How Visa Is Making Payments Safer and Smarter with AI - Ep. 256
Episode
22 min
Read time
2 min
Topics
Fundraising & VC, Design & UX, Artificial Intelligence
AI-Generated Summary
Key Takeaways
- ✓Virtual GPU optimization: Visa isolates memory and compute into separate virtual GPU instances on single cards, giving users one-tenth of a GPU instead of full allocation, dramatically improving cluster utilization while maintaining user experience for enterprises with limited cloud access.
- ✓Code modernization with GenAI: One engineer used GPT-4 to convert 50 legacy jobs from an unsupported programming language to Python in a single quarter, saving Visa $5 million by automating code translation that no internal staff could perform manually.
- ✓Ray Everywhere strategy: Visa adopted AnyScale's Ray ecosystem for the entire AI pipeline from data conditioning through model training to serving, creating a unified factory approach that accelerates model refresh cycles critical for staying ahead of evolving fraud tactics.
- ✓Privacy-preserving personalization: Visa creates high-quality consumer embeddings from trillions of transaction observations without exposing raw cardholder data, developing abstract representations that enable better product recommendations than competitors while maintaining strict privacy standards and regulatory compliance.
What It Covers
Sarah Laszlo, Senior Director of Visa's machine learning platform, explains how Visa leverages AI for fraud prevention, personalized cardholder experiences, and agentic commerce while managing petabyte-scale data in proprietary data centers.
Key Questions Answered
- •Virtual GPU optimization: Visa isolates memory and compute into separate virtual GPU instances on single cards, giving users one-tenth of a GPU instead of full allocation, dramatically improving cluster utilization while maintaining user experience for enterprises with limited cloud access.
- •Code modernization with GenAI: One engineer used GPT-4 to convert 50 legacy jobs from an unsupported programming language to Python in a single quarter, saving Visa $5 million by automating code translation that no internal staff could perform manually.
- •Ray Everywhere strategy: Visa adopted AnyScale's Ray ecosystem for the entire AI pipeline from data conditioning through model training to serving, creating a unified factory approach that accelerates model refresh cycles critical for staying ahead of evolving fraud tactics.
- •Privacy-preserving personalization: Visa creates high-quality consumer embeddings from trillions of transaction observations without exposing raw cardholder data, developing abstract representations that enable better product recommendations than competitors while maintaining strict privacy standards and regulatory compliance.
Notable Moment
Laszlo reveals Visa possesses a dataset rivaling Google's scale, with petabytes of transaction data providing consumer insights that even major tech companies cannot access, enabling uniquely powerful personalization models based on actual purchasing behavior rather than browsing history.
Episode Transcript
Hello, and welcome to the NVIDIA AI podcast. I'm your host, Noah Kravitz. AI's impact on the financial services industry has already been quite significant. From improving customer satisfaction and loyalty to streamlining operations and reducing costs, artificial intelligence is transforming an industry that's already been at the forefront of technology innovation for quite some time now. Visa is leading the way in leveraging AI to transform payment experiences. And with us to talk about how they're doing it is Sarah Laszlo. Sarah is senior director of Visa's machine learning platform, where she's architecting the infrastructure that will power Visa's future. Before joining Visa, Sarah well, her resume is really impressive and too long to get into right now, but I have to mention she was on NPR Science Friday, which is pretty cool. Sarah, welcome. Thank you so much for taking the time to join the AI podcast. Yes. Thank you so much. So before we get into all the stuff you're doing at Visa, all the stuff Visa's doing, would you tell us a little bit about your own journey, maybe how you got started in AI, and how you wound up in the role you're in now? Yeah. So, one thing that I always like to remind people of these days is that, of course, everybody thinks of artificial intelligence as something maybe that computer scientists do, but we need to remember that the back propagation paper that opened the field back up again after sort of the AI winter was, yes, Geoff Hinton was on there, but it was also coauthored by three psychologists, David Rumelhart. And I came up through that tradition of psychology. Oh, no kidding. Yeah. So my PhD is in psychology, and I became interested in computational neuroscience. There were many steps along the way Sure. Sure. Dot dot. Yeah. But now I still do it. Very cool. Did you practice as a psychologist? I was not ever a clinical psychologist or therapist. I was a cognitive neuroscientist. Right. So, you know, I worked with human research participants, but never in a therapeutic context. Got you. And so was computational neuroscience kind of your pathway leading to where you are now? Yeah. So, my postdoctoral adviser, David Plaut, was appointed in both psychology and computer science at Carnegie Mellon, and my academic grandfather in that line is Jeff Hinton. So Amazing. Most of the people who who were in that line and now do this. Right. Because that was sort of there were not that many people in 2009 that were doing deep learning. And so if you are one of those, you're one of the only, you know, 20 people that have fifteen years of deep learning experience. Totally. Totally. Incredible. I kind of hinted at it, and we don't want we wanna talk about what you're doing. How did you wind up with this role? Yeah. So I was working in responsible AI at Google, and I did that for …
Get the full transcript (4,462 words) + summary by email — free
One-time email with the complete transcript and AI summary of this episode. No account needed.
