As the demand for deep learning continues to increase across the enterprise and academic spaces, Nvidia continues to tout its superior position in the market.
The company definitely didn't do so lightly either, with four big releases all aimed directly at deep learning systems.
Read next: Nvidia supercharges deep learning at GTC 2018
Firstly, Nvidia made a shift from its traditional GPU architecture by including embedded deep learning capabilities in the workstation, giving designers and data scientists the ability to design products faster.
Specific product launches included the Quadro GV100 and Quadro vDWS graphics cards, which include high performance for deep learning training. It also released an update to what it calls the world's leading deep learning computing platform, Tesla V100 alongside the first single-server two petaflops deep learning system, DGX-2.
In the world of data centres, Nvidia expanded its deep learning inference offerings with new TensorRT 4 software to support neural networks in hyperscale data centres whilst also delivering integration of TensorRT to Google’s TensorFlow framework.