New science begins where existing knowledge ends. New medicines and materials are forged beyond the edge of what is known. We predict, we test, we learn, we create. With each idea and experiment, we turn the wheel of science. 

Today, artificial intelligence is mastering existing knowledge—recognizing complex patterns in centuries of recorded discovery. This is possible through the remarkable power of scale that transforms quantitative improvements into qualitative leaps. By increasing compute, data, and model size, AI systems consistently achieve not only faster performance, but fundamentally new capabilities. 

In science, AI trained on millions of scientific papers, genetic sequences, and chemical structures can perform impressive tasks in summarizing literature, predicting protein structures, and modeling complex systems. More historical data will make these systems more capable, but the world extends beyond what has been written down. There is more to the universe than what is on the internet. Most of the world lies outside of curated datasets. 

At the heart of our work lies our ambition to reinvent the most important wheel in history—the wheel of the scientific method. To enable an intelligence revolution for the wheel of science, science needs a new kind of laboratory, where AI can explore beyond the edge of what is known. Not simply an automated lab, but a lab fundamentally built for scientific intelligence to experiment, to play, and to learn. We believe that a new kind of intelligence, something we call Scientific Superintelligence, will emerge when AI can design and run thousands of parallel experiments, each advancing understanding of the physical world. This is what we are building at Lila. 

As the ability to perform such experiments scales, so too does the capability of scientific AI. At Lila, we believe that science, spanning from physical science to life science and beyond, is governed by scaling principles that mirror the pathways of progress in AI. Just as larger AI models unlock emergent abilities, scaling scientific experimentation enables discoveries that remain hidden at smaller scales. 

Just as AI playing countless games of Go opened up creative new strategies, new capabilities are possible when AI can conduct self-guided research—designing and running experiments, learning from each result, and using that knowledge to design better experiments. 

When AI turns the wheel of science, new paths are illuminated, new results brought into the world faster than could be imagined. The challenges we face, in health, climate, and beyond demand urgency and an acceleration of science. We cannot wait for incremental progress. 

For transformative science we must transform the scientific process. To turn the incremental to the exponential, we are rethinking the scientific method from first principles. 

We are builders, problem solvers, and truth seekers working at the intersection of AI and experimental science. Join us in reimagining what science can become.