SKOLKOVO INNOVATION CENTER, MOSCOW, RUSSIA
APRIL 16, 2019
SKOLKOVO INNOVATION CENTER, MOSCOW, RUSSIA | APRIL 16, 2019

Licensable Artificial Intelligence (AI) Processors for Autonomous Computing: Balancing Performance and Flexibility

Mark Skanavi
14:00 14:30

Licensable Artificial Intelligence (AI) Processors for Autonomous Computing: Balancing Performance and Flexibility

Autonomous products like robots, cars and drones need multiple processors embedded with varying performance and power consumption levels, including:

1) tiny microcontrollers for sensors and actuators;

2) mid-range processor cores to control robotic vision algorithms with associated AI processors to perform neural network computation;

3) A supervisory processor cluster running an operating system like Linux that can combine all the AI results and other control data for the the navigation and control of the product in its environment.

Wave Computing is laser-focused on accelerating AI from the datacenter to the edge for more than 10 years. The company’s MIPS processor technology is backed by 30+ years of experience in designing CPU cores for an array of edge applications - from precision farming systems and automobiles, to wireless modems, networking and Internet of Things devices. In fact, Wave Computing’s MIPS processor technology is currently enabling over 80 percent of vehicles equipped with Advanced Driver Assistance Systems (ADAS) from today’s leading automotive manufacturers.

While most AI solutions today are datacenter-centric and used for both training and inferencing, there a significant need for more specialized AI hardware solutions that are more powerful and efficient to meet the sophisticated training models at use in the ‘next-generation’ of embedded edge applications.

Gartner’s 2019 CIO Survey indicated 14% of organizations currently employ AI in nearly all data-rich aspects of their operations, and nearly 50% intend to do so in 2020. However, market research also indicates many companies cite lacking a clear AI strategy as the #1 barrier to the successful adoption of AI within their organization. In this session you’ll learn how to architect an AI strategy that makes sense for your organization and how to support that with an end-to-end, scalable, efficient AI platform capable of supporting your AI-application needs of today and tomorrow.

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Mark Skanavi
14:30 15:00

Speaker

Senior Staff IC Design & Verification Engineer,
Wave Computing