My high-level view is that Hadoop was very excellent for its intended use case, and that because of this, people have abused it to do things quite unlike what it was designed for. It's amazing that a glorified logs processing framework could do anything like machine learning well. Mahout embodies that interesting struggle.
I can only believe that most any of the "next gen" frameworks discussed here, which are necessarily more general-purpose, will be better for things like machine learning. I am not so interesting in MR 2.0 -- nothing wrong with it just not something better conceptually for machine learning. I like projects like Ciel from MS Research -- simply more general purpose graph- and data-flow-oriented frameworks. I personally believe that while Mahout *could* be anything, that it's reached about the level of scope it can possibly sustain given the amount of effort coming in, in trying to do something interesting on top of MapReduce. This will be useful for a couple years to come yet. That is to say: I think it will be interesting to explore another machine-learning-at-scale project in 2 years or so on top of one of these next-gen frameworks. (Was that the question?)
