[State of Research Funding] Beyond NSF, Slingshots, Open Frontiers — Andy Konwinski, Laude Institute

Dual-track funding model

The Institute operates a nonprofit for pre-incorporation open research and Laude Ventures for post-incorporation startups, unified by an obsession with 'shipping'—open source projects for the nonprofit and commercial products for the venture arm.

Researcher-led governance

Organization runs 'for researchers, by researchers' with 50+ top faculty (including Jeff Dean) and unicorn founders from Databricks and Perplexity serving as investment partners and advisors.

Right resource, right time

Structure targets the critical 'dotted line' of incorporation to provide resources exactly when researchers need them, bridging the gap between academic breakthrough and commercial application.

Multi-founder teams derisk startups

Large research teams with 7-8 co-founders (like Databricks, OpenAI, or VMware) reduce 'founder divorce risk' while proving ability to execute breakthroughs together before raising capital.

Replicating the Databricks Motion

Path follows NSF-funded research becoming open-source breakthroughs (like Apache Spark) that translate into hundred-billion-dollar companies, a model also seen in Perplexity, Anysphere, and Google.

New gold standard for VCs

Researcher-led startups have reached a tipping point where PhD founders are becoming the highest-leverage path from breakthrough to world-changing company, attracting top-tier venture interest.

Compound systems focus

Slingshots fund the 'layer above' base models—context management, agent tool use, memory curation, and prompt optimization—exemplified by DSPy/JEPA optimizers using evolutionary genetic techniques.

Post-training efficiency

Research targets continual learning methods that update model knowledge without full retraining (avoiding 10,000 GPU hours), analogous to human memory updating rather than brain rewiring.

Concrete funded projects

Specific initiatives include Terminal Bench (evaluation frameworks), Arena (comparison platforms), and research into compound AI systems that manage context and agent decisions.

NSF's critical funding gap

NSF's $1 billion annual computer science budget—facing potential cuts to half—is insufficient for frontier AI research, which requires $10-100 billion annually to compete globally.

Venture-style selection

Replaces traditional peer review with Silicon Valley 'picker' expertise to deploy capital faster, with stronger opinions narrowly focused on high-impact AI systems, cryptography, and architecture.

Geographic diversification

Expanding beyond Berkeley/Stanford to CMU, MIT, UIUC, University of Washington, and Canadian universities (Toronto, Waterloo, McGill) via PhD entrepreneurship clubs.