If I understand the Prediction API correctly it's a text classifier. I would imagine it's a bayesian classifier, like the kind found in most spam filters. I don't know how accurate it is...it would be nice to see how it performs on a standard corpus (like the 20newsgroups).

If you're handy with linux and you don't want to deal with their API, you could probably just download and install rainbow http://www.cs.umass.edu/~mccallum/bow/rainbow/ (though it is a very difficult installation).

It can be used as a text classifier. It takes as input a collection of (output, input1, input2, ..., input_n) tuples, stored in the newly-announced Google Storage, and then uses a variety of machine learning algorithms (which I would bet includes some Bayesian stuff) to build a model which it can use to take (input1, input2, ..., input_n) tuples and predict the corresponding output.

So, that's the API. You can do a lot of the same things offline, with almost the same file format, using Weka:

http://en.wikipedia.org/wiki/Weka_(machine_learning)

So if you're interested in playing around with Google's Prediction API, you should probably download Weka and fiddle with it some. It's pretty easy to get started with, and it will definitely give you an idea for the sort of thing you can do here.

Another interesting project is crm114: http://crm114.sourceforge.net/

It's ridiculously easy to use. I used it for identification of spam/scam messages and setting it up was just 5 lines of code.

I wrote a blog post about using it here: http://smokinn.com/blog/post/253

I built a bayesian text classifier on App Engine a few weeks ago but it was too slow to be of any use (the datastore that is). Still fun to get it to work though. Did stumple upon a Bayesian classifier web service: http://www.uclassify.com/Default.aspx

Will certainly check out Weka, it's installed on the pc's at my college so when I get the chance I will.

The prediction API looks really interesting.

Can anyone think of some interesting use cases and the implications of making something like this available to the masses?

The Prediction API has the potential to be really cool.

Wonder how concerned the Directed Edge (YC) guys are about Google entering their space.

Directed Edge is a lot higher-level than this, and more focused on making it easy for their users to make good recommendation engines. Prediction API is focused on more general tasks, and for that reason I predict that it'll have trouble competing with Directed Edge. Unless some startup comes along and competes with Directed Edge using Prediction API as a back-end -- but we can talk about that later, if it ever happens.

Prediction API is a nice broad tool, but Directed Edge still has a big advantage in their niche.

Not too concerned at this stage. We'll see how well the Prediction API will actually work in the wild for product and content recommendations. Beyond that, I'm not sure whether Google will excel in ease-of-use and support.

Too bad the data has to be on the Google Storage Service. It will be some time before people like me will get their hands on an API key for that.

I would love to play with this [for a side project], any ideas on what the timelines are for access for small fish like me?

Download Weka. The file format is almost identical, and it has a nice GUI to get you started fast. Google's algorithms and infrastructure may be more sophisticated and scalable, but if you want something a lot like this for a side-project, Weka is easy to start with and it's available right now.

http://www.cs.waikato.ac.nz/ml/weka/