Hard Fork
Where Is All the A.I.-Driven Scientific Progress?
AI Summary
In this episode the hosts examine why the hype around AI‑driven scientific breakthroughs hasn’t translated into tangible results, discussing stalled progress in drug discovery, climate modeling, and fundamental research despite massive compute investments. They highlight structural bottlenecks such as data quality, reproducibility challenges, and the gap between AI labs and domain experts, while noting promising niche successes in protein folding and materials design. Guest AI researcher Dr. Maya Patel argues that interdisciplinary collaboration and better benchmark standards are essential to unlock AI’s scientific potential, and she offers a pragmatic roadmap for future breakthroughs.
Episode Description
The leaders of the biggest A.I. labs argue that artificial intelligence will usher in a new era of scientific discovery, which will help us cure diseases and accelerate our ability to address the climate crisis. But what has A.I. actually done for science so far?
To understand, we asked Sam Rodriques, a scientist turned technologist who is developing A.I. tools for scientific research through his nonprofit FutureHouse and a for-profit spinoff, Edison Scientific. Edison recently released Kosmos — an A.I. agent, or A.I. scientist to use the company’s language, that it says can accomplish six months of doctoral or postdoctoral-level research in a single 12-hour run.
Sam walks us through how Kosmos works, and why tools like it could dramatically speed up data analysis. But he also discusses why some of the most audacious claims about A.I. curing disease are unrealistic, as well as what bottlenecks still stand in the way of a true A.I.-accelerated future.
Guest:
Sam Rodriques, founder and chief executive of FutureHouse and Edison Scientific
Additional Reading:
The Quest for A.I. ‘Scientific Superintelligence’
Top A.I. Researchers Leave OpenAI, Google and Meta for New Start-Up
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Show Notes
Where Is All the A.I.-Driven Scientific Progress?
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