How Datumo’s $15.5M Funding is Shaping the Future of AI Model Evaluation

Laude Institute's Slingshots Program: Transforming AI Research Funding

Update The Launch of Slingshots: A Paradigm Shift in AI Funding On November 6, 2025, the Laude Institute unveiled its inaugural batch of Slingshots AI grants, presenting a transformative opportunity in the landscape of artificial intelligence research. Unlike the conventional academic funding processes that have been historically restrictive and competitive, the Slingshots program aims to bridge the gap between academic innovation and practical application. By offering a unique blend of resources—ranging from funding and advanced computational capabilities to engineering support—the initiative is designed to empower researchers to address critical challenges in AI, particularly in evaluation. Why the Slingshots Program Matters The launch comes at a crucial juncture when AI startups have attracted a staggering $192.7 billion in global venture capital in 2025 alone, capturing more than half of all VC investment. Yet, early-stage researchers continue to grapple with limited resources. By challenging the norms of traditional funding models, this initiative represents an effort to ensure that groundbreaking scientific achievements do not languish in academic obscurity. Each recipient of the Slingshots grant is not only promised financial assistance but also committed to delivering tangible products—be it a startup, an open-source codebase, or another form of innovation. This outcomes-driven approach sets a new standard in research funding, where accountability and real-world impact are prioritized. Highlighted Projects from the Initial Cohort The first cohort of Slingshots includes fifteen innovative projects from some of the world’s leading institutions, such as Stanford, MIT, and Caltech. Among these projects are notable endeavors like Terminal-Bench, a command-line coding benchmark designed to enhance coding efficiency and standardize evaluations across AI platforms. Similarly, Formula Code aims to refine AI agents’ ability to optimize code, addressing a critical gap in AI performance measurement. Columbia University's BizBench contributes to this cohort by proposing a comprehensive evaluation framework for “white-collar” AI agents, tackling the need for performance benchmarks that span beyond technical capabilities to include practical applications. The Role of AI Evaluation A central theme of the Slingshots program is its emphasis on AI evaluation, an area often overshadowed by more aggressive commercialization pursuits. As the AI space grows, clarity in evaluating AI systems becomes increasingly paramount. John Boda Yang, co-founder of SWE-Bench and leader of the CodeClash project, voiced concerns about the potential for proprietary benchmarks, which could stifle innovation and lead to a homogenization of standards. By supporting projects that seek to create independent evaluation frameworks, the Laude Institute positions itself as a champion for transparent and equitable benchmarks that foster progress. Implications for Future Entrepreneurship The Slingshots program is not just a funding initiative; it embodies a strategic effort to reshape the future of AI entrepreneurship. As the startup growth rate climbs worldwide, particularly in the Asia-Pacific region, maintaining a balance of innovation and ethical considerations is essential. With the rollout of Slingshots, researchers now have a stronger footing to engage in the entrepreneurial sphere while addressing societal challenges. The prospect of entrepreneurial success is complemented by an extensive support system, allowing researchers to draw from resources that would otherwise be inaccessible. This dynamic is pivotal as it empowers innovators to bring forward ideas and technologies that can facilitate real change in the industry. Success Stories and Future Prospects Initial success stories emerging from the program demonstrate its potential impact—the Terminal-Bench project has already established itself as an industry-standard in a remarkably brief time frame. Such rapid development exemplifies how adequate support can compress lengthy traditional research cycles into shorter timeframes, thereby accelerating the path from concept to marketplace. As we look to the future, it is evident that the Slingshots program should serve as a template for fostering innovation while dismantling existing barriers in research funding. If the inaugural cohort achieves its objectives, the model could inspire expanded initiatives across the broader research ecosystem, promoting both economic growth and ethical standards within the tech industry. Conclusion: The Future of AI Funding The Laude Institute’s Slingshots program marks a significant shift in how artificial intelligence research is financed and pursued. By addressing the systemic hurdles faced by early-stage researchers and promoting a culture of responsible innovation, the program paves the way for developments that prioritize social benefit alongside technological advancement. As we witness the emergence of the inaugural recipients’ projects, the AI landscape might very well be on the brink of a transformation that could redefine the industry's trajectory for years to come.