Linear Digressions

In our follow-up episode to last week's introduction to the first self-driving car, we will be doing a technical deep dive this week and talking about the most important systems for getting a car to d...

10 Apr 201740min

In October 2005, 23 cars lined up in the desert for a 140 mile race.  Not one of those cars had a driver.  This was the DARPA grand challenge to see if anyone could build an autonomous vehicle capable...

3 Apr 201713min

Figuring out what features actually matter in a model is harder to figure out than you might first guess.  When a human makes a decision, you can just ask them--why did you do that?  But with machine ...

27 Mar 201720min

It's hard to get information to and from Mars.  Mars is very far away, and expensive to get to, and the bandwidth for passing messages with Earth is not huge.  The messages you do pass have to travers...

20 Mar 201723min

You may be shocked to hear this, but sometimes, people on the internet can be mean.  For some of us this is just a minor annoyance, but if you're a maintainer or contributor of a large project like Wi...

13 Mar 201715min

Advances in neural networks are moving fast enough that, even though it seems like we talk about them all the time around here, it also always seems like we're barely keeping up.  So this week we have...

6 Mar 201716min

When you're estimating something about some object that's a member of a larger group of similar objects (say, the batting average of a baseball player, who belongs to a baseball team), how should you ...

27 Feb 201727min

Say you're looking to use some Bayesian methods to estimate parameters of a system. You've got the normalization figured out, and the likelihood, but the prior... what should you use for a prior? Em...

20 Feb 201718min