Beyond the simulations and optimizations of, e.g., stock market prices in the world of finance, the principles of stochastic optimization are widely used in Deep Learning and AI related fields of today. But speaking for the latter, their efficiency is ‘dubious’ at best.
Solving stochastic optimization in combination with physics equations for the engineering sectors is several orders of magnitude more challenging and computationally extremely demanding. Our research at Rafinex has reduced the computational time of stochastic topology optimization (STO) down from many weeks to just a few hours.
Reach out & put us to the challenge!
[read more on LinkedIn]