Sky Canvas Project: Fireworks From Space
Star-ALE is the new Japanese start-up company looking to launch the latest spectacle in entertainment that is set to blow us all away! The new Sky Canvas Project is a new development that is looking to combine astronomy with entertainment and bring us the world’s…
Star-ALE is the new Japanese start-up company looking to launch the latest spectacle in entertainment that is set to blow us all away! The new Sky Canvas Project is a new development that is looking to combine astronomy with entertainment and bring us the world’s first satellite-based artificial meteor shower that is to be showcased at the 2020 Summer Olympics which will be held in Tokyo.
With real shooting stars being scarce and a whole meteor showers being even rarer, not many people get to experience these amazing natural phenomena. But, that could all be set to change. Although the Sky Canvas Project is obviously not the real thing, Star-ALE is hoping it will be just as spectacular, if not even better!
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The thing with real meteor showers is that are often over quite quickly. With The Sky Canvas Project, the showers will be designed to travel at slower speeds and longer distances in the sky than naturally occurring showers creating the maximum visual experience. Star-ALE says that their artificial shooting stars will shine just slightly dimmer than Sirius, the brightest star that can be seen from earth, and will be used from a range of materials that will create a host of colors as the meteors burn through the sky.
As with every new innovative product, there comes a downfall – the cost. Every single meteor pellet that is used as part of the artificial meteor shower will cost Japan over $8000. Add that to the expense of the construction of the satellite and the launch itself and the figures stack up quite quickly. But, Astronomy is widely supported in Japan by public funding and government assistance so I am sure it will certainly be one big display to remember at the 2020 Summer Olympics.
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Daniel Okafor
Daniel Okafor is the Senior AI Reporter at TrendinTech, where he covers large language models, machine learning research and the practical use of artificial intelligence across business and government. He previously reported on artificial intelligence for MIT Technology Review, covering the labs behind the current generation of frontier models and the policy debates in Washington and Brussels. Daniel holds a Master of Science in Machine Learning from Carnegie Mellon University and follows the research community closely, attending NeurIPS and ICML each year to speak with the people behind the papers. He has a particular interest in evaluation: how models are benchmarked, where those benchmarks fail and what that means for the companies betting on them.
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