The field of AI is evolving rapidly. So rapidly, in fact, that the state of the art will likely advance between the start of your development lifecycle and when you're ready to go to market. This is not only true of machine learning models, algorithms, and development tools, but AI acceleration hardware as well.
Attend this hands-on tutorial as James Hui, Senior Solutions Architect at Wind River, demonstrates how you can get a head start on your AI and machine learning-based solution builds by leveraging a hardware-software co-design strategy based on the company's Simics Virtual Platform and Simulation Software.
Agenda
Step-by-Step Overview of Embedded Machine Learning on Simics
With two decades of experience securing industrial facilities, a license as a Scrum Master, and an educational background in both engineering and philosophy, James Hui has a proven track record of assisting industry-leading customers in their...
Brandon is a tech journalist and electronics marketer with more than a decade of experience covering the embedded sector. In his current role as Editor-in-Chief of Embedded Computing Design, he guides the publication's content strategy, editorial...