How Much Data Is Enough? Why the Riemann Zeta Function Predicts the Future of AI & Discovery
In biomedical AI, we constantly ask: Do we need more data, or do we need a smarter model?In this episode, we break down The Zeta Law of Discoverability—a theoretical framework linking sample size comp...
30 Elo 34min
Why general artificial intelligence is a myth?
Welcome back to the podcast! Today we are diving into a thought-provoking new paper titled 'AI Must Embrace Specialization via Superhuman Adaptable Intelligence' by researchers including Judah Goldfed...
11 Maalis 21min
Taps, Leaks, and Plugs: Explaining the Worldwide Rise in Parkinson's
Why are global Parkinson's disease cases projected to skyrocket to 25.2 million by 2050?In this episode, we explore an ingenious "bathtub analogy" to explain this massive growth. We break down the "in...
6 Maalis 19min
Hallmarks of Cancer: The Paper That Defined a Field
Few scientific papers truly define a field. The Hallmarks of Cancer is one of them.In this episode, I dive into the evolution of the Hallmarks framework—where it started, how it has shaped decades of ...
1 Helmi 18min
Closing the Women’s Health Gap: From History to Future Innovation
This episode dives into the history and persistent gaps in women’s health research — from decades of exclusion in clinical trials to today’s underfunding of critical conditions like menopause, autoimm...
16 Syys 202519min
Rotterdam Studie Bijgewerkt 2024
De Rotterdam Studie is een langlopende, populatie-gebaseerde cohortstudie in Nederland die zich richt op het identificeren van risicofactoren en het begrijpen van het verloop van multifactoriële aando...
1 Touko 20257min
Beyond Human Data: How AI Will Learn Like We Do
We’re standing at a turning point in AI. Until now, machines have learned by studying us — reading our books, analyzing our conversations, mimicking our decisions.But what happens when AI starts learn...
28 Huhti 202514min
