A.I. Scientists Are Here. But Is Progress Accelerating? | EP 170

Quick Overview

AI progress in drug discovery and core science is accelerating significantly, as demonstrated by the 2024 generation of AI models like those from Google DeepMind and Anthropic, which are already producing results previously expected years later, although the hype surrounding some claims still needs to be tempered with scientific rigor and long-term validation.

Key Points: Sam Rodrigues, co-founder and CEO of Future House & Edison Scientific, is the guest expert discussing AI's impact on scientific discovery, particularly in biology. The current generation of AI models (like those from Google DeepMind and Anthropic) is producing results much faster than previously anticipated, with some achievements that were expected years out now occurring in 2024. A key breakthrough discussed is AI's ability to generate novel scientific hypotheses, such as designing a new antibiotic that inhibits a virus or bacterium that previously had no known inhibitor. The cost of running these complex AI experiments is high, with one model run costing $200 per prompt, necessitating careful prioritization by scientists. Rodrigues notes that while AI excels at tasks like predicting protein structure (e.g., AlphaFold), the bottleneck is often the subsequent need for slow, expensive wet-lab validation, which requires patient scientists and significant funding. The expectation is that AI will continue to accelerate scientific breakthroughs, potentially solving major diseases within the next decade or two, but this relies on continued progress in areas like BCI (Brain-Computer Interfaces) and automated lab work.

Context: This episode of the Hard Fork podcast features Kevin Roose and Casey Newton interviewing Sam Rodrigues, the co-founder and CEO of Future House and Edison Scientific. The discussion centers on the current state and future trajectory of AI, specifically focusing on how rapidly AI is advancing scientific discovery, particularly in biology and drug development, and whether the public hype matches the actual, verifiable scientific progress being made.