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AWS Online Event: AI/ML for Startups
9:00 AM PT - 12:00 PM PT | 12:00 PM ET - 3:00 PM ET
Event Agenda
Introduction and housekeeping
9:00 AM - 9:15 AM PT
Confessions of AI/ML Startup Founders
9:15 AM - 9:55 AM PT
Panel: WhyLabs Co-founder & COO, Maria Karaivanova, Jaxon.AI CEO, Scott Cohen and WOMBO.ai Founder & CEO, Ben-Zion Benkhin
Startups focused on artificial intelligence/machine learning (AI/ML) will face a variety of challenges as they begin building out their product. To help learn from those who’ve done it before, we’ve gathered AI/ML founders from some of the world’s top startups to give a peek behind the scenes into the secrets of their own success. We’ll get the inside scoop on their untold stories and learn how they persevered through unexpected difficulties. You'll learn about common mistakes and get practical advice to help you navigate the challenges ahead.
Scaling your Startup: What to Expect when Building an ML Team
9:55 AM - 10:30 AM PT
Scaling up from a single engineer working off of their laptop to a dedicated team is an exciting milestone. But with growth comes growing pains. As you scale up your machine learning (ML) team, it's essential to leverage cloud services and tools just like you do for the rest of your development teams. Discover how to set up a data lake and implement it into an ML experiment workflow, how to prepare an end-to-end workflow to easily share the workload, and other tips for scaling your startup.
How to Accelerate your Models with Amazon SageMaker
10:30 AM - 11:00 AM PT
Machine learning (ML) can be a complex process for any size company. The lack of integration between workflow steps and tools not only makes it difficult, but time-consuming. That’s why startups use Amazon SageMaker to build, train, and deploy ML models. We'll dive deep into demonstrating SageMaker’s advanced features that help you train and iterate on your ML models faster. You'll learn techniques to transform your ML research project into a production-ready service.
Select the Right ML Instance for your Training and Inference Jobs
11:00 AM - 11:30 AM PT
In the past, accessing a graphic processing unit (GPU) to accelerate your data processing or scientific simulation code was difficult. Today, startups can log on to their AWS console and choose from a range of GPU-based Amazon EC2 instances on demand. Whether you're looking for a do-it-yourself or a fully managed approach, we'll show you how to choose the right instance on AWS to meet your target performance goals. You'll learn how to maximize resource utilization to find performance bottlenecks, and how to reduce overall training and inference costs.
Demystifying Kubernetes for ML Developers and Data Scientists
11:30 AM - 12:00 PM PT
Kubernetes has become an indispensable tool for scaling machine learning training and inference deployments to hundreds of instances for faster experimentation and to meet increasing customer demand. However, running and managing Kubernetes and Kubeflow environments can seem challenging for machine learning developers and data scientists. In this session, we'll introduce Kubernetes and containers technologies from a data scientist’s point of view. We’ll dive into why you need Kubernetes for machine learning, how to use Kubernetes and Kubeflow on AWS for large-scale training, hyperparameter optimization, model deployment, end-to-end pipeline orchestration, along with plenty of demos and examples geared towards the ML practitioner.
Conclusion and wrap-up
12:00 PM PT
Moderator closing remarks
Session Details
- Day 1
- Day 2
- Day 3
- Day 4
- Day 5
- Track6 Session 1
- Track7 Session 1
- Track8 Session 1
- Track9 Session 1
- Track10 Session 1
Day 1
Tab 1 content
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Day 2
Tab 2 content
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Day 3
Tab 3 content
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Day 4
Tab 4 content
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Day 5
Tab 5 content
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Track6 Session 1
Tab 6 content
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Track7 Session 1
Tab 7 content
Organizations today are looking to free themselves from the constraints of on-premises databases and leverage the power of fully managed databases in the cloud. Amazon RDS is a fully managed relational database service that you can use to run your choice of database engines including open source engines, Oracle, and SQL Server in the cloud. Amazon RDS automates time-consuming database administration tasks and adds capabilities such as replication and Multi-AZ failover to make your database deployments more scalable, available, reliable, manageable, and cost-effective. This session covers why you should consider moving your on-premises Oracle & SQL Server deployments to Amazon RDS and the tools to get started.
Track8 Session 1
Tab 8 content
Organizations today are looking to free themselves from the constraints of on-premises databases and leverage the power of fully managed databases in the cloud. Amazon RDS is a fully managed relational database service that you can use to run your choice of database engines including open source engines, Oracle, and SQL Server in the cloud. Amazon RDS automates time-consuming database administration tasks and adds capabilities such as replication and Multi-AZ failover to make your database deployments more scalable, available, reliable, manageable, and cost-effective. This session covers why you should consider moving your on-premises Oracle & SQL Server deployments to Amazon RDS and the tools to get started.
Track9 Session 1
Tab 9 content
Organizations today are looking to free themselves from the constraints of on-premises databases and leverage the power of fully managed databases in the cloud. Amazon RDS is a fully managed relational database service that you can use to run your choice of database engines including open source engines, Oracle, and SQL Server in the cloud. Amazon RDS automates time-consuming database administration tasks and adds capabilities such as replication and Multi-AZ failover to make your database deployments more scalable, available, reliable, manageable, and cost-effective. This session covers why you should consider moving your on-premises Oracle & SQL Server deployments to Amazon RDS and the tools to get started.
Track10 Session 1
Tab 10 content
Organizations today are looking to free themselves from the constraints of on-premises databases and leverage the power of fully managed databases in the cloud. Amazon RDS is a fully managed relational database service that you can use to run your choice of database engines including open source engines, Oracle, and SQL Server in the cloud. Amazon RDS automates time-consuming database administration tasks and adds capabilities such as replication and Multi-AZ failover to make your database deployments more scalable, available, reliable, manageable, and cost-effective. This session covers why you should consider moving your on-premises Oracle & SQL Server deployments to Amazon RDS and the tools to get started.
