Session Presentations
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Day 1
Innovation Slot 2: Accelerating Finance with NVIDIA Blackwell: Supermicro’s Next-Gen Infrastructure
• Highlighting high-performance, energy-efficient solutions with tailored end-to-end support, ideal for financial services like trading and fraud detection• Blackwell launch - NVIDIA HGX B200 8-GPU System: Showcase the air-cooled NVIDIA HGX B200, delivering scalable, cost-effective AI performance for financial workloads
• Demonstrate how Supermicro’s systems reduce latency and enhance efficiency in high-frequency trading and fraud detection
Innovation Slot 3: AI-Powered Document Processing in Banking and Finance
Financial institutions are increasingly implementing AI and machine learning to automate document extraction, classification, and analysis. While traditional OCR (Optical Character Recognition) was a foundational technology, today's solutions far exceed these limited capabilities, moving toward true cognitive automation.
Day 2
• Prepare and manage trusted data to unlock the full potential of AI in business operations.
• Focus on the most valuable AI opportunities that deliver measurable results.
• Develop skilled teams and robust infrastructures to scale AI across the organization.
• Embed fairness, explainability, and ethics into AI systems to maintain trust and accountability
• The evolution of AI agents in finance: From efficiency to revenue generation
• Quantitative results from collaborations with leading banks and financial institutions
• Enhanced accuracy and time reduction in M&A strategy, financial analysis, and credit assessment
• Practical implementation approaches tailored to New York market requirements
With the rapid rise of Generative AI (GAI), artificial intelligence has taken center stage for both businesses and regulators alike. As regulations proliferate, staying informed about AI legislative and policy developments across various jurisdictions has become critical.
Ideally, regulating AI should unlock its potential in a clear, risk-informed manner. But do these regulations achieve that goal? Or do they risk stifling innovation and hindering growth instead?
• What are the key challenges banks face in keeping up with the rapidly evolving landscape of AI regulations?
• How can Large Language Models (LLMs) be leveraged to streamline the process of comparing AI regulations?
• What are the specific benefits of using LLMs for regulatory compliance, particularly in terms of efficiency, accuracy, and insights gained?
• Identifying how LLMs are transforming the analysis of unstructured financial data
• How LLMs are enabling the development of innovative fintech product
• Reviewing the current NLP trends and latest SOTA algorithms Overview of the latest NLP algorithms and industry use cases that are easier to solve using the open-source NLP methods