The Fifth Elephant - Pune Edition

The landscape of autonomous systems is rapidly evolving, shifting from traditional, modular approaches to integrated, end-to-end AI stacks. These stacks represent a significant leap forward, capable of directly translating raw perception inputs – such as camera images and lidar data – into precise action control outputs without relying on intermediate, hand-engineered modules. This streamlined architecture promises increased efficiency and adaptability, but hinges on the availability of massive, high-quality datasets for effective training.

Our work concentrates on enabling these end-to-end AI stacks through a deep dive into training and development methodologies utilizing synthetic data generated by World Foundation Models (WFMs). We explore how to leverage the vast potential of WFMs to create realistic and diverse large-scale datasets necessary to train and validate these complex AI systems. This approach addresses several critical challenges in the autonomy space, paving the way for more robust and capable self-driving technologies.

Key Takeaways:

• Shift to End-to-End AI: The autonomy field is moving towards end-to-end AI stacks that directly link perception to action.
• WFMs Enable Synthetic Data: World Foundation Models are a key enabler for generating realistic and diverse synthetic data for training and validation.

Target Audience:

• AI/ML Engineers (Autonomy Focus): Professionals specializing in artificial intelligence and machine learning, specifically those working on autonomous systems.
• Research Scientists (Robotics/AI): Researchers exploring the latest advancements in robotics, AI, and autonomous systems.
• Technical Leaders (Automotive/Robotics): Individuals in leadership positions responsible for strategic technology decisions within the automotive or robotics industries.

About Speaker:

Abhilash SK is a Technical Architect at the Autonomous Driving practice in KPIT. His responsibilities include leading techincal research for autonomous driving domain with a focus on E2E AI stacks and WFMs. He holds a Masters Degree from Bangalore University and has a wide range of publications and patents on AI and related topics.