> BIG
PICTURE
R Vijayalayan
Manager, Automotive Industry Field Application Engineering Team, MathWorks India Pvt. Ltd.
Engineers Don’t Need
to Become Data Scientists to Achieve Success in AI With the need for efficiency improvement and meeting the shrinking timelines, there’s a big need for virtualization of the electrified vehicle development and testing using simulation emphasizes R Vijayalayan, Manager, Automotive Industry Field Application Engineering Team, MathWorks India Pvt. Ltd. During an extensive e-interaction with Niloy from BISinfotech the veteran pans across on how AI is solving complex engineering projects, the trends shaping the Indian auto sector, their leadership in ModelBased Design and challenges for Indian Auto sector when it comes to innovating high-tier autonomous segment. Much more in the edited excerpts below.
> JULY 2021
Q
How has been MathWorks supporting complex engineering projects especially when it comes to solving AI challenges? Engineers working on AI projects often expect to spend a large percentage of their time developing and fine-tuning AI models. Though modeling is an important step in the workflow, the model is not the end of the journey. MathWorks believes that engineers should consider four steps for a complete AI-driven workflow as it is critical to unearth any issues early on for success in AI implementation. The four-step process consists of Data Preparation, AI Modeling, Simulation and Test and Deployment.
Engineers don’t need to become data scientists to achieve success in AI. MathWorks has designed tools, and apps to help them build and integrate AI into their workflows. The engineers bring in the domain knowledge rather than spending inordinate amounts of time becoming
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