Ok, so it's not quite that popular, but it is being heralded as one of the biggest advances in linear modelling in a few decades - and that's saying a lot for a field that has been relatively unchanged for almost two centuries. Essentially, it's a new take on model selection, or determining which independent variables should be included when modeling a response variable.
Oh, and the lasso is a form of restricted regression model which is quite compatible with the LARS algorithm.
I'm going to stop writing now.
*The 2004 article published in the Annals of Statistics is here, but it has blurry grayscale images. My link is to a 2003 version, but hey - it's in color!