platoseed
Autonomous AI research
We are automating AI research and development. Our aim is to help AI researchers uncover the next AlphaFold or build the next Transformer, faster, more systematically, and at scale. We treat discovery not as a matter of luck, but as a combinatorial search problem. Every major breakthrough in AI over the next decade will be made by Thesis.
Thesis is an AI research lab focused on automating AI R&D to advance scientific discovery. It positioning itself as an autonomous frontier AI lab that uses recursive self-improvement to explore hypotheses, experiments, and evaluations across domains like materials, robotics, and climate science.
Thesis provides a platform that automates AI R&D, enabling an autonomous loop where outcomes from experiments optimize subsequent ones. It offers a cloud-based environment (Thesis Cloud) with daily token limits in the Free/Spark tier and usage-based pricing (Ultra tier) for larger-scale workloads, allowing rapid setup without heavy manual tool integration.
Who it’s for: Labs and research teams doing cutting-edge AI-driven research in materials discovery, robotics, drug discovery, climate science, and related fields who need an autonomous R&D frontier AI lab.
Hiring AI researchers and engineers; YC-backed; active product and pricing page
Thesis will automate AI research. Maximally truth-seeking. Prev: AI R&D at Google X, Nvidia and Stanford's AI Lab, working with Andrew Ng and Chelsea Finn. B.S. Math & CS, M.S. Stats Stanford
Betting the farm that AI will become meaningful in the discovery of new science. Second time founder. Previously scaled stablecoin payments infrastructure from zero to billions. Columbia CS & Math.
Making it possible for researchers anywhere to discover the next Transformer or invent the next AlphaFold.
Thesis is an applied AI lab that accelerates AI discovery, enabling researchers worldwide to discover new models like Transformers or innovations such as AlphaFold. It aims to make state-of-the-art AI discovery 10x faster and cheaper, focusing on rapid experimentation and autonomous model training, with results on OpenAI’s MLE-Bench and a team with backgrounds in AI research and fintech.

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