Bringing Back Moore's Law

What Is SimianQuant?

SimianQuant is a library for quantitative development that uses artificial intelligence to turbocharge the capabilities of development teams. Using the library, programmers can write code that:

  1. Runs upto 100x faster
  2. Requires upto 10x fewer lines of code
  3. Does not require maintenance

The library is designed for problems in the fields of Quantitative Finance, Trading, Robotics and Computational Biology.

Automating Implementation

The library provides mechanisms to separate the mathematics of a model from its implementation, and then automating the implementation. It saves programmers from the tedious task of writing good, clean and fast code.

SimianQuant is the software analogue of an engineer 3D printing a component from a computer model instead of drawing it by hand and having it machined by a skilled technician.

Write Once, Use Everywhere

Modern models need to be evaluated in multiple contexts, either for different end goals like sensitivity analysis (using algorithmic differentiation) and bulk processing (like Value at Risk), or to integrate with different external systems. Since the underlying mathematics is the same, the SimianQuant library can be used to generate an implementation that is separately and specifically optimized for each context.

This not only allows users to use the strengths of each platform rather than work around their weaknesses (yielding a significant performance improvement), but also frees programmers from the intricacies of writing, integrating and maintaining generic and parallelized code.

Ideal Users

Using the SimianQuant library is equivalent to telling a team of expert programmers and mathematicians what you want to do, and letting them figure out how to do it. Therefore, the ideal users of the library are subject matter experts who would prefer to spend their time capturing the nuances of their domain rather than dealing with the complexities of writing and integrating code.

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