In a recent episode of People by WTF, Zerodha co-founder Nikhil Kamath sat down with Dario Amodei, CEO of Anthropic, to explore the future trajectory of artificial intelligence, its implications for biotechnology, and the shifting dynamics of data-driven competitive advantage.
During the conversation, Amodei outlined his view that artificial intelligence may significantly accelerate scientific discovery, particularly in healthcare and biotechnology. “I’m positive on biotech. I think biotech is about to have a renaissance… ultimately driven by AI,” he said.
He emphasized that advancements in AI could enable faster optimization of biological systems, highlighting peptide-based therapies and cell-based treatments such as CAR-T as areas where AI-driven design may expand the scope of medical innovation.
The discussion also addressed evolving assumptions around data as the primary driver of AI progress. Amodei noted that reinforcement learning environments and synthetic data generation are becoming increasingly important in model development. “When you train on math or coding environments, you’re not really getting data… it’s more synthetic. You’re creating the data,” he said, adding that “dynamic data that the model creates itself… is becoming more important.”
While acknowledging that data remains relevant, particularly in language optimization and enterprise applications, Amodei suggested that intelligent iteration and environment-based learning may play a larger role in future AI advancements and may reduce the centrality of static data as a competitive moat.
Kamath and Amodei further discussed usability challenges as AI adoption expands beyond technical audiences. Amodei highlighted Anthropic’s efforts to improve accessibility and invest in user education, noting that “there’s a learning curve,” and comparing prompt engineering to learning a musical instrument. He added, “You mostly learn by doing.”
The conversation also explored regulatory and geopolitical dimensions shaping AI deployment. Amodei referenced data localization policies in Europe as an indicator of how global AI infrastructure may evolve toward regionally grounded architectures involving distributed data centers and compliance-driven deployment models.
Reflecting on AI’s broader trajectory, Amodei reiterated a balanced perspective that acknowledges both transformative potential and associated risks. “My instinct is we’re about to cure a lot of diseases,” he said, while also noting the importance of responsible development and governance.
The discussion concluded with a focus on the convergence of artificial intelligence and biology as a potential driver of long-term technological transformation, with both speakers highlighting programmable biology as a key frontier for AI-driven innovation.
