MIT Uses Machine Learning Algorithm To Make TCP Twice As Fast

An anonymous reader writes "MIT is claiming they can make the Internet faster if we let computers redesign TCP/IP instead of coding it by hand. They used machine learning to design a version of TCP that's twice the speed and causes half the delay, even with modern bufferbloated networks. They also claim it's more 'fair.' The researchers have put up a lengthy FAQ and source code where they admit they don't know why the system works, only that it goes faster than normal TCP."

Comments

Re:For a second there

[cold fjord]

Colossus: The Forbin Project

Re:All Jokes Aside... Still No.

[jkflying]

It's not that we don't understand *why* something like a genetic-algorithm designed antenna works so well. We can evaluate its performance using Maxwell's equations and say, "Yes, it works well." without ever having to build the thing. What we don't have is a set of guidelines or 'rules of thumb' that can result in an antenna design that works just as well.

The difference is that the computer evaluates a billion antennas for us, doing some sort of high-dimensional genetic optimisation on the various lengths of the antenna components. It doesn't 'understand' why it gets the results it does. We do, because we understand Maxwell's equations and we understand how genetic optimisation works. But Maxwell's equations only work for evaluating a design, not for giving a tweak which will improve it. And we're dealing with too many variables that are unknown to have a closed-form solution.

As for this algorithm, they basically did the same thing. They defined a fitness function and then repeatedly varied the code they were using to find the best sequence of code. However, unlike the antenna analogy, they used actual equipment to evaluate the fitness function, not just a model. This means that they don't have an accurate model, which means that your complaint that we don't know why this works is entirely valid, and the antenna analogy is not =)