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Labelbox Accelerate 2021 Learn. Improve. Repeat.

Oct 20-21st, 8am - 11am PDT

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Join us on October 20th and 21st for our annual flagship event. Labelbox Accelerate offers a forum for the AI community to come together and discuss the opportunities and challenges associated with building an effective AI program. Learn how companies are utilizing AI to drive improved business results and gain practical insight on how to transform your own AI/ML operations.


At this event, you will:

Hear how organizations across different industries are configuring their ML Ops teams, designing workflows and gathering data on what’s working

Learn how to better incorporate automation techniques like Model Diagnostics and Model Assisted Labeling to improve efficiency

Get an in-depth look at what’s coming next from Labelbox


Speakers

  • Cathie Wood

    CEO/CIO, Ark Invest

    Read more

  • Admiral William F. Moran

    Retired, United States Navy

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  • George Hoyem

    Managing Partner, IQT

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  • Doug Philippone

    Head of Global Defense, Palantir Technologies

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  • Bryan Walsh

    Future Correspondent, Axios

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  • Ramanan Paramasivan

    R&D Director, Stryker

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  • Dr. Bernhard Kainz

    Associate Professor in the Department of Computing, Imperial College London

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  • Lars Roessler

    Venture Partner, BSH Startup Kitchen

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  • Anthony Jarc

    Director, Research and Data Science, Intuitive

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  • Arjun Adhikari

    Data Scientist, Blue River Technology

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  • Dr. Mark Wronkiewicz

    Data Scientist, NASA Jet Propulsion Laboratory

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  • Jake Lee

    Data Scientist, NASA Jet Propulsion Laboratory

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  • Miao Zhang

    AI Scientist, Early Clinical Development, Genentech

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  • Hong Noh

    Senior Product Manager, Criteo

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  • Matthew McAuley

    Senior Data Scientist, Allstate

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  • Steve Sobel

    Global Industry Leader - Communications, Media & Entertainment, Databricks

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  • Nirav Sheth

    Director-ISV & Partner Sales, Google Cloud Platform

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  • Miles Adkins

    Partner Sales Engineer, Snowflake

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  • Joel Gongora

    Customer Facing Data Scientist, DataRobot

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  • Manu Sharma

    CEO, Labelbox

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  • Dan Buczaczer

    CMO, Labelbox

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  • Audrey Smith

    Director of Labeling Operations, Labelbox

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  • David Liang

    Group Product Manager, Labelbox

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  • Lara Powollik

    Machine Learning Data Lead, Labelbox

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  • JT Vega

    Machine Learning Support Engineer Team Manager, Labelbox

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Agenda

October 20th and 21st (All times in PDT)
Day 1
October 20th

8:00-8:10

Welcome remarks

8:10-9:00

Keynote
Your competitive advantage should be data

With over 40 years of experience identifying and investing in innovation, ARK Invest CEO, Cathie Wood discusses what she believes it takes to win in AI with Labelbox CEO Manu Shama.

Speakers:
Cathie Wood, CEO/CIO, Ark Invest | Manu Sharma, CEO, Labelbox

9:00-9:40

Panel
Lessons learned from my first year with a training data platform

Learn how organizations are successfully moving from a proof of concept to large scale deployment of their ML programs utilizing a training data platform.

Speakers:
Hong Noh, Senior Product Manager, Criteo | Matthew McAuley, Senior Data Scientist, Allstate

9:40-9:50

Networking break

9:50-10:20

Case study
Blue River Technologies: Driving efficiencies with model-assisted labeling

Hear what drove Blue River Technologies to adopt model-assisted labeling, enabling them to achieve significant time and cost savings.

Speakers:
Arjun Adhikari, Data Scientist, Blue River Technologies
Product deep dive
Introduction to Labelbox

Learn more about the Labelbox platform through a live demo that showcases core functionalities including annotation tools and quality management features.

Speakers:
JT Vega, Lead Machine Learning Support Engineer, Labelbox
Partner sessions
Snowflake, Datarobot

Learn about the Labelbox Connector for Snowflake which enables users to easily annotate unstructured data and warehouse the results for data science use-cases in Snowflake.

