Learn how Cambridge Spark helps organisations and leaders develop the data and AI skills that drive real transformation: cambridgespark.com

Ever wondered how Formula 1 teams make lightning-fast decisions at 200mph? In this episode, host Raoul-Gabriel Urma sits down with Ruth Buscombe, former race strategist for Scuderia Ferrari, Sauber, and Haas F1, to unpack the incredible world of real-time data strategy in one of the most high-pressure environments on Earth.

Ruth shares what it's really like making million-dollar calls in milliseconds, how her team processes 1.1 million data points per second from each car, and why the best lessons come from spectacular failures (not champagne-soaked victories).

One of the most fascinating parts of the discussion is when Ruth explains the eternal tension between data and gut feel, and why human intuition still matters even when you have the best models in the world.

Spoiler: your "gut" is really just your brain's LLM of past experience.

They also explore how F1 teams decide which sensors and data points actually move the needle when margins come down to 0.012 seconds, and what it's like to make high-stakes pit-stop calls with incomplete information (sound familiar, business leaders?).

Ruth also shares some powerful stories about ‘failing forward’, including why Mercedes boss Toto Wolff says "the day we fail is the day our competitors should fear us most."

Plus, they look at how AI is transforming sports broadcasting, with F1 now able to search 75 years of race footage using simple natural-language queries. And of course, they wrap up with a quick-fire round covering everything from Python vs MATLAB to favourite subjects at Cambridge and yes, Taylor Swift workout playlists.

Be sure to follow Data & AI Mastery wherever you listen to your podcasts to never miss an episode.

You can check out Formula 1's official site to learn more about the sport, or head to F1 TV if you want to dive deeper into the data and analysis Ruth works on.

Whether you're leading a startup, managing a data team, or just fascinated by how top performers think under pressure, this conversation is packed with insights you can actually use.

Chapters

00:00 - Introduction: Learning from F1's best failures

02:00 - Ruth's journey from Cambridge engineering to the F1 pit wall

03:00 - The insane scale of F1 data (1.1M points/second!)

06:00 - How do you decide what data to collect?

09:00 - Three pillars: Performance, competitor analysis & race strategy

13:00 - When should you trust data vs. gut instinct?

17:00 - Managing risk like a portfolio manager

20:00 - Creating a culture that embraces pressure

23:00 - AI transforming F1 broadcasting & fan experience

26:00 - Quick-fire: Python, physics & being a Swiftie

27:00 - Key takeaways for business leaders

Links

Connect with Ruth on LinkedIn

Follow Raoul for more AI insights on LinkedIn

Explore Cambridge Spark’s AI upskilling programmes at cambridgespark.com

Visit Formula 1's official site at formula1.com

Visit F1 TV at f1tv.formula1.com

Learn how Cambridge Spark helps organisations and leaders develop the data and AI skills that drive real transformation: cambridgespark.com

In this episode of Data & AI Mastery, host Dr. Raoul-Gabriel Urma speaks with Ming Tang, Chief Data and Analytics Officer at NHS England. Ming has spent her career leading some of the most ambitious digital and data transformations in the UK public sector.

Together, they explore how data and AI are reshaping the future of healthcare, from modernising patient journeys and connecting siloed systems to deploying AI tools that help clinicians and operations teams work smarter. Ming’s insights highlight how the right mindset, structure, and curiosity can unlock meaningful impact at scale.

Listeners will also discover how the NHS is building a connected, patient-centric ecosystem through the Federated Data Platform (FDP) and the single patient record initiative and why listening and collaboration, not just technology, are key to solving complex system challenges.

Whether you work in healthcare, data science, or digital transformation, this conversation offers powerful lessons in leading with purpose, designing around users, and scaling innovation responsibly.

Be sure to follow Data & AI Mastery wherever you listen to your podcasts to never miss an episode.

Chapter Markers:

(03:30) Lessons from leading large-scale transformation

(06:00) Why listening and curiosity matter more than technology

(11:00) Designing flexible, modular NHS systems for efficiency and collaboration

(15:00) The Federated Data Platform: enabling connected, data-driven care

(18:00) Real-world AI applications in the NHS: discharge summaries, voice tech & analytics

(21:00) Advice for leaders; adopting AI through curiosity and context

(25:00) Raoul’s reflections; leading with empathy, curiosity, and user-first thinking

Useful Links:

Connect with Ming on LinkedIn

Follow Raoul for more AI insights on LinkedIn

Explore Cambridge Spark’s AI upskilling programmes at cambridgespark.com

Learn more about how CambridgeSpark.com is helping organisations and professionals master Data & AI skills to stay ahead in the digital era.

In this episode of Data & AI Mastery, host Dr. Raoul-Gabriel Urma sits down with Dr. Petar Veličković, Senior Staff Research Scientist at Google DeepMind and Affiliate Lecturer at the University of Cambridge.

Together they explore how cutting-edge AI research transitions from theory to practice, spanning from breakthroughs in graph neural networks that power Google Maps worldwide, to the use of AI as a discovery partner in mathematics. Petar shares his journey from Serbia to Cambridge to DeepMind, and the pivotal lessons learned at every stage.

Listeners will also hear how DeepMind’s graph machine learning models improve global travel-time predictions in Google Maps, how AI can accelerate scientific discovery, including mathematical proofs and what the concept of an “AI scientist” might mean for the future of research.

Whether you’re a data scientist, ML engineer, or executive exploring AI strategy, this episode offers a masterclass in applying AI innovation with purpose and impact.

Be sure to follow Data & AI Mastery wherever you listen to your podcasts to never miss an episode.

Chapter Markers:

(06:00) - Inside DeepMind; what a Senior Staff Research Scientist does

(13:00) - From research to real-world impact: challenges & latency trade-offs

(19:00) - AI for mathematics; collaborating with top researchers

(25:00) - Defining the “AI scientist” and the future of autonomous research

(30:00) - What’s next for AI agents and self-directed systems

(31:00) - Quick-fire round; programming languages, school favourites & music

(33:00) - Raoul’s takeaways; user focus, AI as a thought partner, safe deployment

Useful Links:

Connect with Petar on LinkedIn

Follow Raoul for more AI insights on LinkedIn

Explore Cambridge Spark’s AI upskilling programmes at cambridgespark.com