In condensed matter physics, there is an area called turbulence that has wide practical application: weather, golfing, navigation, bridges, building subs, boats, and planes.
(Most of you know turbulence from those random unexplained dips you get when your plane is in flight.)
But for theoreticians, turbulence is different.
In 1941, some Russian guy wrote a theory for the dissipation of vortices in highly turbulent flows:
Since then…nothing. Any significant contribution to turbulence has been beyond smartest minds in theoretical physics, despite the describing equations discovered by 19th century classical physics.
In physics, we like to say:
Turbulence is the graveyard of great physicists.
Artificial Intelligence
The topic of machine learning came up before dinner as it relates to online-analytical processing (OLAP). I find it absurd, that in an area where most people can’t even code a proper data warehouse, working in the business world where practical realities are paramount, people talk about doing machine learning. You need a great OLAP before you can even talk about machine learning.
Machine learning is a branch of Artificial Intelligence (AI). And since I recently stated my opinions of AI, Andrei steered the topic that direction—to wait for the horse hair to snap.
He didn’t have to wait long.
This incident occurs shortly after this talk.
Mager asked, “What is this?”
This is a slide representing theoretical curves for Black Body Radiation. The deviation from the classical theory created the field of quantum mechanics and its theory became the source of Einstein’s only Nobel Prize. But is best popularized by this xkcd comic.
Note that in the comic, the points are the measured energy density of the cosmic microwave background radiation of the universe; the line is the theoretical curve for black body radiation. This represents an experimental confirmation of Big Bang Theory (the theory, not the TV show).
So in this one slide, you can see the stars, the subatomic, and everything in between. Is it a wonder…?
“Look, you’re talking about a field that has been around for sixty years now that has yet to make something of significance—Clippy is like their claim to fame. Search? Nope, map-reduce crushed it. Fingerprint recognition and spam detection? Nope, statistical probability-based recognizers like Bayesian ones are how those are done. Chess? No, a brute force Alpha-beta pruning game theory approach crushes those all the time.”
“…but chess isn’t an interesting problem,” Some Guy interrupts.
(I’ll mention at this point that Some Guy is apparently writing a book on Artificial Intelligence. In my defense, he didn’t have the balls to admit this at the time…or at all to me for that matter.)
“Isn’t it funny how that as soon as AI gets their asses handed to them, the problem suddenly becomes uninteresting? You’re talking about a branch that attracts the brightest minds in computer science. At a certain point, you should just get a little humility, admit failure, and move on.”
“So what you’re saying is you’re afraid of failure?” A triumphant smirk creeps across Some Guy’s face. I can read his thoughts. I think, Your heros are the ones who washed out of my major.
Instead, I say, “So what you’re saying is you’re afraid of making a contribution to the world?”
And the horse hair goes… Snap!
