AI Capable Of Showing How The Universe Works


A team of researchers recently pioneered the world’s first AI universe simulator. It’s fast; it’s accurate; and its creators are baffled by its ability to understand things about the cosmos that it shouldn’t.

Scientists have used computer simulations to try and digitally reverse-engineer the origin and evolution of our universe for decades. The best traditional methods using modern technology take minutes and produce okay results. The world’s first AI universe simulator on the other hand, produces results with far greater accuracy in just milliseconds.

The speed and accuracy of a project at the Flatiron Institute, called the Deep Density Displacement Model, or D3M for short, wasn’t the biggest surprise to astrophysicists who used artificial intelligence techniques to generate complex 3-D simulations of the universe in an amazing 30 milliseconds, including how much of the cosmos is dark matter.

The real shock was that D3M could accurately simulate how the universe would look if certain parameters were tweaked even though the model had never received any training data where those parameters varied. The results are so fast, accurate and robust that even the creators aren’t sure how it all works.

It’s like teaching image recognition software with lots of pictures of cats and dogs, but then it’s able to recognize elephants. Nobody knows how it does this, and it’s a great mystery to be solved”.

Our universe is a strange and mostly unknown place. Humanity is just beginning to set our sights beyond observable space to determine what’s out there and how it all ended up the way it is. Computer simulations like those made by D3M have become essential to theoretical astrophysics.

Scientists want to know how the cosmos might evolve under various scenarios, such as if the dark energy pulling the universe apart varied over time. Such studies require running thousands of simulations, making a lightning-fast and highly accurate computer model one of the major objectives of modern astrophysics.


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