Tune in to MLOps Workshops, hosted by:

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AWS Online Event: AI/ML for Startups

Thursday, November 4, 2021
9:00 AM PT - 2:45 PM PT | 12:00 PM ET - 5:45 PM ET

About the Event

Join us for AWS Online Event: AI/ML for Startups. During this virtual event, you’ll be able to explore natural language processing (NLP) models with AWS solutions architects, hear untold stories from founders of the world’s top startups about their massive scaling success, discover how to leverage cloud services, manage your data, and much more. You’ll also get a behind-the-scenes look into how to best use the individual tools and resources that AWS offers to support and expedite your company’s growth.


Event Agenda

Event Agenda

Moderator Introduction and Housekeeping


Speakers: Emily Webber, Machine Learning Specialist Solutions Architect, AWS | Neel Kishan, Business Development Manager AI/ML, AWS 

GPT-3, Wu Dao, Megatron-LM, Compositional Transformers and more. In this session we'll explore a variety of extreme scale NLP models and the distributed science and architecture that make them tick. In this session you'll learn about the newly launched distributed training toolkits on the AWS cloud and learn about how customers from Hyundai to Hugging Face are pushing the boundaries on transformer-based models. You'll learn about custom hardware AWS is developing to lower costs and boost performance. You'll also learn about how to partner with AWS to bring your unique technology to the enterprise cloud market!

Moderator: Ari Kalfayan, Senior Business Development Manager - AI/ML, AWS
Speakers: Tamás Görbe, PhD Co-founder and COO, Menten AI | Armen Kopoyan, Head of Sales, Grid.ai | Matthew Rocklin, CEO, Coiled Computing | Chris Van Pelt, Co-founder, Weights & Biases

Startups focused on artificial intelligence/machine learning (AI/ML) will face a variety of challenges as they begin building out their product to scale. Conditions must be right, and data centers are not a viable option. Instead, you must have a cloud provider in place to facilitate. 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 massive scaling 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.

Speaker: Rob Ferguson, Principal Business Development Manager - AI/ML, AWS

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.

Speakers: Sundar Ranganathan, Global Head of Business Development - ML Frameworks, AWS | Geeta Chauhan, PyTorch Partner Engineering Head, Facebook

PyTorch, the popular open-source ML framework, has continued to evolve rapidly since the introduction of PyTorch 1.0, which brought an accelerated workflow from research to production. We’ll deep dive into some of the most important new advances, including large scale distributed training, techniques for performance optimization, production scale deployments along with best practices for building Responsible AI solutions.

MLOps Workshops hosted by Tecton.ai, OctoML, Fiddler, Pachyderm, and Activeloop.

Speaker: Achal Shah, Software Engineer, Tecton.ai

Feature stores play a pivotal role in the modern machine learning stack. More and more data scientists and engineers are working together to create and manage features for both model training and for real-time inference. But how do you build, deploy, and use a feature store in the first place?In the tutorial, we will walk through a use case to build a real-time credit scoring application using Feast and AWS storage components: Redshift (offline store) and DynamoDB (online store). In particular, we will talk through how to:

• Create a training dataset as a loan table, which holds historical loan data with accompanying features, including a target variable: whether a user has defaulted on their loan.
• Demonstrate on-demand feature transformations
• Build a predictive model and use SageMaker for model experiments
• Serve real-time predictions with this model by using DynamoDB as the online feature store

Speaker: Phil Mazenett, Senior Solutions Engineer, OctoML

The 2021 Enterprise Trends in Machine Learning survey revealed that the cost of deploying ML to production is skyrocketing and that the time to deploy has increased year over year. This session is for organizations looking to evolve their ML deployment workflows and processes to accelerate time to production. Attendees will learn about new model performance optimization techniques and open source technologies. As well, they will get guidance on how to benchmark performance of optimized models across a variety of hardware options. Attendees will also take away strategies for automating manual steps in their deployment pipeline. And finally this workshop will cover actionable insight on how these approaches can be implemented to work with your existing AI/ML implementations on AWS.

Speakers: Amy Hodler, Lead Evangelist, Fiddler | Amal Iyer, Data Scientist, Fiddler

ML models tend to lose their predictive power over time and can fail silently. In this session, we’ll review how to identify and stay ahead of the common culprits: model drift, data integrity, outliers and bias. You’ll see how cutting-edge explainable AI and model analytics can quickly find the root cause of operational issues. And we’ll outline how model and cohort comparison help teams iterate and get new models in production faster.

We’ll demonstrate how leading enterprises on AWS are achieving trustworthy AI by integrating model performance management into their MLOps lifecycle, with Amazon SageMaker and AWS. You’ll walk away knowing how to use continuous ML monitoring and explainability to achieve optimal model performance and accelerate business outcomes.

