Replace PayPal keynote speaker with Avinash Karn

Update the SSLLFM 2026 keynote from Chandramouliswaran (Mouli) V to Avinash Karn (Senior Director, AI Strategy, PayPal), using the provided bio and abstract without em or en dashes.

Co-authored-by: Cursor <cursoragent@cursor.com>

Author: PriyaTomar

ssllfm2026/index.md

@@ -47,11 +47,11 @@ This special session examines the deployment of large language and foundation mo
 
 ### The Operating System for AI-Native Enterprises: From Experimentation to Agentic Transformation
 
-**Dr. Chandramouliswaran (Mouli) V**, VP of AI & Site Lead, PayPal
+**Avinash Karn**, Senior Director, AI Strategy, PayPal
 
-Dr. Chandramouliswaran (Mouli) V is VP of AI & Site Lead at PayPal, where he has worked since 2009, overseeing global teams in data science, big data, platform engineering, risk and compliance, forecasting, and payments. He earned his PhD from the Wharton School at the University of Pennsylvania. Before PayPal, he contributed to quantitative finance and trading strategies at Spark Capital and held data science, risk, and loyalty analytics roles at American Express. His work spans product and technology leadership, quantitative finance, and building analytics capability across startups, enterprise settings, and global delivery centers.
+Avinash Karn is Senior Director of AI Strategy at PayPal, where he leads AI strategy and engineering within PayPal's central AI group and builds AI products, both customer-facing and internal, that shape how the company operates in the age of Agentic AI. His portfolio spans Business AI Transformation programs that tie AI investment to measurable business outcomes; Agentic Commerce, positioning PayPal as the economic operating system for the agent economy; an AI Fluency Index measuring enterprise adoption maturity; and foundational AI Research advancing PayPal's frontier AI capabilities. Avinash built the measurement science that gives leadership confidence in AI ROI. A first-principles, frameworks-driven leader, Avinash sits at PayPal's leadership table on AI positioning and competitive strategy, and shapes academic and industry dialogue across India on the future of AI-native enterprises.
 
-**Abstract**: Large language models have dramatically lowered the barrier to enterprise AI experimentation. Yet for most organizations, the real challenge is no longer experimentation but transformation. Moving from isolated pilots to AI-native operating models requires more than new tools; it demands new ways of working, new organizational capabilities, and new architectural foundations. Drawing from practical experiences at PayPal, this keynote explores how enterprises can scale AI adoption through a combination of workforce fluency, platform democratization, internal AI champions, and measurable organizational enablement. The talk will examine how AI initiatives were prioritized around business outcomes and productivity gains across finance operations, conversational platforms, workflow automation, and emerging agentic systems. The keynote will also discuss the technical and operational realities of deploying enterprise-scale AI in regulated environments, including orchestration frameworks, semantic caching, memory architectures, evaluation systems, governance, and production deployment considerations. Finally, the session will outline emerging patterns for the next generation of AI-native enterprises, where reusable AI capabilities evolve into foundational enterprise primitives, enabling organizations to move from AI-assisted work toward increasingly autonomous and adaptive operating models.
+**Abstract**: Large language models have lowered the barrier to enterprise AI experimentation, but for most organizations, the real challenge is now transformation, not experimentation. Moving from isolated pilots to AI-native operating models demands new ways of working, new organizational capabilities, and new architectural foundations. Drawing on practical experience at PayPal, this keynote explores scaling AI adoption through workforce fluency, platform democratization, internal AI champions, and measurable organizational enablement, and how initiatives were prioritized around business outcomes across finance operations, conversational platforms, workflow automation, and emerging agentic systems. The talk also covers the technical and operational realities of deploying enterprise-scale AI in regulated environments: orchestration frameworks, semantic caching, memory architectures, evaluation systems, governance, and production deployment, before outlining emerging patterns for AI-native enterprises, where reusable AI capabilities become foundational primitives that move organizations from AI-assisted work toward increasingly autonomous, adaptive operating models.
 
 ### Towards Trustworthy and Scalable Graph Foundation Models