Join us in this insightful podcast-style interview with Kausthub Krishnamurthy, a Senior Manager and Machine Learning Engineer at Nearmap, as we explore the fascinating world of robotic vision within deep learning. Kausthub shares his journey from modular cube flow pipelines to developing data pipelines and training models for computer vision at Nearmap, highlighting the multidisciplinary nature of robotics that intertwines machine learning, computer vision, software engineering, and robotics. Key Highlights: Robotic Vision and Machine Learning: Delve into the complexities of robotic vision, comparing classical computer vision techniques with deep learning methods, and discussing their applications in automation, field robotics, and cloud machine learning. Design Considerations: Understand the design considerations for integrating machine learning into robotics, addressing challenges related to real-time data processing, connectivity, hardware-software ecosystem, and the evolving roles within robotic vision and sensing. Simulation-Driven Development: Explore the importance of simulation-driven development in robotics, leveraging tools like ROS and Moose, and the role of agile development approaches in shaping the future of robotics. Career Paths and Continuous Learning: Gain insights into career paths in robotics beyond engineering, the vital role of simulation in robotics training, and tips for continuous learning and career advancement in the field. Project Ideas and Internship Tips: Discover project suggestions and internship tips for aspiring robotics professionals, and considerations regarding data privacy and safety in the context of consumer-direct robotics use. Embark on this enlightening conversation with Kausthub Krishnamurthy as he unravels the intricacies of robotic vision, machine learning, and the future of robotics in the dynamic landscape of technology and innovation.