I wear a bow tie now. Bow ties are cool.

That's the old paradigm, of programs that do what they are programmed to do. The new way is YOLO and hope for the best.

We keep executing them before they've even done anything wrong!

Think of the atoms as primordial croutons.

As opposed to the evenings being dark and unpleasant? Perhaps it's a morning person thing.

"I am unable to Kelno'reem as I once did, since I began using Tretonin."

No, they have to stay one step ahead. It'll be x64.

Just curious...

Training adjusts the weights. It doesn't adjust the network structure, except to the extent that some weights go to zero.

Great Scott!

A while back someone figured out that neural nets needed history, and RNNs (recursive neural networks) were born. The current "time" in the network referenced previous "times." The problem was, RNNs kind of sucked.

The attention mechanism is a fancier version of the same idea. Instead of referring to a few previous times, you refer to ALL previous times with context-dependent weights.

Transformers were the end state of replacing recursive nets with attention in a much of different places.

You need to understand that neural networks have structure. A network to recognize images is fundamentally different from a network to recognize voice. There are "LEGO blocks" of structure they use to architect these things. Transformers, long short-term memory (LSTM), etc.

The real advances come from identifying new LEGO blocks to use.

A big company will hire a CEO named Dat Ash. I look forward to the headlines.

If you ask Google Maps for a route, it will find one pretty efficiently. But if the mountain pass that is the fastest way is closed, and the next fastest way is 3 hours longer, it's going to do a LOT of searching across the graph before it finds that. These hacks are no different. The agent can't do the obvious thing so it starts trying everything to find a way through. It's still just state space search in the end.

Everyone has figured out by now how to manipulate Trump via flattery.