NYC Agenda

Agenda

• 9:00 – 9:15a

  Welcome by Domino
• 9:15 – 9:45a

  Driving AI value at enterprise scale in 2024

  Nick Elprin CEO, Domino Data Lab

  Enterprises are ramping up AI across all areas. How do you meet high expectations without sacrificing budgets or responsible practices? Hear from Domino executives, industry experts, and thought leaders as they discuss the enterprise's path to AI success.
• 9:45 – 10:20a

  Changing the culture of AI

  Linda Avery Former CDAO The Federal Reserve, Verizon, co-founder Live Fire AI

  For AI to flourish and play a transformational role requires not just great technology, but also a well-functioning operating model that engages business leadership. Learn from an AI transformation expert on what makes the difference.
• 10:20 – 10:55a

  AI: What’s next? — GenAI and beyond

  John Thompson Global Head, Artificial Intelligence (AI) at EY

  AI has been used in commercial settings with great success for at least 20 years. GenAI exploded onto the scene about 2 years ago and shows no signs of slowing in innovation, adoption, and value realization.

  What does the next few years hold for us in relation to GenAI? What is next after GenAI? What does Causal AI look like and bring? And, finally what will composite AI applications composed of Traditional AI, GenAI, and Causal AI look like and bring to us?

  Come to this session, bring your questions and we will discuss these ideas and more. Your views and ideas are welcome. Let’s talk!
  
• 11:15 – 12:00p

  Computer Science 2.0 and what it means for finance

  Vijay Saraswat Head of Gen AI, Fidelity

  2020 marked the dawn of Computer Science 2.0: we now have a new kind of computer available that can accept instructions and data in text, and attempts to work with them as humans would. In terms of our ability to demonstrate how to perform complex, hitherto unimaginable, tasks in the real world, this marks a quantum leap in capabilities. However, the technology is fragile and raises new reliability issues – from an engineering point of view, it is extremely difficult to work with. Yes, we just discovered how to fly — and it is completely thrilling. Now how do we control this, to avoid crashing all the time?

  The AI product mindset: How Moody’s turned models into a service

  Logan Clark Associate Director, Moody's Analytics

  Over the last decade, Moody’s risk analysis services have emerged as a key part of our economic fabric. Powering this change is an analytics and AI product mindset. This enabled Moody’s to partner with customers to deliver trustworthy insights by combining customer data with decades of proprietary information. Hear how Moody’s was able to achieve that in our fireside chat with Associate Director Logan Clark.
• 12:00 – 1:00p

  Networking lunch
• 1:00 – 1:45p

  Data Science Track

  How FINRA IT drives AI-powered oversight at a colossal scale

  Ivan Black Director of Engineering, Delivery Services at FINRA

  FINRA is dedicated to protecting investors and safeguarding market integrity in a manner that facilitates vibrant capital markets. That translates into massive transaction data volumes to analyze against regulatory and operational frameworks. FINRA, nonetheless, overcomes this monumental challenge. Part of the answer is in its ability to harness AI/ML to scale its oversight. We are joined by FINRA’s Ivan Black, who will share with us the lessons his IT team learned from their epic AI enablement journey.

  
  

  IT Track

  Measure the economy in real-time, no ETL required

  Alex Izydorczyk CEO of Cybersyn

  Explore the potential of external data using real world case studies from the hedge fund industry.

  During this session, you will learn how to access data from 60+ public domain sources in a single location – including KPIs from SEC filings that are not readily available in a structured machine readable format.
• 2:00 – 2:45p

  Data Science Track

  Machine learning at scale

  Linan Qiu Head of AI and Machine Learning Engineering, Bridgewater Associates

  AIA Labs is an in-house venture at Bridgewater dedicated to developing and applying state-of-the-art AI & ML tools to generate returns in markets. The strategy requires machine learning training at scale. In a year we scaled from training thousands of models per run to nearly a million. Learn about why and how we scaled our compute.

  IT Track

  Operationalizing and scaling financial services AI in the real world

  Ken Gaume Data & Analytics Consulting Director, NTT Data

  Russell Fishman Global Head of Solutions Product Management, NetApp

  Financial services IT professionals supported AI initiatives for years now. Yet the emergence of genAI is increasing pressure from the top to deliver AI-based solutions throughout the institution.

  In this fireside chat, we are lucky to have banking IT veteran Ken Gaume share his deep perspective and 20 years of FSI experience. Ken will discuss how today’s challenges can become opportunities, what institutions need to sustain regulatory relationships, and how to efficiently support the most demanding emerging AI initiatives.
• 3:00 – 3:30

  Partner session with NVIDIA

  Malcom DeMayo Global VP, Financial Services, NVIDIA
• 3:30 – 4:00p

  It’s the End of the World as we Know It (with AI That’s Fine)

  Kjell Carlsson, Ph.D. Head of AI Strategy, Domino

  Roughly 100 years ago, the Wall Street crash led to the Great Depression and ultimately World War II. Today the conditions for economic catastrophe and geopolitical strife are far more obvious than they were then. Every major asset class is overvalued and debt to GDP ratios are at their highest levels during peacetime. Politicians across the spectrum are pursuing policies that increase protectionism and hurt the global economy.

  In this environment, how do we survive, thrive and maybe even prevent mass economic stagnation? AI (including ML) isn’t our best friend, it is our only friend. Only by accelerating innovation and adoption of AI can we unlock new sources of economic growth, build organizational resilience, and increase agility to changing economic conditions. Through AI we can develop the next generation of products and services, and augment our limited human intelligence that got us into this mess in the first place. We can tackle the biggest challenges humanity faces with AI – health, climate change, conflict. We just need to build our capabilities for innovating with AI, governing it and operationalizing it at scale.
• 4:00 – 6:00p

  Networking reception