Replica theory shows deep neural networks think alike
By David Nutt, Cornell Chronicle
March 12, 2024
How do you know you are looking at a dog? What are the odds you are right?
If you’re a machine-learning algorithm, you sift through thousands of images – and millions of probabilities – to arrive at the “true” answer, but different algorithms take different routes to get there.
A collaboration between researchers from Cornell and the University of Pennsylvania has found a way to cut through that mind-boggling amount of data and show that most successful deep neural networks follow a similar trajectory in the same “low-dimensional” space.
Read more here.