Celebrate over 20 years of AI/ML at Innovation Day

Be our guest as we celebrate 20 years of AI/ML innovation on October 25, 2022, 9:00 AM – 10:30 AM PT.  The first 1,500 people to register will receive $50 of AWS credits. Register here.

Over the past 20 years, Amazon has delivered many world firsts for artificial intelligence (AI) and machine learning (ML). ML is an integral part of Amazon and is used for everything from applying personalization models at checkout, to forecasting the demand for products globally, to creating autonomous flight for Amazon Prime Air drones, to natural language processing (NLP) on Alexa. And the use of ML isn’t slowing down anytime soon, because ML helps Amazon exceed customer expectations for convenience, cost, and delivery speed.

During the virtual AI/ML innovation event on October 25, we take time to reflect on what’s been done at Amazon and how we have packaged this innovation into a wide breadth and depth of AI/ML services. The AWS ML stack helps you rapidly innovate and enhance customer experiences, enable faster and better decision-making, and optimize business processes using the same technology that Amazon uses every day. With the most experience; the most reliable, scalable, and secure cloud; and the most comprehensive set of services and solutions, AWS is the best place to unlock value from your data and turn it into insight.

We will also take a moment to celebrate customer success using AWS to harness the power of data with ML and, in many cases, change the way we live for the better. Mueller Water Products, Siemens Energy, Inspire, and ResMed will show what’s possible using ML for sustainability and accessibility challenges such as water conservation, predictive maintenance for industrial plants, personalized medical care resources for patients and caregivers, and cloud-connected customized recommendations for patients and their healthcare providers.

The 90-minute session doesn’t stop there! We have special guest speaker Professor Michael Jordan, who will talk about the decision-making side of ML spanning computational, inferential, and economic perspectives. Much of the recent focus in ML has been on the pattern recognition side of the field. In Professor Jordan’s talk, he will focus on the decision-making side, where many fundamental challenges remain. Some are statistical in nature, including the challenges associated with multiple decision-making. Others are economic, involving learning systems that must cope with scarcity, competition, and incentives, and some are algorithmic, including the challenge of coordinated decision-making on distributed platforms and the need for algorithms to converge to equilibria rather than optima. He will ponder how next-generation ML platforms can provide environments that support this kind of large scale, dynamic, data-aware, and market-aware decision-making.

Finally, we wrap up the celebration with Dr. Bratin Saha, VP of AI/ML, who will explain how AWS AI/ML has grown to over 100,000 customers so quickly, including how Amazon SageMaker became one of the fastest growing services in the history of AWS. Hint—SageMaker incorporates many world firsts, including fully managed infrastructure, tools such IDEs and feature stores, workflows, AutoML, and no-code capabilities.

AWS has helped foster ML growth through capabilities that help you deploy it at scale by operationalizing processes. We have seen this play out in many different industries. For example, in the automotive industry, the assembly line has standardized automotive design and manufacturing, and launched a revolution in transportation by helping us transition from hand-assembled cars to mass production.

Similarly, the software industry went from a few specialized business applications to becoming ubiquitous in every aspect of our lives. That happened through automation, tooling, and implementing and standardizing processes—in effect through the industrialization of software. In the same way, ML services from AWS are driving this transformation. In fact, customers today are running millions of models, billons of parameters, and hundreds of billions of predictions on AWS.

Dr. Saha will also look back at the history of flagship AI services, including services for text and documents, speech, vision, healthcare, industrial, search, business processes, and DevOps. He will explain how to use the AI Use Case Explorer, where you can explore use cases, discover customer success stories, and mobilize your team around the power of AI and ML. Dr. Saha will end on his vision for AWS AI/ML services.

We can’t wait to celebrate with you, so register now! If you’re among the first 1,500 people to register, you will receive $50 of AWS credits.

Happy innovating!

About the author

Kimberly Madia is a Principal Product Marketing Manager with AWS Machine Learning. Her goal is to make it easy for customers to build, train, and deploy machine learning models using Amazon SageMaker. For fun outside work, Kimberly likes to cook, read, and run on the San Francisco Bay Trail.