
S2 EP11 - Foundational AI Models for Fluids
04/24/25 • 22 min
In this episode of the Neil Ashton podcast, the discussion revolves around foundational models in fluid dynamics, particularly in the context of computational fluid dynamics (CFD). Neil shares insights from a recent panel discussion and explores the potential of AI in predicting fluid behavior. He discusses the evolution of AI in CFD, the challenges of data availability, and the differing adoption rates between industries. The episode concludes with predictions about the future of foundational models and their impact on the engineering landscape.
Chapters
00:00 Introduction to the Podcast and Topic
01:09 Foundational Models in Fluid Dynamics
10:09 The Evolution of AI in CFD
19:52 Future Predictions and Industry Dynamics
In this episode of the Neil Ashton podcast, the discussion revolves around foundational models in fluid dynamics, particularly in the context of computational fluid dynamics (CFD). Neil shares insights from a recent panel discussion and explores the potential of AI in predicting fluid behavior. He discusses the evolution of AI in CFD, the challenges of data availability, and the differing adoption rates between industries. The episode concludes with predictions about the future of foundational models and their impact on the engineering landscape.
Chapters
00:00 Introduction to the Podcast and Topic
01:09 Foundational Models in Fluid Dynamics
10:09 The Evolution of AI in CFD
19:52 Future Predictions and Industry Dynamics
Previous Episode

S2 EP10 - Dr. Kurt Bergin-Taylor, Head of Innovation - Tudor Pro Cycling
In this episode of the Neil Ashton podcast, Neil discusses the intersection of cycling and engineering with Kurt Bergin-Taylor, head of innovation at Tudor Pro Cycling. They explore how technology and science are transforming cycling into a more competitive and innovative sport, akin to Formula One. The conversation covers various aspects of cycling, including the importance of aerodynamics, nutrition, and the holistic approach to rider performance. Kurt shares insights from his academic background and experiences in professional cycling, emphasizing the need for tailored training and the integration of technology in enhancing performance. They discuss the future of cycling innovation, emphasizing the importance of individualization in gear, collaborative relationships with partners, and the evolving mindset of young cyclists. Kurt highlights the significance of data and AI in optimizing performance and strategies in cycling, while also addressing the need for viewer engagement in the sport. Finally Kurt shares valuable advice for aspiring engineers looking to enter the cycling industry, stressing the importance of mentorship and practical experience.
Chapters
00:00 Introduction to the Podcast and Themes
04:55 Kurt Bergin-Taylor: Background and Role at Tudor Pro Cycling
10:08 The Structure and Dynamics of a Pro Cycling Team
12:59 Innovation in Cycling: Aerodynamics, Thermal Management, and Safety
19:14 Nutrition, Training, and Performance in Cycling
29:18 Future Innovations in Cycling Equipment and Systems
30:42 Understanding Individualization in Cycling Gear
34:30 Collaborative Innovation in Cycling Equipment
38:20 The Evolving Mindset of Young Cyclists
42:28 Enhancing Viewer Engagement in Cycling
46:24 The Future of Data and AI in Cycling
50:05 Advice for Aspiring Engineers in Cycling
Takeaways
- Cycling is increasingly influenced by technology and engineering.
- Tudor Pro Cycling is focused on long-term performance and innovation.
- Aerodynamics plays a crucial role in cycling performance.
- Thermal management is essential for riders in extreme conditions.
- Nutrition has dramatically improved in cycling over the last decade.
- Training methodologies must be tailored to individual riders.
- The relationship between power output and speed is complex.
- Safety innovations are critical as speeds increase in cycling.
- Understanding the whole system of rider and equipment is vital.
- Professional cyclists have different recovery capabilities compared to amateurs. Individualization in cycling gear is crucial for performance.
- Collaborative innovation with partners enhances product development.
- Young cyclists are more educated but sometimes overlook tactical aspects.
- Data-driven insights are essential for optimizing race strategies.
- Viewer engagement can be improved through real-time data sharing.
- AI and machine learning are emerging tools in cycling optimization.
- Mentorship is vital for aspiring professionals in the cycling industry.
- Practical experience and initiative can open doors in professional sports.
- Cycling offers a holistic approach to engineering and performance.
- The cycling industry is growing, providing more opportunities for engineers.
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