As quantum computing moves from experiment to early deployment, what’s needed to build a QC-readiness kit? Panelists will discuss how to separate hype from reality; identify the top questions you should ask potential QC suppliers; explore whether (or not) there are penalties for taking a wait-and-see attitude; and look at current and forecast spending plans in the quantum market. You’ll walk away with a better idea of what constitutes a thoughtful QC on-ramp in financial services.
Moderator: John Russell, Managing Editor, QCwire, HPCwire
Bob Sorensen Senior Vice President of Research, Chief Analyst for Quantum Computing, Hyperion Research
Heather West, PhD
Research Manager, Infrastructure Systems, Platforms, and Technologies, IDC
Jay Boisseau CEO & Co-founder, Vizias, Former HPC & AI Technology Strategist, Dell
GenAI and LLMs have caught many Financial Services Institutions off guard. In this session we will share the necessary steps required to “set the Quantum foundations” and reveal why, given the speed of evolution of our Quantum hardware, we believe the time to start is now. We will cover specific use cases relevant to the Financial Services industry and explain why all Quantum will be hybrid (a combination of Classical and Quantum) for the foreseeable future. Lastly, we’ll review the implications of preparing for the upcoming Quantum era.
Philip Farah VP Sales, Industries and Strategic Relationships, IonQ
There’s a lot of hype around quantum computing today, but to many it can seem an obscure technology perpetually relegated to the distant future. This session will provide an overview of quantum computing: what it is, how it works, and what it’s good for, with a focus on financial services. It will also outline some exciting new developments in QC that could bring useful quantum computing to the Financial Services industry.
Enrique Vargas, Head of Quantum Sales, Americas, IBM Quantum
High Performance Computing Track
High Performance Computing Overview: The State of HPC in 2023
HPC in financial services delivers faster understanding of complex data. Technology has enabled more advanced algorithms, including new disruptive formulas. With an increase in the cadence of technology releases, coupled with new technology vendors entering the infrastructure space, being aware and prepared is a challenge. If you’ve been wondering about how disaggregated, general-purpose computing might impact your next HPC/compute project, or are simply curious about near-term disruptive technologies, our fireside chat will discuss some of these technology changes, their challenges, and their extrapolated value for the financial services markets.
Ryan Quick Principal,Providentia Worldwide
Craig Yamasaki Senior Director of Product
The rapid and continuing rise of Generative AI (ChatGPT, Bard, and others) has pushed the demand for GPUs to unprecedented levels and created a “squeeze” on GPU availability. The prospect of extremely long lead times and prohibitive cost for GPUs may invite HPC users to seek more performance from the traditional (and available) CPUs and utilize GPUs available in the cloud. This panel will bring together industry leaders to discuss how HPC systems and the cloud can continue to provide users with high performance in the coming age of GPU scarcity.
Moderator: Doug Eadline, Managing Editor,HPCwire
Prabhu Ramamoorthy CFA, FRM, CAIA, Global Partner Success Manager, NVIDIA
Kiran Agrahara Cloud Solutions Architect, Intel
Wyatt Gorman Solutions Manager, HPC and AI Infrastructure, Google Cloud
Thomas Jorgensen Senior Director, Technology Enablement, Supermicro
In this fireside chat, Wall Street’s HPC legends, representing Citigroup, Goldman Sachs, JPMorgan Chase, and Morgan Stanley, come together to share their collective wisdom and experiences in large-scale Grid and HPC management. Delving into the past and present, they provide invaluable insights for navigating the evolving landscape of HPC, AI, Big Data, and Cloud technologies and the operational models required to support them at scale. Join us as they illuminate the path forward in a future where massive computational power, data, and the convergence of AI and Quantum computing promise to reshape the industry.
Moderator: Roman Chwyl, Managing Director Grid as a Service, IBM
Ty Panagoplos CEO, ParkWest Advisors, Former EVP & CIO Transformation, Santander US, CIO, TD Securities, and Executive Director, JPMorgan Chase Grid
J Ram Co-Founder, Concourse Labs, Former Managing Director, Goldman Sachs Grid and CTO/Executive Director, Morgan Stanley
Dino Vitale Distinguished Engineer, Infrastructure Tech Solutions Cloud Engineering, TD Bank Group, and former SVP Citigroup Grid and Director, Morgan Stanley Grid
The Holy Grail of Investing is to stay ahead of markets with real-time calculations as well as tapping into org sources, such as alternative data. With quantitative HPC + AI convergence, learn how financial firms are accelerating price discovery/risk for real-time exposures, as well as alternative data, with Gen AI NLP/LLM models from unstructured data to serve internal needs as well as those of their customers.
Prabhu Ramamoorthy, CFA, FRM, CAIA, Global Partner Success Manager, NVIDIA
Can a vendor’s value proposition be presented with only three slides in five minutes? Can they stand up to tough questioning from a seasoned industry analyst? Find out in this session as Dan Olds from Intersect360 Research moderates a select group of vendors giving short presentations and being made to answer three tough questions – one of which will be a complete surprise. This is a fast-moving and fun session which will get past the marketing-speak and uncover the real story behind the story.
Moderator: Dan Olds, Chief Research Officer, Intersect360 Research
SVP, Marketing, Hammerspace
Doug Norton Chief Marketing Officer, InspireSemi
Rob Glanzman Global Strategic Alliances Principal Architect, Financial Services, Pure Storage
Nick Ihli Director of Solutions Engineering and Cloud, SchedMD
Wednesday, September 27th | Data Management + AI
All times listed in EDT.
