Ciro Santilli @cirosantilli 37

"Intel Research Lablets", that's a terrible name.

Surprisingly, it can also become a superfluid even though each atom is a fermion! This is because of Cooper pair formation, just like in superconductors, but the transition happens at lower temperatures than superfluid helium-4, which is a boson.

aps.org/publications/apsnews/202110/history.cfm: October 1972: Publication of Discovery of Superfluid Helium-3 contains comments on the seminal paper and a graph which we must steal.

Source: github.com/QBobWatson/ila.

Written in MathBook XML.

They died so completely, Googling "ICL" now has higher hits such as Imperial College London.

CNN convolution kernels are not hardcoded. They are learnt and optimized via backpropagation. You just specify their size! Example in PyTorch you'd do just:as used for example at: activatedgeek/LeNet-5.

This can also be inferred from: stackoverflow.com/questions/55594969/how-to-visualise-filters-in-a-cnn-with-pytorch where we see that the kernels are not perfectly regular as you'd expected from something hand coded.

This LibreTexts book does have some interest!

Two symmetric matrices $A$ and $B$ are defined to be congruent if there exists an $S$ in $GL(n)$ such that:

Like the matrix representation of a bilinear form, it is a matrix, but now the matrix has to be a symmetric matrix.

We can then immediately see that the matrix is symmetric, then so is the form. We have:But because $B(x,y)$ is a scalar, we have:and: