Autoscience reports a milestone in publishing peer-reviewed work largely authored by its AI agent, Carl, including at least one paper accepted at an ICLR workshop.

Autoscience, a San Mateo AI research lab, has raised $14 million in seed funding led by General Catalyst, with participation from Toyota Ventures, MaC Ventures, Perplexity Fund and S32, to automate the development of new machine learning models.

CEO Eliot Cowan says the goal is to compress a decade of ML research into months, enabling faster discovery and a competitive edge for customers.

Industry context notes other AI research advances, such as Sakana AI in Tokyo, which also claims peer-reviewed work in ICLR, signaling a broader trend toward AI-driven scientific inquiry.

Autoscience aims to replace traditional human-led R&D with autonomous AI-driven discovery and deployment to accelerate proprietary ML breakthroughs.

The press release includes standard contact information, with Markets Insider and Business Insider Editorial Teams not involved in creating the post.

Autoscience positions its offering as a turnkey autonomous R&D service to test, validate, and translate ideas into production-ready models rapidly.

Autoscience has prior recognition, including a peer-reviewed ICLR 2025 workshop paper and a Silver Medal in Kaggle Santa 2025, highlighting milestones for autonomous AI systems.

General Catalyst’s Yuri Sagalov emphasizes that scalable experimentation and faster validation-to-production workflows are central as automation accelerates ML development.

Cowan argues humans cannot efficiently sift through the flood of research papers, while AI can review tens of thousands to find those relevant to specific modeling problems.

The investment signals investor confidence in autonomous AI R&D to speed testing, validation, and productionization of new models.

Funding will scale the managed service for Fortune 500 and large private companies, expanding the engineering team and increasing capacity to generate and ship continuous model improvements.