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Prithviraj Banerjee on data sharing

From S2, EP6 - Dr. Prith Banerjee - ANSYS CTO · · DrNeilAshton

“To build foundational models I will have to get all the CAD files from Airbus and Boeing and other OEMs — will they be willing to give it to us? This is why you need a business model and governance: customers could opt in to give anonymized data to ANSYS so we can train a richer model on the cloud.”

Prithviraj Banerjee
Chief Technology Officer, ANSYS Inc
Controversial Policy Impact data sharinggovernancecloudfoundational models

On , Prithviraj Banerjee, Chief Technology Officer at ANSYS Inc, spoke about data sharing during S2, EP6 - Dr. Prith Banerjee - ANSYS CTO on DrNeilAshton.

S2, EP6 - Dr. Prith Banerjee - ANSYS CTO
Watch on YouTube at 39:55
S2, EP6 - Dr. Prith Banerjee - ANSYS CTO
DrNeilAshton
Watch on YouTube at 39:55
In this episode of the Neil Ashton Podcast, Dr. Prith Banerjee, CTO of Ansys, shares his extensive journey from academia to the corporate world, discussing the interplay between academia and industry, the role of startups in innovation, and the transformative potential of AI and ML in simulation. He emphasizes the importance of solving real-world problems and the need for collaboration between academia, startups, and large corporations to foster disruptive innovation. He discusses innovative business models for data sharing, the intersection of data-driven and physics-informed approaches, the role of open source in AI innovation, the potential of foundational models in computer-aided engineering (CAE), the future of quantum computing in simulation, and offers advice for aspiring innovators and entrepreneurs. He emphasizes the importance of collaboration, data governance, and the need for interdisciplinary approaches to solve complex problems in engineering and technology. Dr. Banerjee's book - The Innovation factory: https://www.amazon.com/Innovation-Fac... Chapters 00:00 Introduction to the Podcast and Guest 05:18 Dr. Prith Banerjee's Journey: From Academia to CTO 09:10 The Role of Academia, Startups, and Industry 17:22 Advice for Startups: Motivation and Market Sizing 24:04 The Impact of AI and ML on Simulation 35:07 Future of AI in Physics and Simulation 36:10 The Power of Data in AI Models 40:33 Incentivizing Data Sharing for Better Models 42:55 Physics-Driven vs Data-Driven Approaches 47:30 The Role of Open Source in AI Innovation 52:06 Foundational Models and Simulation Data 58:22 The Future of CAE and Quantum Computing 01:06:29 Advice for Aspiring Innovators Audio-only Apple podcast version: https://podcasts.apple.com/gb/podcast... Spotify version: https://open.spotify.com/episode/4AiA... Keywords Neil Ashton, Prith Banerjee, CAE, AI, ML, simulation, academia, startups, industry, innovation, AI, data sharing, physics-driven, open source, foundational models, quantum computing, CAE, simulation, innovation, engineering
Prithviraj Banerjee

About Prithviraj Banerjee

Chief Technology Officer · ANSYS Inc

Prithviraj Banerjee, Chief Technology Officer at Ansys, discussed the company's approach to simulation and artificial intelligence in a December 2024 podcast. He described Ansys as a leading modeling and simulation company that uses physics-based methods such as finite element and finite volume techniques. Banerjee stated that his role involves examining the future of simulation and technologies like AI, machine learning, and high-performance computing to drive future products. He noted that a key challenge is balancing accuracy and speed in simulation tools. Banerjee outlined Ansys's development of a platform called SimAI, which allows customers to train AI models on their own design problems, reducing simulation time for later designs. He also described a longer-term vision for foundational AI models for physics, analogous to large language models, that would be trained by Ansys on a broad set of physical data. Banerjee acknowledged that building such models would require access to customer data and discussed potential business models involving anonymized data sharing with compensation. He also mentioned that quantum computing could accelerate simulation within a decadeasi.

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