Open or closed AI? Nvidia’s Nader Khalil and Sydney Sykes take on one of the decisions shaping next-gen startups at TechCrunch Disrupt 2026

Startup founders face a choice between open and proprietary AI models that affects their company's future.

At TechCrunch Disrupt 2026, Nvidia executives Nader Khalil and Sydney Sykes will lead a session titled "The Open vs. Closed AI Debate Is Just Getting Started." The discussion, scheduled for October 13-15 in San Francisco, will focus on the critical decision startups face when choosing between proprietary and open-source AI models. This choice impacts cost, infrastructure, margins, differentiation, speed, and control for new companies. Khalil, Director of Developer Tech, and Sykes, Global Head of VC Partnerships, will explore the trade-offs involved, considering Nvidia CEO Jensen Huang's view that the future involves both proprietary and open AI. The session will also address the evolving AI landscape, where open models are rapidly advancing, and proprietary labs continue to push boundaries. The experts aim to provide clarity on where each approach makes commercial sense and how founders can make informed decisions for their businesses.

The core of the discussion revolves around the strategic decision of whether to leverage proprietary AI models for rapid development or opt for open models to gain greater control and flexibility. This choice has profound implications for a startup's operational costs, infrastructure management, product differentiation, and overall speed to market. Nvidia's stance, as articulated by CEO Jensen Huang, suggests a hybrid future where both approaches coexist, challenging a simplistic either/or dichotomy for founders.

The rapid advancement of open-source AI, evidenced by numerous research papers citing Nvidia's open models, alongside continued progress from proprietary labs, creates a complex commercial landscape. This session is designed to help founders and investors understand where true competitive advantage lies, whether in data, workflow, or specialized technology, rather than solely relying on the underlying AI model. Understanding these nuances is crucial for building investable and scalable businesses in the current AI market.