Mackenzie is the Global Startup Evangelist at AWS. His days are spent traveling the globe to meet startups, share their stories, and connect engineering teams together. Every day there are a large number of startups launching on AWS across every imaginable industry. It’s Mackenzie’s mission to find stories of startups that are helping to improve the world and share these stories with a wide audience.
Join us for an evening with visionary AI founders and AWS leaders at the elegant Elsie Rooftop during New York Tech Week. This exclusive gathering features a cocktail reception and an engaging panel discussion exploring how the frontier is shifting from static models to continuously learning systems — where the real product isn't the model at launch, but the system's ability to improve in production. Connect with fellow innovators and executives for meaningful dialogue on building persistent learning loops, operationalizing AI improvement as a core product primitive, and why rate of learning is becoming the metric that defines winners — all while building lasting relationships in an exclusive setting.
The frontier is shifting from static models to continuously learning systems where the real product is not the model at launch, but the system’s ability to improve in production. This panel focuses on companies building persistent learning loops: capturing high-signal feedback, fine-tuning in near real-time, and compounding advantage through usage. Founders will share how they operationalize learning as a core product primitive, the VC will discuss why rate of improvement is becoming the key investment metric, and AWS will outline how infrastructure is evolving to support continuous training, evaluation, and deployment at scale.
Andrew Dai, Co-Founder & CEO of Elorian . Formerly Google Brain & DeepMind: developed foundational techniques underpinning modern large language models. First author of the 2015 work introducing LM pretraining followed by supervised fine-tuning. Co-led early mixture-of-experts models including GLaM; lead for Gemini data area and co-led pretraining for PaLM 2.
Roland Barcia is a Director at Amazon Web Services (AWS), leading the Specialist Technology Team (STT). With over 27 years of experience helping customers build and modernize systems, Roland leads a team building agentic AI tools, solutions, and platforms that empower AWS Specialists worldwide — including prototyping, Technical Field Communities, Specialist Engineering and Products. He is recognized for creating industry-leading architecture blueprints and driving enterprise cloud adoption at scale. A former IBM Fellow, Roland has authored 5 books, written over 50 articles, and holds a Master's Degree from NJIT.
Roger Murff brings more than 25 years of experience building and scaling software businesses to Lightspeed, where he supports over 300 portfolio companies with go-to-market strategy, ecosystem growth, and product partnerships. Roger was an executive at Databricks, where he was part of a team that grew the technology partner ecosystem from the ground up to over 500 partners representing 20% of total company revenue. Before that, he held leadership roles at AWS, Box, and Microsoft, helping startups and enterprises alike define new markets and scale from pre-revenue to IPO.
Amrita Sarkar is a mathematician, former VC, and AI ecosystem builder who leads North America Frontier AI Startup GTM at AWS, alongside global Healthcare & Life Sciences GTM initiatives. With a PhD in Computational Biology and 15 years spanning technology, venture capital, and deeptech, she partners with frontier AI founders, model builders, and investors to turn breakthrough research into enterprise adoption, strategic partnerships, and category-defining growth. Having lived and worked across Asia, Europe, and North America, she brings a global perspective on the evolution of AI and startup ecosystems.
