What if you could train massive machine learning models in half the time without compromising performance? For researchers and developers tackling the ever-growing complexity of AI, this isn’t just a ...

Hardware fragmentation remains a persistent bottleneck for deep learning engineers seeking consistent performance.

Deep learning and artificial intelligence have been huge topics of interest in 2016, but so far most of the excitement has focused on either Nvidia GPUs or custom silicon hardware like Google's ...

SE: There seems to be a parallel growth between the adoption of machine learning and GPUs. Is the need for machine learning driving GPU adoption, or are GPUs creating the opportunity to embrace ...

NVIDIA announced that Facebook will power its next-generation computing system with the NVIDIA® Tesla® Accelerated Computing Platform, enabling it to drive a broad range of machine learning ...