During our last trip Los Angeles, conference participants experienced a thrilling machine-learning, real-time demonstration as part of the SIGGRAPH 2017 Real-Time Live! showcase: Physics Forests. This data-driven fluid simulation, with surface generation, foam, coupling with rigid bodies, and rendering, is capable of simulating several million particles in real time. It uses the regression forest to estimate the behavior of particles and rendered surfaces. The method can handle a wide range of fluid parameters. Since then, Physics Forests has only grown and built on the capabilities it boasted in 2017.

Summary: Researchers from UC Berkeley have developed a new technique that uses deep networks and AI to colorize images. UC Berkeley computer scientists develop smarter, enhanced data-driven colorization system for graphic artists. For decades, image colorization has enjoyed an enduring interest from the public. Though not without its share of detractors, there is something powerful about this simple act of adding color to black and white imagery, whether it be a way of bridging memories between the generations, or expressing artistic creativity. However, the process of manually adding color can be very time consuming and require expertise, with typical professional processes taking hours or days per image to perfect.

If you're a content creator, you're not just striving to do your best work. You want to make your best work better. At the SIGGRAPH conference, which runs July 31-Aug. From Siri to Smart Cars to Netflix recommendations, AI is infused in our daily lives. Now, thanks to the computational power of NVIDIA GPUs, new AI accelerated workflows are optimizing content creation, saving artists and studios time and money, and driving greater creativity.