  The Eureqa symbolic regression program has recently received extensive press
praise. A representative quote is
  "There are very clever 'thinking machines' in existence today, such as
Watson, the IBM computer that conquered Jeopardy! last year. But next to
Eureqa, Watson is merely a glorified search engine."
  The program was designed to work with noisy experimental data. However, if
the data is generated from an expression for which there exists more concise
equivalent expressions, sometimes some of the Eureqa results are one or more of
those more concise equivalents. If not, perhaps one or more of the returned
Eureqa results might be a sufficiently accurate approximation that is more
concise than the given expression. Moreover, when there is no known closed form
expression, the data points can be generated by numerical methods, enabling
Eureqa to find expressions that concisely fit those data points with sufficient
accuracy. In contrast to typical regression software, the user does not have to
explicitly or implicitly provide a specific expression or class of expressions
containiing unknown constants for the software to determine.
  Is Eureqa useful enough in these regards to provide an additional tool for
experimental mathematics, computer algebra users and numerical analysis? Yes if
used carefully. Can computer algebra and numerical methods help Eureqa?
Definitely.
