Intel AI Summit: New 'Keem Bay' Edge VPU, AI Product Roadmap

At its AI Summit today in San Francisco, Intel touted a raft of AI training and inference hardware for deployments ranging from cloud to edge and designed to support organizations at various points of their AI journeys. The company revealed its Movidius Myriad Vision Processing Unit (VPU), codenamed "Keem Bay," for edge media, computer vision and inference applications. The company said the VPU, available the first half of 2020, incorporates "highly efficient architectural advances" and will deliver more than 10 times the inference performance of current Movidius VPUs and up to six times the power efficiency of competitor processors. Intel claimed that "early performance testing indicates that Keem Bay will offer more than 4x the inference throughput of Nvidia's similar-range TX2 SOC at one third less power, and nearly equivalent throughput of Nvidia's next higher class SOC, Nvidia Xavier, at one fifth the power. Keem Bay will also be supported by Intel's OpenVINO Toolkit for development of computer vision applications – "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," according to Intel. It also will be incorporated into Intel's newly announced Dev Cloud for the Edge, launched today, designed to allow developers to test algorithms on any Intel hardware. Intel also offered the first live demonstrations and additional architectural details of its Nervana Neural Network Processors for training (NNP-T1000) and inference (NNP-I1000) ASICS for cloud and data center environments, first announced last August at the Hot Chips conference. In discussing the company's AI products roadmap (see above), Naveen Rao, corporate VP/GM of Intel's AI Products Group, said the combination of "the new Intel hardware will enable the industry to embrace much larger and more complex AI algorithms, expanding what can be achieved with AI in the cloud and data center, an edge server, or an IoT device." "With this next phase of AI, we're reaching a breaking point in terms of computational hardware and memory," said Rao. "Purpose-built hardware like Intel Nervana NNPs and Movidius Myriad VPUs are necessary to continue the incredible progress in AI.