Data Management Track
Data Management Overview: The State of Big Data in 2023
Generative AI has taken the world by storm in 2023, and for good reason: the technology has the potential to be truly transformative for an enterprise. But no matter how advanced GenAI is, it suffers from the same data management challenges as any other form of advanced analytic or machine learning. In this session, we’ll take a look at the biggest data management challenges presenting themselves in 2023, as well as some of the technology, tools, and techniques that leading-edge companies are using to get beyond those challenges and realize the true potential of transformative GenAI.
High-performance computing applications, web-scale storage systems, and modern enterprises increasingly have the need for a data architecture that will unify data at the edge, as well as in data centers and clouds. These organizations with massive-scale data requirements need automated data orchestration coupled with the extreme high performance of a parallel file system and a standards-based solution that will be easy to deploy on machines with diverse security and build environments. In this session you will learn:
How to unify data created in different clusters and locations into a single namespace, and place locally to applications and compute for processing and AI
The latest technologies available to deliver parallel file system performance from data sets stored in a hybrid cloud environment
The latest in standards-based technologies available for data orchestration and storage at mass scale
How to secure data at a global level to ensure protection, governance, and access rights are maintained no matter where data is being used or stored
One of the highest priorities for many financial service institutions centers around digital modernization and a strategy/approach to enable machine learning and AI at enterprise level. This talk will help identify key challenges and considerations for leveraging the cloud when running AI/ML workloads, including AI vs. ML ecosystems, data management, ML/AI ops, and a discussion of the challenges and considerations of adopting generative AI Large Language Models (LLMs).
Dino Vitale, Distinguished Engineer, Infrastructure Technology Solutions Cloud Engineering Team, TD Bank Group
Artificial Intelligence Track
Artificial Intelligence Overview: The State of AI in 2023
There are many new challenges in delivering AI Factories at scale. The demand for large-scale GPU clusters is building, but a knowledge gap exists between what large enterprises are familiar with and what this new technology requires in order to design, build, deploy, and manage. The end result is usually poor performance and availability for a massive financial investment. This talk will discuss how to avoid some of those mistakes and how to get the maximum return on your AI Factory investment.
Troy Kaster, Vice President of Generative AI, Penguin Solutions
In the fintech domain, the integration of advanced Machine Learning (ML) methods encounters specific challenges due to regulatory requirements. It’s vital for ML implementations in this sector to be both transparent and ethically compliant. This presentation will cover:
Explainability of ML Models: Why simply having a powerful model isn’t enough, and the vital role of transparency and explainability in today’s finance landscape.
MLOps — Beyond the Buzzword: A deep dive into the methodology that’s revolutionizing model lifecycle management, making sense of the whirlwind from training to real-time monitoring.
Federated Learning: Delve into the world of decentralized ML, a beacon for data privacy, and its growing relevance in a world clamoring for data rights.
Case Studies: Engaging stories from the frontlines detailing the wins, pitfalls, and unexpected turns of AI/ML in regulatory scenarios.
Through the Regulator’s Lens: Gaining insights into the regulatory psyche, understanding their reservations, and aspirations for big data, AI, and ML in shaping the future of market regulation.
The Art & Science of Model Operationalization: Navigating the journey of models from the lab to the limelight, focusing on deployment nuances, version tales, and the balancing act between development and production stages.
Join us to gain comprehensive insights into the best practices for ML model management in the regulated FinTech landscape.
Sagar Gaikwad, Managing Director, Bucket Theorem,Former Head of Machine Learning Foundations, Capital One
Join industry leaders from Zilliz, NVIDIA Guardrail, and Databricks MosaicML as we delve deep into the evolving world of Large Language Models (LLMs) and Generative AI. While LLMs like ChatGPT have made headlines and are a hot topic of discussion, they’re just the tip of the iceberg. We’ll discuss:
What challenges are currently limiting the broader adoption of LLMs in enterprises?
Are there inherent risks or pitfalls in over-relying on AI-driven decision-making?
What infrastructural, data, and security considerations should technology leadership prioritize to ensure a mature AI strategy?
With AI continually advancing, how can organizations strike a balance between leveraging open-source solutions and third-party managed services?
Whether you’re an AI enthusiast or a FinServ professional grappling with AI’s potential in your domain, this discussion promises to provide valuable insights into the state and future of AI. Join us in unraveling the complexities and charting the course forward.
Moderator: Sagar Gaikwad, Managing Director, Bucket Theorem, Former Head of Machine Learning Foundations, Capital One
Ricardo Portilla Industry Principal, Databricks
Christopher Parisien Senior Manager of Applied Research, NVIDIA Guardrail
This discussion will focus on how the emergence of Generative AI has created new areas of focus for organizations to develop and utilize AI responsibly. Topics will include traditional risk in AI, new risks unique to Generative AI, emerging legislation, and how organizations are beginning to address these new challenges.
Traci Gusher,Americas Data and Analytics Leader, Ernst & Young
The Analyst Crossfire is a compelling and quick-moving panel discussion where some of the best and brightest minds in the industry discuss some of the most interesting and provocative topics in the industry today. Broken into four 15-minute segments, Dan Olds from Intersect360 Research will moderate and pose provocative questions covering the state of Quantum computing, the links between HPC, AI, and Wall Street, and how customers can tackle the enormous data management challenges posed by the advent of AI. The result will be an unscripted, spontaneous conversation that will dive into some of the most interesting topics today. You’ll hear some compelling arguments, and maybe even have a little fun along the way.
Moderator: Dan Olds, Chief Research Officer, Intersect360 Research
Chief Commercial Officer, Cornelis Networks
Alan Benjamin President and CEO, GigaIO
Troy Kaster Vice President of Generative AI, Penguin Solutions