EECS researchers receive Laude “Slingshot” awards to advance next-generation AI systems

by Matthew Santillan on April 2, 2026

Three research projects featuring contributors from Sky Computing Lab have recently been selected for Laude’s Slingshot program.

Featured Research Projects:

  • Continual Learning Benchmark
  • Researchers: Parth Asawa, Matei Zaharia
  • A benchmark that evaluates how well models and systems improve over time, explicitly testing continuous learning rather than point-in-time static capability.
  • MAP: Measuring Agents in Production
  • Researchers: Melissa Pan, Matei Zaharia
  • A comprehensive study of production agents across 26 domains reveals that reliability remains the top challenge, currently mitigated through systems-level design, suggesting underexplored research directions for future agent systems.
  • OpenThoughts-Agent
  • Researchers: Etash Guha, Ryan Marten, Ben Feuer, Negin Raoof, Richard Zhuang, Tyler Griggs (Sky), Charlie Ruan (Sky), Alex Shaw, Mike Merrill, Ludwig Schmidt, and Alex Dimakis (EECS).
  • An end-to-end open setup for training and evaluating terminal agents, with curated data, real environments, and RL loops that make agent research reproducible for everyone.

The Laude Slingshot is a specialized funding initiative by Laude Institute, an organization that supports computer science researchers turning research into real-world impact.

The Slingshot program, unlike traditional multi-year grants, is an agile funding mechanism designed by Laude to accelerate the translation of computer science research. It specifically targets “bottleneck” problems—the precise technical or resource hurdles that, once resolved, can propel a project to its next major milestone. By injecting rapid capital and connecting academic teams with a vital network of industry experts, Laude helps Berkeley researchers operate with the speed and efficiency of a startup. This critical support ensures that UC Berkeley’s breakthrough discoveries move from the lab to the public domain and industry applications faster than ever before.

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