September 13, 2024

Computer History Museum

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AWS Community Day Bay Area

About AWS Community Day Bay Area

The power of cloud computing and digital technologies is reshaping the way we live, work, and interact with the world around us. To fully tap into this transformative potential, we need to join forces as a community to explore the latest trends, technologies, and best practices..

This Community Day, let's commit to deepening our understanding of the varied facets of AWS, sharing our insights, and exploring new ways to apply these technologies to address real-world challenges.

The AWS Community Day Bay Area features expert-led talks, technical workshops, hands-on labs, and networking opportunities with industry leaders and fellow enthusiasts from around the globe. Whether you're an experienced professional or a newcomer in the world of AWS, come join us. Be part of the movement to create a better, smarter, and more connected world.

Topics at the AWS Community Day Bay Area

Architecting for High Availability in AWS
Machine Learning on AWS: Tools and Real-World Applications
Deep Dive into Serverless Architecture with AWS Lambda
Securing Your Applications on AWS: An Overview of Key Services
Cost Optimization Strategies in AWS
Deploying Microservices on AWS: Containers vs. Kubernetes
Building and Deploying Serverless Applications with AWS Amplify
Embracing Infrastructure as Code with AWS CloudFormation and AWS CDK
Navigating the AWS Big Data Ecosystem: Engineering and Processing, Strategies
Building Resilient Applications with AWS Well-Architected Framework

KEYNOTE SPEAKER

Jeff Barr - Chief Evangelist at AWS

Jeff Barr - Chief Evangelist at AWS

Jeff Barr, the Vice President and Chief Evangelist for Amazon Web Services (AWS), is our keynote speaker. Known for his seminal blog posts and regular updates about AWS services, Jeff's insights have been instrumental in shaping the direction of the cloud industry. His ability to distill complex technologies into accessible content has made him a beacon for many in the field. Attendees will have the unique opportunity to meet and interact with him in this exclusive gathering. Don't miss this chance to learn from and network with Jeff Barr at our conference

DISTINGUISHED SPEAKERS

I want to be a speaker!
Principal Developer Advocate, AI & ML @ AWS.

Antje Barth

Principal Developer Advocate, AI & ML @ AWS.

Topic TBD

Antje works with AWS customers, helping them understand the benefits and capabilities of the AWS platform and advising them on best practices for developing and deploying cloud-based applications. Barth is also a popular speaker, author, and trainer, focusing on big data, analytics, and machine learning. Antje has authored multiple publications related to these topics, and she frequently presents at conferences and workshops.

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Transformative Technology Leader @ AWS

Arnab Sinha

Transformative Technology Leader @ AWS

Topic TBD

Given the excitement around Generative AI wanted to share AWS’s perspective on this topic. Amazon has been doing ML for over 20+ years and we see it everyday operations in our retail business, cloud services and the services we build. In this talk we will cover what generative AI is, its benefits and use cases. There are many questions we hear from our customers on how to best use AI in their business. In this talk we have identified 5 important considerations that customers can use to quickly build and deploy generative ai apps at scale. In addition, we will touch upon new services that customers can adopt to quickly choose from various LLMs available from leading startups, cost optimize their training and inference workload and increase developer productivity. The audience will leaving this talk knowing how to leverage AWS capabilities for their initiatives.

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Developer Relations @ AWS

Banjo Obayomi

Developer Relations @ AWS

Building Generative AI Applications with SageMaker Foundational Models

Discover the power of AWS SageMaker Jumpstart Notebooks in this hands-on workshop. Learn to deploy foundational models for text & image generation, integrate them with Lambda, and create a front-end application. Explore how to harness AI for building creative, scalable, and user-friendly solutions. No prior AI/ML experience required. You will be provided AWS Accounts

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Developer Advocate @ Twitch

Brandon Carroll

Developer Advocate @ Twitch

Protect your workloads against generative AI cyberthreats

Generative AI and natural language processing (NLP) AI models have been made available to the general public with ease of use and high levels of accuracy. While there are a myriad of potential benefits and benign uses for the technology, there are also many concerns about it’s use to develop malicious exploits and more effective cyberattacks. What does that mean for cybersecurity? And how can you defend against the misuse of Gen AI capabilities? In this workshop attendees will learn and build a working defense with AWS security services to combat the potential misuse of sophisticated Gen AI bot capabilities. .

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AWS Machine Learning Hero

Ed Miller

AWS Machine Learning Hero

Bear Necessities: Edge AI for Wildlife Conservation

Join us as we explore the exciting world of wildlife conservation through the lens of machine learning. Discover how the BearID Project is using advanced technology to monitor brown bears in their natural habitats. From training models on Amazon SageMaker to deploying them on edge devices using AWS IoT Greengrass and Arm's software defined camera framework, this talk promises to be a wild ride!

