Note that “ray tracing” is not a singular method that ‘always’ delivers full realism. It is a continuum of techniques mixing the physics of light, geometry, and other mathematics going from simple hard shadows to complex techniques like subsurface scattering skin translucency. Of course, the higher the fidelity, the more computationally intense, but also optimizations and AI techniques help reduce the time to image.
We are now reaching a point that commodity computing platforms from laptops to workstations to servers have computing and AI features to deliver the leap in visual fidelity that ray tracing methods deliver. Moving forward you can expect usages surging that utilize ray tracing delivering a leap in visual impact touching everyone more often. For example, there are already diverse types of applications and products benefitting through high-fidelity ray tracing across a range of industry segments. Creators are challenged to create real life in 3D, from alien faces to explosions, using physical-based models to ensure photorealism. Scientists working to solve some of the world’s most difficult problems, want high-fidelity visualization to understand complex phenomena with large data sets. Product engineering and architects want cost-effective 3D design tools. If it’s visual and realism improves the results, ray tracing will be there!
As ray tracing continues to evolve, we are delivering on what customers ask for in driving innovation in our products. For example, the visualization to build the Covid-19 model first created by the University of Chicago in collaboration with others1 used AI-based denoising components built in the Intel® oneAPI Rendering Toolkit to help researchers understand the data sets. And in the world of professional 3D modeling, Maxon’s well-known Cinema 4D product uses the same AI denoise library to achieve film quality VFX fidelity in a fraction of the rendering time.
