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Maybe 100 years ago mathematicians could hide in ivory towers and treat the subject like a liberal art. But in 2021 engineers are right at the gate.

Engineers want more algebras for their intricate software, more analysis for their haptic feedback systems, more topology and algebraic geometry for their robots and artificial intelligence systems.

If mathematicians do not publish about it, engineers will publish. Where mathematicians refuse to be rigorous, engineers and logicians will invent languages that automate writing proofs.

It is the end of an era. It is like seeing the Catholic religion split into the multitude of other Christian religions.

You are a cyborg.

Take good care of yourself by keeping your software bug free and up to date.

What even IS intelligence?

Knowing optimizations in a space is just mathematical knowledge. You don't have to be intelligent to pretty much utilize everything that would count as intelligence.

So what could it be in 50 years? Possibly ownership of GPU cores and the latest and greatest optimization software.

Have to say I am pretty fond of systems science, particularly software engineering.

Programs are these formal structures. They do not rust or anything like that. But they still age in a way that all complex systems age.

One such consequence of this is that systems with a hardy design can last pretty much forever. There is a lot of "brown field" and a bunch of time is spent rebuilding especially important systems out of stronger logic.

But two areas that software seems to change, even in such bullet proof systems, is security problems and new hardware. Interfacing can mitigate upkeep costs from hardware growth. But security issues tend to cause rewrites. What fixes security upkeep requirements are small edge cases of mathematical purity. But I think most systems can never be so clean.

Curve25519 implementation is both the most blessed and cursed code in the world.

On one hand, it has the cleanest math and attracted the best minds to work on it. Now the code deployed in most projects have been fully optimized, and formally verified to be mathematically correct and secure. One of the biggest accomplishment in crypto applications in recent years.

On the other hand, the monstrous, machine-generated assembly or C code will give any unsuspected programmer a heart attack.

Seriously, "you are not expected to understand this."

git.kernel.org/pub/scm/linux/k

Anybody here interested in mathematical logic?

I really like Wolfram's theory of physics. It is easy to understand. At its core it is a bunch of graph theory with hints of everything else in the universe.

But I am biased because I am also a language designer, and we are both math literate. So I think in a lot of the same ways he does.

wolframphysics.org/

I am having a great time with calculus of computation. It reads like a math logic book, but there is a solid proof system that comes as a companion to it.

theory.stanford.edu/~arbrad/pi

purpl.cs.purdue.edu/

Purdue, and others are also trying out "Software 2.0". The idea is that programmers design a nice solid type system, proof code if you will. Underneath this are many machine learning algorithms to accomplish the difficult task of implementation.

Get it while its hot. Mathematical logic is a common element of compiler and formal language design.

engineering.purdue.edu/~xqiu/e

A machine learning course that is more rigorous than average while still being not purely theoretical. Partake in the story of the world my friends, or whatever Descartes said.

engineering.purdue.edu/ChanGro

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