Today we're joined by Alex Smola, Vice President and Distinguished Scientist at AWS AI.
We had the pleasure to catch up with Alex prior to the upcoming AWS Machine Learning Summit, and we covered a TON of ground in the conversation. We start by focusing on his research in the domain of deep learning on graphs, including a few examples showcasing its function, and an interesting discussion around the relationship between large language models and graphs. Next up, we discuss their focus on AutoML research and how it's the key to lowering the barrier of entry for machine learning research.
Alex also shares a bit about his work on causality and causal modeling, introducing us to the concept of Granger causality. Finally, we talk about the aforementioned ML Summit, it's exponential growth since its inception a few years ago, and what speakers he's most excited about hearing from.
You know AWS as a cloud computing technology leader, but did you realize the company offers a broad array of services and infrastructure at all three layers of the machine learning technology stack. In fact, tens of thousands of customers trust AWS for machine learning and artificial intelligence services, and the company aims to put ML in the hands of every practitioner with innovative services like Amazon CodeWhisperer, a new ML-powered pair programming tool that helps developers improve productivity by significantly reducing the time to build software applications.
To learn more about AWS ML and AI services, and how they’re helping customers accelerate their machine learning journeys, visit twimlai.com/go/awsml.