Innovate faster with the most comprehensive set of AI/ML services
Watch these post-event recorded sessions - all about artificial intelligence, machine learning, and data. You’ll learn about the most cutting-edge machine learning tools, gain strategies to build future-proof applications, and bring more organization to your data-driven organization.

Becoming a data-driven organization
Developing a data-driven culture requires a mindset shift. Learn from AWS customer examples and Amazon itself about how to address these challenges and transform your data into a strategic asset.

Building a smarter organization: Powered by machine learning
In this session, tailored to business leaders, AWS Enterprise Strategists share how organizations can embrace AI/ML, along with stories on how some customers use them to achieve profound results.

How AWS Trainium and AWS Inferentia help train and deploy 100B+ parameter models at scale

Use cases for maximizing business value from data
Many organizations are sitting on a treasure trove of data but don’t know how to get value out of it. In this session you will learn how AWS enables leading use cases of putting data to work.

Solve common business problems with AWS AI/ML services
In this session, learn how companies across industries are using artificial intelligence (AI) to address use cases that create measurable results.

Carrier’s data-led path to sustainable buildings and cold chain solutions
Carrier’s CDO Bobby George and AWS Enterprise Strategist John Clark talk about earning buy-in for data transformation, evolving a data-centric culture, and how data strategy relates to sustainability.

Accelerate business growth with personalized user experiences
In this session, learn how the simple integration of Amazon Personalize into your existing websites and marketing systems can create high-value personalization at every touchpoint.

Deliver high accuracy and efficiency with intelligent document processing
Many organizations have a fragile or inadequate document processing pipeline. In this session, learn how to take advantage of AWS’s latest innovations in AI and ML to process documents efficiently.

Transform your existing contact center with Conversational AI and Call Analytics
In this session, you will learn about AWS Contact Center Intelligence (CCI) and Conversational AI solutions and how to integrate them into your preferred contact center solution.

Natural language powered chatbots with Amazon Kendra & Amazon Lex
In this session, we will share how AI services like Amazon Kendra and Amazon Lex can help you build conversational interfaces into any application quickly, with no machine learning expertise required.

Unlock AI/ML-powered customer experience improvements with Amazon Connect
In this session, hear how Amazon Connect unlocks AI/ML-powered innovation that offers personalized digital experiences, improved agent productivity, and captures business insights.

Enable predictive maintenance for industrial equipment with machine learning
Join this session on predictive maintenance to learn how to prevent downtime in industrial machinery by automatically detecting abnormal behavior and proactively acting on potential failures.

Building, training, and deploying a movie recommendation engine
In this session, learn how startup Vale partnered with ClearScale to use modern AI/ML technology to create a new platform for watching movies and TV shows through its Streaming Guide application.

Accelerate your ML journey with Amazon SageMaker low-code tools
The ML journey requires experimentation. In this session, learn how tools like Amazon SageMaker allow you to experiment faster so you can focus more on refining predictions and less on low-level code.

Productionize ML workloads using Amazon SageMaker MLOps
In this session, explore Amazon SageMaker machine learning operations (MLOps) features and learn how to increase automation and improve the quality of your ML workflows.

Boost ML development productivity with managed SageMaker notebooks in the cloud
Join this session to learn how to increase productivity with SageMaker Studio notebook capabilities, from simplified data preparation to automatic conversion of notebook code to production-ready jobs.

Train ML models at scale with Amazon SageMaker
In this session, learn how Amazon SageMaker reduces the time and cost to train and tune large-scale machine learning models without the need to manage infrastructure.

Deploy ML models for inference at high performance and low cost
High-performance, cost-effective model deployment is critical to ML return on investment. In this session, learn how to use Amazon SageMaker’s inference abilities to quickly deploy ML models at scale.

Practical decision-making using no-code ML
Organizations everywhere are using ML to accurately predict outcomes. In this session, you will learn how to use Amazon SageMaker Canvas for cases across sales, marketing, finance, and operations.
