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S2, EP6 - Dr. Prith Banerjee - ANSYS CTO

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Manage episode 455760649 series 3572969
Conteúdo fornecido por Neil Ashton. Todo o conteúdo do podcast, incluindo episódios, gráficos e descrições de podcast, é carregado e fornecido diretamente por Neil Ashton ou por seu parceiro de plataforma de podcast. Se você acredita que alguém está usando seu trabalho protegido por direitos autorais sem sua permissão, siga o processo descrito aqui https://pt.player.fm/legal.

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-Factory-Prith-Banerjee-PH/dp/B0B7LZPDZW
Youtube version of this episode: https://youtu.be/9Ic5xgJt6BQ
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
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

  continue reading

Capítulos

1. Introduction to the Podcast and Guest (00:00:00)

2. Dr. Prith Banerjee's Journey: From Academia to CTO (00:05:18)

3. The Role of Academia, Startups, and Industry (00:09:10)

4. Advice for Startups: Motivation and Market Sizing (00:17:22)

5. The Impact of AI and ML on Simulation (00:24:04)

6. Future of AI in Physics and Simulation (00:35:07)

7. The Power of Data in AI Models (00:36:10)

8. Incentivizing Data Sharing for Better Models (00:40:33)

9. Physics-Driven vs Data-Driven Approaches (00:42:55)

10. The Role of Open Source in AI Innovation (00:47:30)

11. Foundational Models and Simulation Data (00:52:06)

12. The Future of CAE and Quantum Computing (00:58:02)

13. Advice for Aspiring Innovators (01:06:29)

22 episódios

Artwork
iconCompartilhar
 
Manage episode 455760649 series 3572969
Conteúdo fornecido por Neil Ashton. Todo o conteúdo do podcast, incluindo episódios, gráficos e descrições de podcast, é carregado e fornecido diretamente por Neil Ashton ou por seu parceiro de plataforma de podcast. Se você acredita que alguém está usando seu trabalho protegido por direitos autorais sem sua permissão, siga o processo descrito aqui https://pt.player.fm/legal.

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-Factory-Prith-Banerjee-PH/dp/B0B7LZPDZW
Youtube version of this episode: https://youtu.be/9Ic5xgJt6BQ
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
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

  continue reading

Capítulos

1. Introduction to the Podcast and Guest (00:00:00)

2. Dr. Prith Banerjee's Journey: From Academia to CTO (00:05:18)

3. The Role of Academia, Startups, and Industry (00:09:10)

4. Advice for Startups: Motivation and Market Sizing (00:17:22)

5. The Impact of AI and ML on Simulation (00:24:04)

6. Future of AI in Physics and Simulation (00:35:07)

7. The Power of Data in AI Models (00:36:10)

8. Incentivizing Data Sharing for Better Models (00:40:33)

9. Physics-Driven vs Data-Driven Approaches (00:42:55)

10. The Role of Open Source in AI Innovation (00:47:30)

11. Foundational Models and Simulation Data (00:52:06)

12. The Future of CAE and Quantum Computing (00:58:02)

13. Advice for Aspiring Innovators (01:06:29)

22 episódios

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