3D Pizza Printing Has Arrived Thanks to NASA
Who doesn’t like enjoying a slice of pizza or two and settling down to watch some good entertainment? Well, now thanks to NASA, even astronauts are now able to join in on this favorite pastime as the first 3D printed pizzas come to fruition.
Who doesn’t like enjoying a slice of pizza or two and settling down to watch some good entertainment? Well, now thanks to NASA, even astronauts are now able to join in on this favorite pastime as the first 3D printed pizzas come to fruition.
NASA have teamed up with Austin, Texas-based company, BeeHex, to try and recreate more delicious foods that can be taken on space missions. With astronauts being away for up to a year at a time, it is important they can have some variation in their diet and with this 3D food printer from BeeHex, that may soon be possible.Using this amazing printer, astronauts can create their own variation of pizza and literally print it out to eat in a matter of minutes. The printer works the same as any other 3D printer and prints the pizza layer by layer. And according to those have dared to test it, it tastes good. So, this could bring a new meaning for astronauts and the world of fine dining. Doctors may even be able to tailor the individual’s food to include vitamins and supplements that they need.
Although originally designed to be used for NASA’s manned mission to Mars in the 2030’s, there is nothing to say that it won’t be used here first, and rumors have it that we may even see this incredible machine available for us mere earthlings to use as early as 2017.
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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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