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Date: Tuesday, January 12, 2021
Time: 8:00am – 9:00am PT
Duration: 1 hour

Traders, whether human or algorithmic, need to adapt to the changing data science landscape. The growing capability of AI, coupled with the increase in available data, mean that firms without an AI strategy will soon be left behind. Discretionary traders who don’t augment their human traders with teams of AI assistants will find themselves trailing the performance of their more data-savvy peers. And systematic traders will find themselves faced with a dual challenge—the amount of data they need for AI and machine learning algorithm development and the accelerated intelligence they need to optimize trading within a target window. The shorter the window, the more challenging it is to execute large AI-driven models.

In this webinar, we’ll share what we’re seeing around augmenting traders and algorithms and the challenges with squeezing more intelligence into ever shorter time windows.

By attending this webinar, you’ll learn:

  • Why trading firms need an AI strategy to survive
  • How the data science landscape is changing financial trading
  • The biggest challenges (and opportunities) to augment traders with AI-driven models
Join us after the presentation for a live Q&A session.



You will receive an email with instructions on how to join the webinar shortly.

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John Ashley

General Manager, Financial Services and Technology, NVIDIA

John Ashley leads the Global Financial Services and Technology team at NVIDIA. His team focuses on global trends and directions in accelerated compute and AI for the entire sector—from hedge funds, fintech, and banking to insurance. NVIDIA supports customers and partners in their adoption of accelerated computing and AI and machine learning techniques to improve time to insight, enable expanded analytics around risk and fraud, and dive deep into customer data to address key business problems. He also started and led the Professional Services Deep Learning Practice for NVIDIA and the NVIDIA Deep Learning Professional Services Partner program, managed the relationship with IBM’s Software and Cognitive Solutions groups, was a senior solutions architect for financial services in New York and London, and supported NVIDIA’s work with the Square Kilometer Array radio astronomy programs. He holds a doctorate in computational sciences and informatics and BS and MS degrees in electrical engineering. His past work experience can best be described as varied—he has been a data scientist, project manager, systems architect, database administrator, and developer and has worked in vendor, consulting, and end-user firms in utilities, government, and finance. He holds a U.S. patent in predictive analytics.

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Webinar: Description here

Date & Time: Wednesday, April 22, 2018