Stories about Lila's research, people, and discoveries

In three months, Lila Sciences’ AI-directed lab proposed, synthesized and screened 2,942 catalysts for green hydrogen, identifying 6 high-performing material families.

Open-ended search is core infrastructure for scientific superintelligence, according to AI researcher Ken Stanley. This profile of Stanley's open-endedness team explores why that approach is central to autonomous science.

Ben Kompa, Head of AI-Lab Innovation, has been named to MIT Technology Review's 35 Innovators Under 35. Ben's work sits at the intersection of AI and automated experimentation, exactly the kind of bridge-building this recognition is meant to celebrate.

Lila's autonomous science platform first discovered ultra-stable mRNA. Then it outperformed the leading CAR-T therapy in non-human primates.

LILA joins DOE's Genesis Mission, earning Phase I awards for three AI-driven science projects with Caltech, LBNL, Northwestern, Argonne, and NLR.

The next era of AI-for-science belongs to agents that can reason across domains and test their own hypotheses in a physical lab.

Shell's Pearl GTL plant took 40 years and $19 billion to deliver ROI — a timeline oil and gas can no longer afford. This piece explores how Lila Sciences' technology is compressing R&D cycles from decades to months through autonomous, lab-based experimentation.

Lila Sciences closed a $350M Series A, bringing total funding to $550M, to scale its AI Science Factories and deploy its scientific superintelligence platform to partners tackling the world’s most complex challenges.

Lila Sciences is introducing the world’s first scientific superintelligence platform for life, chemical, and materials sciences.

Lila Sciences announced a major Series A milestone, raising $235M to advance its mission of building scientific superintelligence.

Fast Company has named Lila Sciences' CEO and co-founder Geoffrey von Maltzahn one of its 2026 Tech Visionaries of the Year, recognizing him "for automating execution of the entire scientific method."

In this episode, Lila's Chris Fussell discusses how autonomous labs could act as a "time machine for science," pulling decades of discovery into the present. He shares lessons from special operations on closing the gaps between silos, and what they mean for policy.

Ben Kompa, Head of AI-Lab Innovation, has been named to MIT Technology Review's 35 Innovators Under 35. Ben's work sits at the intersection of AI and automated experimentation, exactly the kind of bridge-building this recognition is meant to celebrate.

An AI-guided, human-supervised closed-loop platform screened thousands of metal oxide catalysts to discover Ir- and Ru-free, Pd-based oxides that match or exceed incumbent catalysts’ activity for acidic oxygen evolution while dramatically improving stability

This Comment, from the TPC26 conference, argues that AI, autonomous agents, self-driving labs, and quantum computing are converging to transform materials and chemical science discovery.

Abstract from the ASGCT 2026 annual meeting: Lila Sciences used its AI-driven, autonomous “wheel of science” platform to develop a high-performing in vivo CAR-T therapy targeting B cells, aiming to overcome key manufacturing and efficacy challenges facing current T cell immunotherapies.

The AI4Mat-ICLR-2026 workshop brought together researchers across AI-guided design, automated synthesis, and automated characterization to advance materials discovery, featuring invited talks on reinforcement learning and cross-modal materials representations alongside community initiatives like a Tiny Papers track and travel grants.

Only about 5% of scientific hypotheses can be verified cheaply. The rest require real experiments, which makes most of science dark matter for reinforcement learning. Lila Sciences is building the verifier: an autonomous laboratory designed to train AI models.

At Artificial Happiness, senior vice president of Open-Endedness, Ken Stanley, discusses how the path to greatness is paved with stepping stones you can't predict, and the greatest discoveries come from following what's interesting, not what's planned.