Speakers:
Miles Adkins

Learn how to combine the model environment of DataRobot with the active learning of Labelbox to create and deploy your own Data Engine.

Speakers:
Joel Gongora

10:20-10:35

Product deep dive
Expanding our labeling platform: Labelbox updates

Join Group Product Manager David Liang to learn about recent and upcoming updates to our core labeling platform including support for more complex use cases based on video, text, and medical imagery data.

Speakers:
David Liang, Group Product Manager, Labelbox

10:35-11:00

Keynote
How the best achieve AI breakthroughs

Labelbox has seen how more than 200 organizations label, manage, and improve their training data. Come learn what sets apart those who move the fastest, realize the largest efficiencies, and find the greatest success in their ML programs.

We will announce the finalists for our first ever Breakthrough Customer Award.
Speakers:
Dan Buczaczer, CMO, Labelbox
Day 2
October 21st

8:00-8:10

Welcome remarks

8:10-9:00

Keynote panel
The need for strong ML capabilities in national security

A panel of experts discusses the responsibilities and challenges the US faces in the pursuit of building preeminent AI capabilities.

Speakers:
George Hoyem, Managing Partner, IQT | Doug Philippone, Global Defense Lead & Cofounder, Palantir/Snowpoint Venture | Bill Moran, Admiral, United States Navy | & Bryan Walsh, Correspondent, Axios

9:00-9:35

Case study
NASA JPL case study: Employing ML to find signs of life in our solar system

Mark Wronkiewicz and Jake Lee, both Data Scientists at NASA JPL, will share the story of how they developed an algorithm that helps scientists look for signs of extraterrestrial life. Learn why their ML team decided to invest in a training data platform after using disparate in-house tools for different use cases as well as best practices for managing non-technical labelers.

Speakers:
Mark Wronkiewicz, Data Scientist, NASA/JPL | Jake Lee, Data Scientist, NASA/JPL
Panel
Build vs Buy: Exploring the benefits of implementing a home-grown vs. external labeling solution

This panel dives into a question many ML teams consider: should they build their own labeling solutions or invest in a training data platform? Panelists will discuss tactics they used for creating and improving training data before a TDP, the decision to implement a TDP, and what has changed since implementation.

Speakers:
Lars Roessler, Head of BSH Startup Kitchen, BSH | Ramanan Paramasivan, Director R&D, Stryker

9:35-10:15

Panel
The role of nontechnical labelers in creating training data for specialized use cases

ML teams in specialized fields like medical imagery have long believed that creating high quality training data requires a labeling team with significant expertise and experience. However, an increasing number of companies as well as recent research has found they can achieve quality goals leveraging a workforce without deep technical experience while positively impacting time to market and cost.

Speakers:
Miao Zhang, AI Scientist, Early Clinical Development, Genentech | Bernhard Kainz, Senior Lecturer in the Department of Computing, Imperial College | Tony Jarc, Director, Research and Data Science, Intuitive Surgical
Product deep dive
How to optimize your labeling operations set up

We will discuss how Labelbox Workforce solutions can help you achieve both a time and cost savings. Learn more about the different solutions we offer and how to implement them in your current workflow.

Speakers:
Audrey Smith, Director of Labeling Operations, Labelbox | Lara Powollik, Machine Learning Data Lead, Labelbox
Partner sessions
Databricks, Google Cloud Platform

Data teams use Databricks and Apache Spark™ to analyze structured data, but may struggle to apply the same analysis to unstructured, unlabeled data. Learn how combining Databricks and Labelbox gives you an end-to-end environment for unstructured data workflows - a query engine built around Delta Lake, fast annotation tools, and a powerful machine learning environment.

Speakers:
Steve Sobel

Learn how Labelbox's partnership with GCP enables you to integrate Labelbox with BigQuery and store your assets in GCP.

Speakers:
Nirav Sheth

10:15-11:00

Product deep dive
Designing the optimal iteration loop

Learn how the latest generation of Labelbox products will redefine how you structure training data pipelines and help you label less data to achieve meaningful performance gains.

Speakers:
Manu Sharma, CEO, Labelbox