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Vijay
Sanikal
Product Owner, Vehicle Simulation Integration
General Motors
Vijay Sanikal is a Product Owner at General Motors, with 15+ years of experience spanning automotive digital product development, CAE, cloud computing, synthetic data, AI, and thermal systems. His work sits at the intersection of Battery Electric Vehicles (BEVs) and Software-Defined Vehicles (SDVs), where he leads initiatives that reduce time-to-market, improve energy efficiency, and optimize vehicle performance using Software-in-the-Loop (SIL) models and AI-driven predictive analytics. Vijay holds a Master’s in Automobile Engineering from Anna University (MIT Campus) and an MBA in Marketing from Indiana University Kelley School of Business, giving him a rare blend of deep technical expertise and commercial perspective. His current focus is applying synthetic data and machine learning to BEV thermal systems—bridging research and real-world deployment while supporting global sustainability goals.
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15 April 2026 16:30 - 17:00
Panel | What breaks when GenAI scales: Latency, cost, and reliability in the real world
As GenAI adoption grows, the underlying infrastructure is under constant strain. Latency spikes, unpredictable traffic, rising inference costs, and brittle retrieval layers often emerge long after a system looks stable in testing. This session explores how engineering teams are redesigning serving layers, data pipelines, and performance workflows to keep GenAI systems fast, affordable, and reliable at scale. Key takeaways: → How teams reduce latency under real-world load → The cost impact of routing, batching, and caching decisions → Where retrieval layers and vector search introduce scaling limits → Architectural choices that improve reliability as usage grows