jhomedall

I have a VR headset and still prefer head tracking. It's more comfortable, and becomes second nature after an hour or two of use.

There is no way to determine that a non-trivial neural network won't drastically diverge in output due to small changes in input (eg one pixel attacks on image classifiers). This is true for all current models I know of.

Almost all neural network implementations have continuous outputs (ie the nodes in the output layer produce a value between 0 and 1). That doesn't change the above issue at all.

This is much less of an issue with traditional methods

That's useless in this case. You need to be able to prove that it will work with all inputs, and there are too many combinations of inputs to exhaustively enumerate.

Not quite. Lifetime annotations prevent you from accidentally using references after the value they refer to has been freed. They track how long things will live, instead of defining how long they will live.

Basically they turn use-after-free errors into compile errors.

(I'm using 'free' here to mean cleaned up in general. Lifetimes can track stack values.)

Why would static types require you to create additional classes?

Willing to die and willing to endure torture are different things. Everybody breaks given enough pain.

Oh you're right. My bad, sorry.

The top (selected) path is 23 hexes from start to finish, but the winding closer path is 24 hexes.

There is no line. If Google decides to ban you, your only recourse is to post online and hope your story gets enough traction for it to become a PR issue for them.

I've worked on several teams that required PRs before merging, and there was never any toxic behavior. Everybody was happy with it.

Nobody in this thread insulted you.

Encrypting web traffic is a necessary step in making dragnet surveillance impossible.

Certificates from Let's Encrypt are free.

Wow, I had no idea. Thanks for the heads up.