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Labelbox Accelerate 2021

Learn. Improve. Repeat.

Access every session from our annual flagship event. Labelbox Accelerate is a forum for data practitioners and leaders to discuss the best practices associated with building an effective AI program. Become a better AI builder by learning from the world’s top AI and machine learning experts today. Learn more about Labelbox here.


Photo of Manu Sharma
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.


Cathie Wood: CEO/CIO, Ark Invest

Manu Sharma: CEO, Labelbox

Photo of Dan Buczaczer
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.


Dan Buczaczer: CMO, Labelbox

George Hoyem's photograph
Photo of Doug Philippone
Photo of Bryan Walsh
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.


George Hoyem: Managing Partner, IQT

Doug Philippone: Head of Global Defense, Palantir Technologies

Admiral William F. Moran: Retired, United States Navy

Bryan Walsh: Future Correspondent, Axios

Case studies

Photo of Arjun Adhikari
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.


Arjun Adhikari: Data Scientist, Blue River Technology

Photo of Dr. Mark Wronkiewicz
Photo of Jake Lee
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.


Dr. Mark Wronkiewicz: Data Scientist, NASA Jet Propulsion Laboratory

Jake Lee: Data Scientist, NASA Jet Propulsion Laboratory


Photo of Hong Noh
Photo of Matthew McAuley
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.


Hong Noh: Senior Product Manager, Criteo

Matthew McAuley: Senior Data Scientist, Allstate

Photo of Lars Roessler
Photo of Ramanan Paramasivan
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.


Lars Roessler: Venture Partner, BSH Startup Kitchen

Ramanan Paramasivan: R&D Director, Stryker

Partner sessions

Photo of Miles Adkins

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.


Miles Adkins: Partner Sales Engineer, Snowflake

Photo of Joel Gongora

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


Joel Gongora: Customer Facing Data Scientist, DataRobot

Photo of Steve Sobel

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.


Steve Sobel: Global Industry Leader - Communications, Media & Entertainment, Databricks

Photo of Nirav Sheth
Google Cloud Platform

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


Nirav Sheth: Director-ISV & Partner Sales, Google Cloud Platform

Product deep dives

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Introduction to Labelbox

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


JT Vega: Machine Learning Support Engineer Team Manager, Labelbox

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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.


David Liang: Group Product Manager, Labelbox

Photo of Audrey Smith
Photo of Lara Powollik
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.


Audrey Smith: Director of Labeling Operations, Labelbox

Lara Powollik: Machine Learning Data Lead, Labelbox

Photo of Manu Sharma
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.


Manu Sharma: CEO, Labelbox


  • Cathie Wood

    CEO/CIO, Ark Invest

    Read more

  • Admiral William F. Moran

    Retired, United States Navy

    Read more

  • George Hoyem

    Managing Partner, IQT

    Read more

  • Doug Philippone

    Head of Global Defense, Palantir Technologies

    Read more

  • Bryan Walsh

    Future Correspondent, Axios

    Read more

  • Ramanan Paramasivan

    R&D Director, Stryker

    Read more

  • Dr. Bernhard Kainz

    Associate Professor in the Department of Computing, Imperial College London

    Read more

  • Lars Roessler

    Venture Partner, BSH Startup Kitchen

    Read more

  • Anthony Jarc

    Director, Intuitive

    Read more

  • Arjun Adhikari

    Data Scientist, Blue River Technology

    Read more

  • Dr. Mark Wronkiewicz

    Data Scientist, NASA Jet Propulsion Laboratory

    Read more

  • Jake Lee

    Data Scientist, NASA Jet Propulsion Laboratory
  • Miao Zhang

    AI Scientist, Genentech

    Read more

  • Hong Noh

    Senior Product Manager, Criteo

    Read more

  • Matthew McAuley

    Senior Data Scientist, Allstate

    Read more

  • Steve Sobel

    Global Industry Leader - Communications, Media & Entertainment, Databricks

    Read more

  • Nirav Sheth

    Director-ISV & Partner Sales, Google Cloud Platform

    Read more

  • Miles Adkins

    Partner Sales Engineer, Snowflake

    Read more

  • Joel Gongora

    Customer Facing Data Scientist, DataRobot

    Read more

  • Manu Sharma

    CEO, Labelbox

    Read more

  • Dan Buczaczer

    CMO, Labelbox

    Read more

  • Audrey Smith

    Director of Labeling Operations, Labelbox

    Read more

  • David Liang

    Group Product Manager, Labelbox

    Read more

  • Lara Powollik

    Machine Learning Data Lead, Labelbox

    Read more

  • JT Vega

    Machine Learning Support Engineer Team Manager, Labelbox

    Read more