Making Science Larger, not just Faster

The dominant framing of enterprise AI is speed: faster code, faster decisions, faster discovery. That framing misses the larger story. When AI is anchored to the equations of physics, chemistry and biology rather than to the corpus of the open web, it does not just compress timelines — it expands the space of what can be explored. A bigger biochemical landscape for drug discovery. A bigger materials landscape for batteries and alloys. A bigger design landscape for everything humans build. Drawing on SandboxAQ’s deployments across pharma, energy and navigation, Yuval shows why Large Quantitative Models are the first AI architecture capable of growing the pie rather than slicing it thinner, and what that means for any enterprise still measuring AI value in cost reduction.