Nvidia has unveiled the Tesla M40 and the M4 server-based graphics processors, both designed for deep learning training, purpose-built to reduce training time, video transcoding, image processing, and machine learning inference that offloads demanding applications. The new GPUs are designed to add info to online videos such as tags, information about colors, surroundings and even emotions in order to enhance search. They are designed to be parts of hyperscale servers, where videos are stored and then served to computing devices over the Internet. Software models, analytics and algorithms assist the machine-learning GPUs in classifying, tagging and resizing images.

Nvidia says that machine learning to help add information attached to videos could improve the accuracy of search results. Machine-learning processors could also power software models designed to analyze videos and images.

A batch of eight M40 GPUs can be used on high-performance servers where videos and images could pass through algorithms and analytics tools.

The Tesla M40 is based on Nvidia's Maxwell architecture. It offers up to 7 Teraflops of single-precision performance with NVIDIA GPU Boost. The GPU packs 3072 NVIDIA CUDA cores and 12 GB of GDDR5 memory (288 GB/sec memory bandwidth) and draws 250 watts of power.

The smaller M4 is designed for servers based on OpenCompute Project specifications. This one delivers 2.2 teraflops of performance, draws just 50 to 75 watts of power and has 4GB of GDDR5 memory.