Speaker: Jimmy Whitaker, Senior Machine Learning Developer and Developer Advocate, Pachyderm, Inc.

Natural language processing (NLP) is one of the most difficult areas in machine learning. Language is always changing because how we communicate is always changing. When it comes to machine learning our models are only as effective as the data they’ve been trained on. This is why any NLP task ultimately becomes an exercise in data-driven development.

Managing data for machine learning, however, has always been an afterthought. Tracking, versioning, and testing are usually introduced after it’s too late. In this workshop, we’ll show you how to manage your data, automate your training pipelines, and shift to a data-centered development process on a financial market sentiment model, and run it all deployed on AWS with EKS and S3.

In this workshop, attendees will learn how to:

• Train a market sentiment model
• Automate your NLP pipelines
• Shift to data driven development with Pachyderm and AWS

Speakers: Davit Buniatyan, CEO and Founder, Activeloop | Ivo Stranic, Head of Product, Activeloop

Learn how building a solid data foundation can help unlock the full potential of SageMaker and make training more accurate and cost-effective for computer vision models. In this session, we present Activeloop Hub - a simple, open-source API for transforming and streaming data while training models at scale. We discuss how adopting a dataset format specifically designed for AI allows for easy creation, storing, version-control and collaboration for CV datasets of any size. In addition, we present an instant way to visualize and explore your data. Overall, you will be able to adopt a radically simpler SageMaker experience - both for you, and your computer vision datasets.


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

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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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Venue


Join us for AWS Online Event: AI/ML for Startups

Thursday, November 4, 2021 | 9:00 AM PT - 2:45 PM PT | 12:00 PM ET - 5:45 PM ET

Session Proficiency Levels Explained

  • 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

  • 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

  • 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

  • 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

Why should I attend?

  • Discover how AWS technological tools can help you quickly and efficiently build and scale your business

  • Be privy to real-life advice and anecdotes from experienced engineers, business strategists, solutions architects, and analysts who have helped myriad businesses grow

  • Get in-depth answers to the questions you didn’t even know to ask and avoid potential stumbling blocks down the road

Who Should Attend

This event was created for founders who are looking to better understand and harness technology in order to scale their companies. Panels will offer information helpful for anyone in the early days of launching a business and be relevant to those interested in how AWS tools and resources can help nascent startups get off the ground.

Speakers

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    Emily Webber
    Machine Learning Specialist Solutions Architect, AWS

  • EV_aimlstartup-neelkishan_200x200_Nov-2021.jpeg

    Neel Kishan
    Business Development Manager AI/ML, AWS

  • Ari Kalfayan 200x200.png

    Ari Kalfayan
    Senior Business Development Manager - AI/ML, AWS

  • EV_aimlstartup-tamasgorbe_200x200_Nov-2021.jpeg

    Tamás Görbe, PhD
    Co-founder and COO, Menten AI

  • EV_aimlstartup-armenkopoyan_200x200_Nov-2021.png

    Armen Kopoyan
    Head of Sales, Grid.ai

  • EV_aimlstartup-robferguson_200x200_Nov-2021.jpeg

    Rob Ferguson
    Principal Business Development Manager - AI/ML, AWS

  • EV_aimlstartup-sundarranganathan_200x200_Nov-2021.png

    Sundar Ranganathan
    Global Head of Business Development - ML Frameworks, AWS

  • EV_aimlstartup-greetachauan_200x200_Nov-2021.jpeg

    Geeta Chauhan
    PyTorch Partner Engineering Head, Facebook

  • EV_aimlstartup-chrisvanpelt_200x200_Nov-2021.png

    Chris Van Pelt
    Co-founder, Weights & Biases

  • EV_aimlstartup-matthewrocklin_200x200_Nov-2021.png

    Matthew Rocklin
    CEO, Coiled Computing

  • 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

  • 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

Epic Logo Image

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

Yelp Logo Image

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.

Yelp

Airbnb Logo Image

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.

Airbnb

Lyft Image

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.

Lyft

FAQS


Q: Where is this event?

A: This a live online event, hosted by AWS.


Q: When is this event?

A: The event is scheduled for Thursday, November 4, 2021 from 9:00 AM PT - 2:45 PM PT | 12:00 PM ET - 5:45 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: This event will be relevant for anyone in the early stages of founding, building and growing a business.


Q: Why should I attend this event?

A: This event will be led by experienced engineers, architects, business strategist, and development managers who can help walk you through AWS tools, including SageMaker, PhTorch, Feast, and Pachyderm, to grow your business.


Q: What if I can’t attend the live event?

A: You should register to receive post-event on-demand slide decks and videos via email, even if you’re busy during the live event.