Today Intel demonstrated its Intel Nervana Neural Network Processors (NNP) for training (NNP-T1000) and inference (NNP-I1000) — Intel’s first purpose-built ASICs for complex deep learning with incredible scale and efficiency for cloud and data center customers.
Intel also revealed its next-generation Intel Movidius Myriad Vision Processing Unit (VPU) for edge media, computer vision and inference applications.
These products further strengthen Intel’s portfolio of AI solutions, which Intel expected to generate more than $3.5 billion in revenue in 2019 alone.
Now in production and being delivered to customers, the new Intel Nervana NNPs are part of a systems-level AI approach offering a full software stack developed with open components and deep learning framework integration for maximum use.
The Intel Nervana NNP-T strikes the right balance between computing, communication and memory, allowing near-linear, energy-efficient scaling from small clusters up to the largest pod supercomputers. The Intel Nervana NNP-I is power- and budget-efficient and ideal for running intense, multimodal inference at real-world scale using flexible form factors. Both products were developed for the AI processing needs of leading-edge AI customers like Baidu and Facebook.
Additionally, Intel’s next-generation Intel Movidius VPU, scheduled to be available in the first half of 2020, incorporates unique, highly efficient architectural advances that are expected to deliver leading performance — more than 10 times the inference performance as the previous generation — with up to six times the power efficiency of competitor processors. Intel also announced its new Intel DevCloud for the Edge, which along with the Intel Distribution of OpenVINO toolkit, addresses a key pain point for developers — allowing them to try, prototype and test AI solutions on a broad range of Intel processors before they buy hardware.
The M.2 AI could find use in game development by making the gameplay more intelligent.