1. Generate simple data sets revealing Human Level AI type problems.
The test set would be similar in spirit to Caltech 101 - a test set
for computer vision - but for Human Level AI. The test set should be as
simple as possible and is to be posted on the web as a benchmark.
2. How to evaluate generalizability of human level AI algorithms.
We will discuss criteria to estimate degrees of freedom in algorithms.
The end goal is to be able estimate a ratio of scenarios applicable vs.
degrees of freedom for algorithms proposed toward Human Level AI. Such
metrics are intended to facilitate comparisons across AI methods.