One email, no spam. We’ll also show you what SignalCast does.
You just read a 3-minute summary of a 19-minute episode.
Get NVIDIA AI Podcast summarized like this every Monday — plus up to 2 more podcasts, free.
Pick Your Podcasts — FreeKeep Reading
More from NVIDIA AI Podcast
Inside Instacart's AI-Powered Smart Shopping Cart | NVIDIA AI Podcast Ep. 302
Jun 24 · 39 min
The TWIML AI Podcast
How Capital One Delivers Multi-Agent Systems with Rashmi Shetty - #765
Apr 16
More from NVIDIA AI Podcast
How Mistral Is Building Frontier AI for the Enterprise | NVIDIA AI Podcast Ep. 301
Jun 10 · 21 min
The Pitch
#177 Aleoop: Show Me The Sales!
Feb 11
Books, tools, and gear mentioned in this episode
SignalCast may earn commission on purchases via these links.
Tools
by OpenAI
“One engineer used GPT-4 to convert 50 legacy jobs from an unsupported programming language to Python in a single quarter, saving Visa $5 million by automating code translation that no internal staff could perform manually.”
- RayRecommended
by Anyscale
“Visa adopted AnyScale's Ray ecosystem for the entire AI pipeline from data conditioning through model training to serving, creating a unified factory approach that accelerates model refresh cycles critical for staying ahead of evolving fraud tactics.”
More from NVIDIA AI Podcast
We summarize every new episode. Want them in your inbox?
Inside Instacart's AI-Powered Smart Shopping Cart | NVIDIA AI Podcast Ep. 302
How Mistral Is Building Frontier AI for the Enterprise | NVIDIA AI Podcast Ep. 301
Everyone Can Build a Robot: Open Source Embodied AI With Seeed Studio | NVIDIA AI Podcast Ep. 300
Inside AI Tokenomics: How to Profitably Turn Tokens Into Business Value | NVIDIA AI Podcast Ep. 299
Snap’s Secret to Processing 10 Petabytes a Day: GPU-Accelerated Spark | NVIDIA AI Podcast Ep. 298
Similar Episodes
Related episodes from other podcasts
The TWIML AI Podcast
Apr 16
How Capital One Delivers Multi-Agent Systems with Rashmi Shetty - #765
The Pitch
Feb 11
#177 Aleoop: Show Me The Sales!
Eye on AI
Nov 13
#300 Fred Laluyaux: How Decision Intelligence & AI Agents Are Redefining Enterprise Operations
Practical AI
Sep 3
Less about Models; More about Architecture
a16z Podcast
Aug 27
Inside Cursor: The Anatomy of a Generational Startup
Explore Related Topics
This podcast is featured in Best AI Podcasts (2026) — ranked and reviewed with AI summaries.
Read this week's AI & Machine Learning Podcast Insights — cross-podcast analysis updated weekly.
You're clearly into NVIDIA AI Podcast.
Every Monday, we deliver AI summaries of the latest episodes from NVIDIA AI Podcast and 192+ other podcasts. Free for one show.
Start My Monday DigestNo credit card · Unsubscribe anytime