On Thursday, the Laude Institute announced the recipients of its inaugural Slingshot grants, aimed at "advancing the science and practice of artificial intelligence." This innovative program serves as an accelerator for researchers, providing vital resources that are often lacking in traditional academic environments. The Slingshot grants offer funding, computational power, and engineering support to selected teams, who in return commit to delivering tangible outcomes, such as startups, open-source codebases, or other impactful projects.
Key projects among the recipients include:
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Formula Code: Developed by researchers from CalTech and UT Austin, this initiative focuses on evaluating AI agents’ effectiveness in optimizing existing software code.
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BizBench: Proposed by a team at Columbia University, this project aims to create a comprehensive benchmark for assessing "white-collar AI agents" performance.
Additional grants are exploring innovative frameworks for reinforcement learning and model compression, showcasing the diverse approaches being taken within the AI research community.
Among the grant recipients is John Boda Yang, co-founder of SWE-Bench, who will lead the new CodeClash initiative. Drawing inspiration from SWE-Bench’s success, CodeClash will evaluate code through a dynamic competition-based approach, intending to redefine how coding skills are assessed in AI contexts.
The Laude Institute’s Slingshot program represents a significant investment in pioneering AI research and development, with the potential to shape the future landscape of artificial intelligence applications.
