I have been thinking a lot about how to move R&D from a deterministic description of design parameters to a stochastic one.  R&D is essentially tasks undertaken to manage uncertainty around the product’s ability to perform its intended mission.  Uncertainties arise from the underlying variation in design parameters (such as manufacturing variations, material properties or environment where the product will be used).  Traditionally, designers combine all uncertainties and account for them through margins of safety.  These margins actually prevent reuse of R&D into new designs that involve different materials or slightly different objectives.  An logical way around this problem is to deal with the uncertainties directly.  These stochastic methods are very computationally intensive.  I saw this article from NY Times on Lyric Semiconductor Develops a Probability Chip:

Lyric Semiconductor, a start-up that emerged from work at the Massachusetts Institute of Technology, looks to forgo this certainty in favor of probability. It unveiled plans this week to build a chip that can compute likelihoods. Such technology may help figure out which book someone will want to buy on Amazon.com or help create a better gene-sequencing machine.

I am wondering how the chip could be used for more complex stochastic computations.  Any thoughts?