Key Highlights

• Anthropic CEO Dario Amodei predicts AGI (“country of geniuses in a data center”) within one to two years, with 90% confidence within a decade, and warns that society is not prepared for the disruption ahead.
• Anthropic is locked in a standoff with the Pentagon and the Trump administration over two AI red lines: no domestic mass surveillance and no fully autonomous weapons. The company has been designated a supply chain risk – a measure previously reserved for foreign adversaries.
• Amodei argues AI technology is outpacing law and regulation, calling on Congress to act on Fourth Amendment protections and autonomous weapons oversight before it is too late.
• Yann LeCun outlines a research agenda centered on world models and the JEPA architecture, arguing that autoregressive LLMs are fundamentally limited and that self-supervised learning in abstract representation space is the path to human-level AI.
• Amodei sees biotech – especially peptide-based therapies, programmable mRNA, and cell-based therapies like CAR-T – as the sector most likely to be transformed by AI in the near term.

Interviews & Conversations

The AI Tsunami is Here & Society Isn’t Ready — Dario Amodei x Nikhil Kamath (1:08:35)

In this wide-ranging conversation recorded in Bangalore, Anthropic CEO Dario Amodei discusses his path from biophysics to AI, the founding of Anthropic, and his conviction that scaling laws are driving AI toward human-level intelligence. He explains that Anthropic was founded on two core beliefs: that scaling would produce increasingly capable models, and that safety must be taken seriously given the enormous economic and geopolitical consequences. Amodei describes a “tsunami” of AI capability approaching while public awareness remains alarmingly low, and notes that technical work on interpretability and alignment has gone better than expected while societal preparedness has gone worse. On India, he positions Anthropic as an enterprise platform seeking to empower local companies rather than compete with them, while acknowledging that the scope of AI automation will inevitably expand. He also discusses consciousness as an emergent property that AI systems may eventually possess, Anthropic’s decision to give models an “I quit” button, the importance of open-source versus proprietary models (arguing quality follows a power-law distribution favoring frontier models), and the shift from static training data to synthetic and reinforcement-learning-generated data. On investment opportunities, he singles out biotech – particularly peptide therapies and CAR-T cell therapies – as poised for an AI-driven renaissance.