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Senior Enterprise SA @ AWS

Franklin Aguinaldo

Senior Enterprise SA @ AWS

Cost Optimization Strategies in AWS

This intro into cost optimization at AWS walks through the required change in mindset for working on the cloud. This talk focuses on the five pillars of cost optimization which is right-sizing, elasticity, pricing model, storage and mechanisms for cost optimization.

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Lead Data Scientist at SmugMug + Flickr

Geoff Ryder

Lead Data Scientist at SmugMug + Flickr

AI/ML Development on AWS - What Model Should I Use?

We represent data ops, data engineering, and data science on a two-pizza data team at SmugMug. Within our company, a unique contribution by our team is an AWS AI/ML sandbox, based on SageMaker. We'd like to show you how we put that together, and how other teams at the company use it. Highlights are structured access to the data lake, policy-driven control of compute sizes, and GenAI-enhanced data catalogs so our colleagues quickly understand the data they're working with. We will demo how to use the sandbox to train, evaluate, and start the process of deploying models. With the rise of so many great third-party AI models, a critical use case has become rapid internal benchmarking of new models against our own data, so we can decide which one is the best fit for our application.

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justingarrison

Justin Garrison

justingarrison

Fast, Scalable, and Efficient Kubernetes

We've all had to make trade-offs to implement a solution. But with modern Kubernetes a lot of the limitations of yesteryear have been overcome with new features and implementations. Justin will show you how to run Kubernetes clusters that can scale effortlessly, be highly utilized, and react fast to new requirements.

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Infrastructure Architecture Director @ Dolby Laboratories

Mike Graff

Infrastructure Architecture Director @ Dolby Laboratories

Leveraging Cost Categories to build AWS Chargeback reports

In this presentation, I will walk through Dolby's FinOps journey and how we migrated from using a third party reseller for our AWS Billing to bringing everything in house by leveraging AWS Cost Categories to build a simple cost allocation and chargeback solution for our organization. I will talk through the reasoning for the change, how we set it up, and what the benefits were for our company.

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Solutions Architect - ML and Environmental Sustainability @ AWS.

Parth Patel & Isha Dua

Solutions Architect - ML and Environmental Sustainability @ AWS.

Sustainable machine learning for protecting natural resources

"Climate change, pollution, and illegal harvesting endanger the health of forests and oceans worldwide. AWS customers are addressing these challenges by using large sets of natural resource data and AWS artificial intelligence and machine learning (AI/ML) services at the edge. As data increases in complexity and scale, optimization is essential to reducing the environmental impact of ML processing while accelerating analysis, modeling, and simulation. In this session, learn how organizations use AI/ML to predict and respond to environmental threats, and take away practical measures you can deploy to reduce the carbon footprint of your models at all steps of the ML lifecycle."

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Staff Machine Learning Engineer @ Instrumental

Rustem Feyzkhanov

Staff Machine Learning Engineer @ Instrumental

Building scalable end-to-end deep learning pipelines in the cloud.

Machine and deep learning became essential for a lot of companies for internal and external use. One of the main issues with its deployment is finding the right way to train and operationalize the model within the company. Serverless approach for deep learning provides simple, scalable, affordable and reliable architecture for it. My presentation will show how to do so within AWS infrastructure. Serverless architecture changes the rules of the game - instead of thinking about cluster management, scalability, and queue processing, you can now focus entirely on training the model. The downside within this approach is that you have to keep in mind certain limitations and how to organize training and deployment of your model in a right fashion. My presentation will show how to utilize services like AWS Batch, AWS Fargate, Amazon SageMaker, AWS Lambda, and AWS Step Functions to organize scalable deep learning pipelines."

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Big Data Developer @ AWS

Suman Debnath

Big Data Developer @ AWS

Running Spark on AWS in maintainable, reliable and cost-effective way

Running Apache Spark on Amazon Web Services (AWS) offers numerous advantages for processing large-scale data workloads. However, achieving optimal performance, cost-efficiency, and reliability requires careful planning and implementation. In this talk, we will delve into the ultimate guideline for running Spark on AWS in a maintainable, reliable, and cost-effective manner, with a focus on integrating AWS Glue and SageMaker. We will start by discussing the fundamental concepts of Spark, AWS Glue, and SageMaker, providing a solid foundation for understanding their integration. AWS Glue is a fully managed extract, transform, and load (ETL) service that simplifies data preparation tasks, while SageMaker provides a powerful platform for building, training, and deploying machine learning models. This will be a complete demo driven session, wherein we will spend entire time on the console/code.