Multiple City Registration
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Join us for AWS Online Event: AI/ML for Startups
Session Proficiency Levels Explained
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Level 100
Introductory
Sessions will focus on providing an overview of AWS services and features, with the assumption that attendees are new to the topic
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Level 200
Intermediate
Sessions will focus on providing best practices, details of service features and demos with the assumption that attendees have introductory knowledge of the topics
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Level 300
Advanced
Sessions will dive deeper into the selected topic. Presenters assume that the audience has some familiarity with the topic, but may or may not have direct experience implementing a similar solution
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Level 400
Expert
Sessions are for attendees who are deeply familiar with the topic, have implemented a solution on their own already, and are comfortable with how the technology works across multiple services, architectures, and implementations
About the Event
Who Should Attend
Speakers
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Scott Cohen
CEO | Jaxon.AI -
Ben-Zion Benkhin
Founder & CEO | WOMBO.ai -
Haider Naqvi
Senior Solutions Architect | AWS -
Shashank Prasanna
AI/ML Developer Advocate | AWS -
Rob Ferguson
Principal Business Development Manager - AI/ML | AWS -
Ari Kalfayan
Senior Business Development Manager - AI/ML | AWS -
Maria Karaivanova
Co-founder & COO | WhyLabs -
Ryan Kelly, Data Architect, Equinox
Ryan Kelly is a data architect at Equinox, where he helps outline and implement frameworks for data initiatives. He also leads clickstream tracking which helps aid teams with insights on their digital initiatives. Ryan loves making it easier for people to reach and ingest their data for the purposes of business intelligence, analytics, and product/service enrichment. He also loves exploring and vetting new technologies to see how they can enhance what they do at Equinox
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Richard Boyd, Cloud Data Engineer, iRobot
Richard Boyd is a cloud data engineer with the iRobot Corporation’s Cloud Data Platform where he builds tools and services to support the world’s most beloved vacuum cleaner. Before joining iRobot, Richard built discrete event simulators for Amazon’s automated fulfillment centers in Amazon Robotics. His previous roles include cyber warfare systems analyst at MIT and research for the Center for Army Analysis. He holds advanced degrees in Applied Mathematics & Statistics.
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Raju Gulabani, VP of Databases, Analytics & AI, AWS
Raju Gulabani is VP of Databases, Analytics & AI within AWS at Amazon.com. He is responsible for P&<, product management, engineering and operations for Database services such as Amazon Aurora and Amazon DynamoDB, and Analytics services such as Amazon Redshift and Amazon EMR, as well as AI services like Amazon Lex, Amazon Polly, and Amazon Rekognition. Prior to joining Amazon in his current position in 2010, Raju spent four years at Google and built the Google Apps business (now known as G Suite).Earlier in his career, Raju founded an Intel backed Wi-Fi Voice over IP company as well as held engineering management positions at Microsoft.
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Ryan Kelly, Data Architect, Equinox
Ryan Kelly is a data architect at Equinox, where he helps outline and implement frameworks for data initiatives. He also leads clickstream tracking which helps aid teams with insights on their digital initiatives. Ryan loves making it easier for people to reach and ingest their data for the purposes of business intelligence, analytics, and product/service enrichment. He also loves exploring and vetting new technologies to see how they can enhance what they do at Equinox
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Richard Boyd, Cloud Data Engineer, iRobot
Richard Boyd is a cloud data engineer with the iRobot Corporation’s Cloud Data Platform where he builds tools and services to support the world’s most beloved vacuum cleaner. Before joining iRobot, Richard built discrete event simulators for Amazon’s automated fulfillment centers in Amazon Robotics. His previous roles include cyber warfare systems analyst at MIT and research for the Center for Army Analysis. He holds advanced degrees in Applied Mathematics & Statistics.
Customer Highlights
Epics Games’ entire analytics platform runs on AWS. Billions of game events, like player interactions on the map, their accuracy, damage taken and dealt, and what resources they are using are all sent to AWS.
Epics Games’ entire analytics platform runs on AWS. Billions of game events, like player interactions on the map, their accuracy, damage taken and dealt, and what resources they are using are all sent to AWS.
Epics Games’ entire analytics platform runs on AWS. Billions of game events, like player interactions on the map, their accuracy, damage taken and dealt, and what resources they are using are all sent to AWS.
Epics Games’ entire analytics platform runs on AWS. Billions of game events, like player interactions on the map, their accuracy, damage taken and dealt, and what resources they are using are all sent to AWS.
FAQS
Q: Where is this event?
A: This a live online event, hosted by AWS.
Q: When is this event?
A: This is a half-day event, scheduled for Thursday, May 6, 2021 | 9:00 AM PT - 12:00 PM PT | 12:00 PM ET - 3:00 PM ET.
Q: How much does it cost to attend?
A: There is no cost to attend this event.
Q: Who should attend this event?
A: Startup founders and technical decision-makers who are looking to build out their cloud infrastructure to enable powerful, cost-effective, and scalable artificial intelligence.
Q: Why should I attend this event?
A: This free, online event will teach you about the AWS products and solutions to help your startup build fast, powerful, and cost-effective AI/ML models. Plus get business tips from AI/ML startup founders about how to source and manage a top-tier AI/ML data science team.
Q: What if I can’t attend the live event?
A: You’ll miss out on our live Q&A and polling, but don’t worry, you can still access the event sessions on-demand. Even if you can’t attend live, register to receive an email notification about the on-demand recordings.