Ryan Dickherber

Ryan Dickherber is a scientist getting a PhD in Physics at Washington University in St. Louis. I am professionally interested in astrophysics, but also in science and technology more generally. I have a BS in Physics and a BS in Mathematics from the University of Missouri-Columbia. I also have experience in software engineering, electrical and computer engineering, web design, and graphic design.

I listen to post-rock, electronic, pop, and other kinds of music, and I scrobble almost all of it to Last.fm, so you can see exactly what I like.

I have a blog on Posterous, and I also tweet. My old blog is Funny Logic, though I am phasing that out because my Posterous blog is easier to maintain.

Some of my writings.

I have written a lot of stuff over the years. Here is some of it:

2010-08-28 Information: What is it, exactly?
The concept of information is all over the place. Some time ago I became interested in it because I discovered the theoretical understanding of information is lacking. In this post, I try to find a way to merely define what information is. The definition I suggested is that information is a probability distribution. The catch is that there are three distinct kinds of probabilities.

2010-08-18 The Structure of Knowledge: How to learn about everything without learning literally everything.
In order to make good decisions in our lives (or careers), we need to have solid, reliable knowledge, and generally the more relevant knowledge we have, the better. In this post I try to figure out how we can acquire more knowledge in some kind of rigorous way. I argue that the best way to do this is a hierarchical method, where we divide the world up into parts, and learn about all the parts in ever increasing detail.

2010-08-17 A car is to a horse what AI is to a human brain.
Some people believe the best way to create a general-purpose AI is to reverse-engineer the human brain. Here I argue this is probably not the most appropriate way to create an AI. Instead, we ought to approach it like the engineers who developed cars: we ought to simply define precisely what it is we want to make, and then use the available resources to make it. That would be far easier, and would probably produce something far more valuable, than trying to reverse-engineer the human brain. (Of course, there are other benefits to reverse-engineering the human brain besides AI.)

2010-08-17 Privacy vs. Openness: The world is becoming more open, like it or not.
The world is becoming more open and less private. Here I argue that this is inevitable, and we probably cannot stop it, like it or not. Thus we should try to adapt our culture to increasing openness rather than trying to stop it.

2010-07-26 Project Asymmetry: Comprehensive training for humans.
Some humans manage to reach their genetic peak in some area, like athletics or intelligence, but almost all of us have room for improvement. In this post I outline a new project devoted to figuring out how we can employ comprehensive training to ensure we train every attribute of ourselves without leaving anything out. For instance, in the world of physics, it's very tempting to train only intelligence at the expence of, say, strength. But intelligence and strength are complementary and it is to our advantage to train both. The project is called Project Asymmetry because the philosophy is that we ought to constantly improve throughout our entire lives, and not reach a peak and start to decline.

2010-04-23 The Effectiveness of Mathematics
Eugene Wigner wrote a famous article where he argued that the usefulness of mathematics in science ought to be regarded as "mysterous" and a "miracle." Here I argue that there is nothing mysterious or miraculous about mathematics. Instead, mathematics is useful for two reasons. First, it is rigorous and well-defined, so that there are no ambiguities. Thus it is a great medium of communication. Secondly, sometimes mathematical models are actually analogs of real systems, in the same sense that a doll house may be an analog of a real house, and thus we can learn something about the real system by studying the model. And there is nothing mysterious about that.

2010-04-23 The Probability of Our Existence
It is very common for people to argue that our existence is somehow improbable, because the initial conditions of the universe must have been fine-tuned or something of that sort. Here I argue that this is actually a misuse of probability (that is, Bayesian probability). Because all of our information tells us that we exist, our existence is actually highly probable, not improbable. However, it is true that our existence is infrequent in the sense that almost all Earth-sized volumes of space do not contain us.