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Developer Advocate @ Twitch

Todd Sharp

Developer Advocate @ Twitch

Creating Safer Online Communities by Using AI/ML for Live Stream Content Moderation

Live streaming is massively popular due to its interactive and unpredictable nature. But, the unpredictability means that sometimes less than desirable events can be live streamed and that offensive, insensitive chat messages are posted in chat messages during a live stream. Manual admin intervention can be used to prevent or stop offensive live streams and moderate inappropriate chat messages, but manual intervention isn't always 100% perfect. Automated moderation can help, but lacks the contextual awareness of the manual approach. The best approach is a healthy mix of manual and automatic moderation. In this session, we'll look at the various approaches to moderating a live stream and how they can be approved with the help of AI and ML. We'll look at how to analyze portions of a live stream for offensive or inappropriate content and use that analysis as a prompt for moderator intervention. We'll also look at how analyze chat messages for sentiment analysis and PII detection.

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Enterprise Product Development @ Arm

Tina Tsou

Enterprise Product Development @ Arm

Maximizing AI Efficiency on AWS: A Practical Guide to Leveraging Arm’sArchitecture

In this session, attendees will learn practical strategies to leverage the high-performance capabilities of AWS’s Arm-based Graviton2 processors for AI workloads. From understanding the underlying architecture to applying specific software optimizations, the session aims to provide actionable insights for developers and data scientists seeking to improve their AI workload performance on AWS.

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AGENDA

TimeSession Details
Morning Sessions
07:30 AM - 4:00 PM
Badge pick up, Assisted Registration, Information Desk - Grand Lobby
08:00 AM - 09:00 AM
1 hour
Breakfast and Networking - Grand Hall
09:00 AM - 09:20 AM
20 minutes
Welcome, Introductions and Sponsors Parade - John Varghese, AWS Hero - Hahn Auditorium
09:20 AM - 10:20 AM
1 hour
Keynote - Build your own luck - Jeff Barr - Chief Evangelist for AWS - Hahn Auditorium
10:20 AM - 10:50 AM
30 minutes
Tea/coffee break and Networking - Grand Hall Sponsored by AWS
Tracks
Hahn Auditorium
Lovelace
Boole
10:50 AM - 11:15 AM
25 minutes
Bear Necessities: Edge AI for Wildlife Conservation

--Ed Miller

Creating Safer Online Communities by Using AI/ML for Live Stream Content Moderation

--Todd Sharp

Fast, Scalable, and Efficient Kubernetes

--Justin Garrison

11:20 AM - 12:00 noon
40 minutes
Sustainable machine learning for protecting natural resources

--Parth Patel, Isha Dua

Protect your workloads against generative AI cyberthreats

--Brandon Carroll

Running Spark on AWS in maintainable, reliable and cost-effective way

--Suman Debnath

12:00 noon - 1:00 PM
1 hour
Lunch and Networking - Grand Hall SPONSORS WANTED!!
Post Lunch Sessions
Tracks
Hahn Auditorium
Lovelace
Boole
1:00 PM - 1:25 PM
25 minutes
Building scalable end-to-end deep learning pipelines in the cloud.

--Rustem Feyzkhanov

AWS GameDay:
Could extend to 90 or 100 minutes depending on your game play.


Building Generative AI Applications with SageMaker Foundational Models

--Banjo Obayomi

AI/ML Development on AWS - What Model Should I Use?

--Geoff Ryder

1:30 PM - 1:55 PM
25 minutes
Cost Optimization Strategies in AWS

--Franklin Aguinaldo

Maximizing AI Efficiency on AWS: A Practical Guide to Leveraging Arm’sArchitecture

--Tina Tsou

2:00 PM - 3:00 PM
Afternoon Tea break SPONSORS WANTED!!
Tracks
Hahn Auditorium
Lovelace
Boole
3:00 PM - 3:25 PM
Submit your proposal to talk at the conference

--Check the guidelines

Leveraging Cost Categories to build AWS Chargeback reports

--Mike Graff

Generative AI on AWS

--Arnab Sinha

3:30 PM - 3:55 PM
Panel Discussion at the Hahn Auditorium
3:55 PM - 4:15 PM
Raffle & Closing Note - Hahn Auditorium

VOLUNTEERS

Platinum Sponsors

AWS

AWS

Amazon Web Services (AWS) is the world's most comprehensive and broadly adopted cloud platform, offering over 200 fully featured services from data centers globally. Millions of customers—including the fastest-growing startups, largest enterprises, and leading government agencies—are using AWS to lower costs, become more agile, and innovate faster.

Gold Sponsors

Silver Sponsors

DNAnexus

DNAnexus

The world's most secure, trusted cloud platform and global network for scientific collaboration and accelerated discovery.

GitLab

GitLab

Software. Faster. GitLab is the most comprehensive AI-powered DevSecOps Platform.


COMMUNITY PARTNERS

AWS Bay AreaBay Area InfracodersPublice Cloud SecurityAdvanced AWSAWS East Bay Official EventsData Science on AWS

Venue

Computer History Museum

1401 N Shoreline Blvd,

Mountain View, CA 94043