# How Paradigm4 Is Helping Organizations Remove Hidden AI Bottlenecks

Page: https://stenobird.com/podcast/tech-talks-daily-3579/how-paradigm4-is-helping-organizations-remove-hidden-ai-bottlenecks
Text version: https://stenobird.com/podcast/tech-talks-daily-3579/how-paradigm4-is-helping-organizations-remove-hidden-ai-bottlenecks.md
Podcast: [Tech Talks Daily](https://stenobird.com/podcast/tech-talks-daily-3579)
Published: 2026-06-13T00:00:00+00:00
Episode link: https://techtalksnetwork.com/
Audio file: https://traffic.libsyn.com/secure/techblogwriter/Tech_Talks_Daily_P4.mp3?dest-id=289572
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JSON: https://stenobird.com/v1/public/podcasts/tech-talks-daily-3579/episodes/how-paradigm4-is-helping-organizations-remove-hidden-ai-bottlenecks
Duration seconds: 1364

## Resource

What happens when a company focused on drug discovery and life sciences encounters a data problem that nobody else seems able to solve? Recorded at the IT Press Tour in Boston, this episode explores the fascinating story behind Paradigm4 and how a challenge in large-scale biomedical research ultimately led to the creation of flexFS, a cloud-native filesystem designed to tackle some of today's biggest data infrastructure challenges. Joining me on the podcast is David Freund from Paradigm4, who shares how the company was originally founded to help scientists work with enormous datasets in fields such as genomics, bioinformatics, and precision medicine. As researchers began working with population-scale datasets such as the UK Biobank, the team discovered that existing storage technologies either couldn't deliver the performance they needed, lacked the functionality required, or became prohibitively expensive at scale. Our conversation explores the moment Paradigm4 realized it would need to build its own solution, why traditional approaches to cloud storage often struggle under modern analytics workloads, and how flexFS emerged from a real-world customer problem rather than a technology trend. David also explains why object storage has become such an attractive foundation for modern infrastructure, while discussing the challenges of latency, performance, and cost that still need to be addressed. We also discuss why many organizations investing heavily in AI infrastructure may be overlooking one of the biggest constraints on performance. While much of the industry conversation focuses on GPUs and compute power, David argues that data access, movement, and management are becoming equally important considerations as AI workloads continue to grow. Along the way, we touch on c…

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