Welcome to the monthly in-person AI meetup in Chicago, in collaboration with AWS. Join us for deep dive tech talks on AI/ML, food/drink, networking with speakers and fellow developers

Agenda:
* 4:30pm~5:30pm: Checkin, Food/drink and Networking
* 5:30pm~5:40pm: Welcome/community update
* 5:40pm~7:30pm: Tech talks and Q&A
* 7:30pm: Open discussion and Mixer

Tech Talk 1: Churn Prediction & Customer Segmentation using GenAI and Graph Databases
Speakers: Puneet Rawal @AWS
Abstract: Learn how you can utilize AWS services like Amazon Neptune, Sagemaker to store, aggregate customer journey data and use real-time inference to predict churn using convolutional networks. We will also demonstrate how customer experience engineers can use natural language(LLMs) to segment customer data to reduce churn.

Tech Talk 2: Data Science Workbench for ML and GenAI Workloads Powered by AWS and NVIDIA
Speakers: Rahul Gupta (Discover) and Guillermo Tantachuco (AWS)
Abstract: Discover Financial Services has developed a homegrown data Science workbench for ML and Gen AI workloads powered by AWS and NVIDIA CUDA. Discover has used the NVIDIA GPU drivers with CUDA toolkits and EC2 to significantly speed up tasks like risk assessment, fraud detection, portfolio optimization, and accuracy in decision-making. The high performance and parallel processing power of GPUs enable us to analyze vast amounts of data quickly, leading to more informed and timely insights. EC2 powered by AWS play a very important role in this journey. These instances deliver high performance compute in the cloud. Amazon EC2 instances have been proven to reduce machine learning training times from days to minutes as well as increase the number of simulations completed for high performance computing up to 4x over CPU.

Tech Talk 3: Train and deploy foundation model like Stable Diffusion on AWS
Speakers: Kanwaljit Khurmi (AWS)
Abstract: Organizations that are running machine learning (ML) systems and generative AI applications on their local laptops/servers want to take advantage of the scalability and performance of the AWS Cloud. In this session, hear about compute and ML services from self-managed Amazon EC2 to fully managed Amazon SageMaker that you can use to build, train, and deploy foundation models. See a demo of how you can fine-tune a Stable Diffusion model on Amazon EC2 and then deploy it on Amazon SageMaker

Venue:
Amazon Web Services Inc.
227 W Monroe St #1400, Chicago, IL 60606 Google Map
How to find us: 14th floor. Government-issued ID is required for checkin.

Community on Slack/Discord
- Event chat: chat and connect with speakers and attendees
- Sharing blogs, events, job openings, projects collaborations
Join Slack (search and join the #chicago channel) | Join Discord