Laude Institute announces first batch of ‘Slingshots’ AI grants

The Laude Institute announced this on Thursday the first series of Slingshots grantsaimed at “advancing the science and practice of artificial intelligence.”

The Slingshots program is designed as an accelerator for researchers and is intended to provide resources that would not be available in most academic environments, whether it be funding, computing power or product and technical support. In return, the recipients promise to produce a final product, whether it is a startup, an open source codebase, or some other kind of artifact.

The initial cohort consists of 15 projects, with a particular focus on the difficult problem of AI evaluation. Some of these projects will be familiar to TechCrunch readers, including the command-line coding benchmark Terminal Bench and the latest version of the long-running ARC-AGI project.

Others take a fresh approach to a long-standing evaluation problem. Formula Code, built by researchers at Caltech and UT Austin, aims to evaluate the ability of AI agents to optimize existing code, while Columbia-based BizBench proposes a comprehensive benchmark for “white-collar AI agents.” Other grants investigate new structures for reinforcement learning or model compression.

SWE bank co-founder John Boda Yang is also part of the cohort, leading the new CodeClash project. Inspired by the success of SWE-Bench, CodeClash will review code through a dynamic, competition-based framework, which Yang hopes will

“I think people who continue to evaluate against third-party benchmarks are making progress,” Yang told TechCrunch. “I’m a little concerned about a future where benchmarks only become specific to companies.”