Life is about creating patterns.“ — Mizuki Oka et al, #alife2018
Montréal.AI Space believes in enhancing Humanity’s well-being by leveraging superintelligence to explore the Stars : The place where we truly belong.
With higher ingenuity, we implements world‐class agents to design breakthrough deep learning algorithms with an understanding of our Universe.
“I think transfer learning is the key to general intelligence. And I think the key to doing transfer learning will be the acquisition of conceptual knowledge that is abstracted away from perceptual details of where you learned it from.“ — Demis Hassabis
Montréal.AI’s superhuman AI agents can learn from experience, simulate worlds and orchestrate meta-solutions.
Montréal.AI Space is offering a new world age of impactful technical prowesses on a truly global scale.
“Of course, particle physicists are among the first to realize that nature is compositional.“ — Yann LeCun
- Why does deep and cheap learning work so well? — Henry W. Lin, Max Tegmark, David Rolnick
- Introduction to astroML: Machine Learning for Astrophysics — Jacob VanderPlas, Andrew J. Connolly, Zˇeljko Ivezic ́, Alex Gray
- CosmoFlow: Using Deep Learning to Learn the Universe at Scale — Mathuriya et al.
- Bayesian Deep Learning for Exoplanet Atmospheric Retrieval — Frank Soboczenski, Michael D. Himes, Molly D. O’Beirne, Simone Zorzan, Atilim Gunes Baydin, Adam D. Cobb, Daniel Angerhausen, Giada N. Arney, Shawn D. Domagal-Goldman
- Galaxy morphology prediction using capsule networks — Katebi et al.
- Machine Learning for Physics and the Physics of Learning — Steve Brunton, Cecilia Clementi, Yann LeCun, Marina Meila, Frank Noe, Francesco Paesani
- MINERVA-II1: Successful image capture, landing on Ryugu and hop! — JAXA | Japan Aerospace Exploration Agency
- Restricted Boltzmann Machines for Collaborative Filtering — Ruslan Salakhutdinov, Andriy Mnih, Geoffrey Hinton
- A Practical Guide to Training Restricted Boltzmann Machines — Geoffrey Hinton
- GAIA DATA RELEASE 1 — European Space Agency
- Evolved Virtual Creatures, Evolution Simulation, 1994 — Karl Sims
- PHYSICS | MACHINE LEARNING - Recent papers combining the fields of physics and machine learning — physicsml
- AI Model Could Help Robots Navigate on the Moon and Mars Without GPS — NVIDIA
- Machine Learning and Likelihood-Free Inference in Particle Physics Slides | Video — Kyle Cranmer
- Enabling Dark Energy Science with Deep Generative Models of Galaxy Images — Siamak Ravanbakhsh, Francois Lanusse, Rachel Mandelbaum, Jeff Schneider, Barnabas Poczos
- Unity and DeepMind to Advance AI Research Using Virtual Worlds — Business Wire
- A look at deep learning for science — Prabhat
- Searching for Exotic Particles in High-Energy Physics with Deep Learning — Pierre Baldi, Peter Sadowski, Daniel Whiteson
- Estimating Cosmological Parameters from the Dark Matter Distribution — Siamak Ravanbakhsh, Junier Oliva, Sebastien Fromenteau, Layne C. Price, Shirley Ho, Jeff Schneider, Barnabas Poczos
Bringing contributions by scholars recognized as the foremost authorities in their fields, Montréal.AI Space is ahead of a trend that will profoundly influence the future of Humanity.
Montréal.AI Space is looking for successful Associates & Partners : Captains of Industries, Philanthropists, Iconic Tech Entrepreneurs, Financiers and World-Class Scholars to join us in this task of historic proportions.
✉️ Email Us : firstname.lastname@example.org
📞 Phone : +1.514.829.8269
🌐 Website : http://www.montreal.ai
📝 LinkedIn : https://www.linkedin.com/in/montrealai
🏛 Headquarters : 350, PRINCE-ARTHUR STREET W., SUITE #2105, MONTREAL [QC], CANADA, H2X 3R4 *Executive Council and Administrative Head Office
#AIFirst #MontrealAI #MontrealAISpace #MontrealArtificialIntelligence