TECHNOLOGY
Building Scientific Superintelligence
LILA’s ADVANCED AI
A New Kind of Scientific Reasoning Model
Science is the ultimate token generator. Every experiment produces new data that has never existed before. The internet data that powered the current generation of AI has been exhausted, but scientific data generation never runs out. Lila is training a scientific reasoning model on these evergreen tokens to unlock new scaling laws for scientific intelligence.
Hear Andy Beam describe the power of the full agentic framework in his own words.
breadth is depth
A generalizable reinforcement learning engine powered by verifiers and tools
Scale Verifiers
& Tools
Expand what the model can learn and act upon
Autonomous Design
& Workflows
Lab network providing
real-world training rewards
Continuous Policy Optimization
The model learns the scientific method
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Across scientific domains
DNA
RNA
Proteins
Molecules
Cells
Surfaces
Nano
Pores
Coatings
Catalysts
AI SCIENCE FACTORIES
An extensible network of instruments built for AI-driven scientific discovery
An extensible network of instruments built for AI-driven scientific discovery
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Building Scientific Superintelligence
The LILA Intelligence Flywheel
← Inputs
Scientific Tokens
Lila's reasoning model runs the scientific method at scale. Every hypothesis, experimental design, result, and interpretation generates tokens that have never existed before. This is how we build the training data for each successive generation of the reasoning model.
Verifiers
Verifiable rewards have driven AI breakthroughs in math and coding, but most of science is hard to verify. Lila's AI Science Facilities Factories change that. By running real experiments at scale, they act as the world's largest verifier for science, providing the reward signal the model needs to learn.
Scientific Tools
Hard scientific problems require sophisticated tools: molecular dynamics simulators, protein structure predictors, quantum chemistry solvers, gene editors, and robotic lab workflows. Lila's model is pushing the frontier of complex, multi-step tool use, chaining these together to design and execute experiments no single tool could accomplish alone.
Compute
Lila is a new kind of frontier AI lab. Building scientific superintelligence requires the same scale of compute as building the world's most capable language models. We are pushing toward that frontier while pioneering large-scale RL reinforcement learning techniques purpose-built for scientific reasoning.
Outputs →
Science Gets Smarter
Intelligence improves across all of science, not just one domain. Because Lila's model runs the scientific method at scale across many fields, gains in reasoning, tool use, and experimental design transfer broadly. Each generation is a better scientist than the last.
Discovery Gets Faster
Imagine giving every scientific field not just a research team, but a thousand research teams, running experiments in parallel, 24 hours a day. That is what scaling scientific intelligence looks like. The pace of discovery accelerates not by making one scientist faster, but by multiplying the number of scientists working on every problem.
Science Gets Bigger
Scientific superintelligence makes world-class scientific reasoning widely available to anyone. Just as cloud computing made it possible to launch a tech company without building your own data center, Lila makes it possible to do frontier science without building your own R&D organization. Expanding who can do science dramatically increases the GDP of science and creates enormous value for the world.
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The next breakthrough begins here
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