From the scientific point of view, the cosmos is a machine that is constantly in learning
In fascinating new research, cosmologists explain the history of the universe as one of self-teaching, autodidactic algorithms.
The scientists, including physicists from Brown University and the Flatiron Institute, say the universe has probed all the possible physical laws before landing on the ones we observe around us today. Could this wild idea help inform scientific research to come?
In their novella-length paper, published to the pre-print server arXiV, the researchers—who received “computational, logistical, and other general support” from Microsoft—offer ideas “at the intersection of theoretical physics, computer science, and philosophy of science with a discussion from all three perspectives,” they write, teasing the bigness and multidisciplinary nature of the research.
Here’s how it works: Our universe observes a whole bunch of laws of physics, but the researchers say other possible laws of physics seem equally likely, given the way mathematics works in the universe. So if a group of candidate laws were equally likely, then how did we end up with the laws we really have?
“The notion of ‘learning’ as we use it is more than moment-to-moment, brute adaptation. It is a cumulative process that can be thought of as theorizing, modeling, and predicting. For instance, the DNA/RNA/protein system on Earth must have arisen from an adaptive process, and yet it foresees a space of organisms much larger than could be called upon in any given moment of adaptation.”
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