#405 Inside the World of Industrial AI: Manas Talukdar on Data Pipelines and Predictions

In this episode of The CTO Show with Mehmet, we dive deep into the evolving world of industrial AI with Manas Talukdar, Director of Engineering at LabelBox. Based in the Bay Area, Manas has nearly two decades of experience in enterprise AI, data infrastructure, and distributed systems. Throughout his career, he has played pivotal roles in companies like C3 AI and OSIsoft, where he contributed to developing platforms for mission-critical industrial AI applications. In our conversation, Manas unpacks his journey from electrical engineering to working with leading AI platforms and shares valuable insights into the challenges and opportunities of data infrastructure in AI. Manas explains the anatomy of data pipelines, emphasizing the importance of data storage, ingestion, normalization, and analytics as the building blocks of AI systems. He highlights why high-quality, real-time data is crucial for training AI models, especially in mission-critical applications like predictive maintenance and industrial automation. We discuss the emerging concept of synthetic data and how enterprises can leverage it to fill the gap left by the lack of high-quality training data. Manas also touches on AI’s reliance on data infrastructure and the complexities of using synthetic data to enhance large language models. We explore real-world use cases, such as using drones and AI algorithms to predict rust rates in pipelines, showcasing the transformative impact of AI in the industrial sector. Manas also shares his thoughts on integrating AI into traditional industrial systems, offering a glimpse into the future of AI-enabled operations. He sheds light on the importance of building scalable, resilient AI systems and the role of loose coupling in creating adaptable AI solutions that can withstand rapid technological changes. Towards the end of the episode, Manas shares career advice for aspiring AI professionals, emphasizing the importance of foundational knowledge, continuous learning, and finding mentors in the AI field. He also highlights resources like Andrew Ng’s Coursera courses that provide comprehensive training in machine learning and deep learning. More about Manas: Manas Talukdar is a senior software engineering leader in Data Infrastructure for Enterprise AI. He has significant experience designing and developing products in artificial intelligence and large-scale data infrastructure, used in mission critical sectors across the world. He is a senior member of IEEE, AI 2030 Senior Fellow and Advisory Board member. His experience spans over a decade and a half in leadership and critical roles for leading enterprise software companies in the San Francisco Bay Area. He has made key contributions to the preeminent industrial data historian in the world, specially ubiquitous throughout the process industry. As Director of Platform Engineering at C3 AI, the leading Enterprise AI company, he founded and led an organization of multiple teams developing cutting edge capabilities at the intersection of artificial intelligence and large-scale systems. He is currently Director of Engineering at Labelbox, a startup building a data-centric AI platform, where he runs platform and product engineering organizations. https://manastalukdar.github.io/ https://www.linkedin.com/in/manastalukdar/ 00:00 Introduction and Guest Welcome 01:14 Manas Talukdar's Background 02:57 Choosing a Career in Data Infrastructure and AI 04:56 Understanding Data Infrastructure 06:42 The Importance of High-Quality Data for AI 08:52 Challenges with Current LLMs and Data Quality 13:11 Synthetic Data and Ensuring Quality 15:11 Enterprise AI and Custom LLMs 16:38 Industrial Use Cases of AI 18:08 Real-Life Use Cases of Predictive Maintenance 19:22 Building Scalable Data and AI Infrastructure 25:47 Guidance for AI Startups 30:02 Opportunities in Data Processing and Machine Learning 33:29 Advice for Aspiring AI Professionals 36:18 Connecting with Manas and Final Thoughts