synthesize 2023

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The Developer Conference for Synthetic Data

Learn from experts how AI and the evolution of synthetic data are profoundly impacting how we access, share, and build with data.
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Featuring speakers and researchers in AI, ML, and data science from startups, companies, and research institutions.

GooglegretelhumuIlluminaLiltMunich RENeverNvidiaRemitlyRiot GamesRocheSnowflakeStanford UniversitySwiggyUnityUS Department of Defense

Join us for the online conference on Wednesday, Feb 8, 2023, and be part of what comes next in data and AI. Each session is delivered by tech innovators and business leaders using the latest advancements in synthetic data to solve some of the world’s greatest challenges with data.

A Stable Diffusion image of a man riding a motorcycle
Explore
real-world applications for state-of-the-art generative text, tabular, image, video, audio, and simulation-based AI models. Discover new possibilities for building responsible, data-driven AI.
Stylized DNA helix
Learn
ideas and inspire conversations with other researchers, data scientists, and data engineers. Get tips from experts doing groundbreaking work with synthetic data from companies including Illumina, Riot Games, and Gretel.ai.
Stylized render of a CPU generating data
Generate
data through hands-on workshops and live collaborations with other developers in the new Synthetic Data Community. Learn foundational concepts of synthetic generation and how synthetic data fits into the ecosystem of various ML and AI tools and solutions.

Why Synthetic Data?

Synthetic data is information that is generated by AI models or simulations. It is increasingly being used as a replacement for sensitive real-world data.
Accurate – train high-performing production-ready AI and ML models.

Private – mathematically provable privacy makes it easy to share data.

Scalable – unlimited amounts of AI generated data.

Speakers & Sessions

Morning Sessions

9:00 AM - 12:00 PM Pacific Time

Afternoon Sessions

12:00 PM - 3:30 PM Pacific Time
9:00 am
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9:15 am
9:00 am
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9:15 am

Opening Notes

Welcome to all attendees, an overview of the event program and speaker sessions, and an overview of the synthetic data space within AI.

Opening Notes
Ali Golshan
CEO and Cofounder, Gretel
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9:15 am
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9:30 am
9:15 am
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9:30 am

Keynote: In Search of Data…

What brought us to this point in the generative AI and synthetic data market, the needs that emerged to drive this sector, and what could this space look like in the next decade?

Keynote: In Search of Data…
Sridhar Ramaswamy
CEO and Cofounder at Neeva and n.xyz, former SVP of Engineering and Ads at Google.
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9:30 am
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9:40 am
9:30 am
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9:40 am

How Foundation Models can help unlock Multi-Modal Synthetic Data

In this presentation, we will discuss how foundation models can help unlock multi-modal synthetic data by learning to generate synthetic data that is representative of the real data distribution in multiple modalities, such as text, audio, and images. By training a foundation model on a diverse and representative dataset, it can learn to generate synthetic data that is more realistic and diverse, which can be useful for a variety of applications.

How Foundation Models can help unlock Multi-Modal Synthetic Data
Alex Watson
CPO and Cofounder, Gretel
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9:40 am
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10:10 am
9:40 am
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10:10 am

Panel: Large Language Models and new opportunities in Generative AI

Panel: Large Language Models and new opportunities in Generative AI
John Myers
CTO and Cofounder, Gretel
Danny Lange
SVP of AI, Unity Technologies
Jonathan Cohen
VP of Applied Research, NVIDIA
10:10 am
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10:40 am
10:10 am
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10:40 am

Breaking the Data Bottleneck

How companies without large data engineering teams can leverage synthetic data to address regulatory, data privacy concerns and secure sharing of data across trust boundaries. The talk will include real challenges (e.g, building fraud detection models compliant with stringent data localization guidelines) faced by Swiggy and approaches to address them.

Breaking the Data Bottleneck
Vijay Seshadri
Technical Fellow, Swiggy
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10:40 am
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11:10 am
10:40 am
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11:10 am

Leveraging Privacy-Enhancing Technologies with Large Foundation Models

How privacy-enhancing technologies (PETs) like synthetic data and federated learning are helping advance the science and safe application of foundation models.

Leveraging Privacy-Enhancing Technologies with Large Foundation Models
Peter Kairouz
Research Scientist, Google
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11:10 am
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11:40 am
11:10 am
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11:40 am

Panel: How Synthetic Data is Evolving Information Security

The intersection and interplay of data science, data privacy, and information security.

Panel: How Synthetic Data is Evolving Information Security
Chris Hymes
SVP and CISO, Riot Games
Alex Maestretti
CISO, Remitly
Chris Wheeler
VP and InfoSec specialist, Morgan Stanley
Omer Singer
Head of Cybersecurity Strategy, Snowflake
12:00 pm
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12:30 pm
12:00 pm
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12:30 pm

Genomics Innovation in the Age of Generative AI

How synthetic data enables responsible medical and life science research and product development, including NLP technology's increasingly vital role, such as conversational AI.

Genomics Innovation in the Age of Generative AI
Vinayak Kulkarni
Associate Principal Bioinformatics Engineer, Illumina
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12:30 pm
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12:55 pm
12:30 pm
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12:55 pm

Synthetic data for training large NLP models

Synthetic data for training large NLP models
Spence Green
CEO and Cofounder, Lilt
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1:00 pm
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1:10 pm
1:00 pm
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1:10 pm

A Computer’s Vision for the future of computer vision

ML for computer vision has unlocked fantastic capabilities for developers of end-to-end applications. However, image collection, curation, and labeling are often prohibitively expensive. We explore how advances in text-to-image models and zero-shot object identification enable developers to rapidly build and drive business value.

A Computer’s Vision for the future of computer vision
Andrew Carr
Senior Applied Research Scientist, Gretel
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1:15 pm
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1:30 pm
1:15 pm
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1:30 pm

Prepare for turbulence: The relationship between Generative and Physics based synthetic data

Prepare for turbulence: The relationship between Generative and Physics based synthetic data
Nathan Kundtz
CEO, Rendered.AI
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1:30 pm
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1:40 pm
1:30 pm
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1:40 pm

Synthetic data revolutionizing clinical trial data collaboration and research

Synthetic data revolutionizing clinical trial data collaboration and research
Afrah Shafquat
Senior Data Scientist, Medidata Solutions
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1:40 pm
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1:55 pm
1:40 pm
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1:55 pm

Bootstrapping NLP applications with Large Language Models

Bootstrapping NLP applications with Large Language Models
Alexandre Matton
Machine Learning Staff Member, Cohere
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2:00 pm
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2:30 pm
2:00 pm
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2:30 pm

Accelerating 3D Synthetic Data Generation for Perception

Models power AI applications. Training a vision AI model requires mountains of data; this isn’t palpable for many enterprises. In most cases, the data simply doesn’t exist or is restricted. Synthetic data can help overcome the lack of data in most cases, but like any technology, it needs to be implemented properly.

Accelerating 3D Synthetic Data Generation for Perception
Nyla Worker
Product Manager, NVIDIA
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2:30 pm
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3:25 pm
2:30 pm
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3:25 pm

Interview: How LLMs Can Generate Value for Organizations

Digging into various use cases and specific examples of applied synthetic simulation.

Interview: How LLMs Can Generate Value for Organizations
Alex Watson
CPO and Cofounder, Gretel
Aditya Bindal
Product Lead, AWS AI
3:25 pm
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3:30 pm
3:25 pm
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3:30 pm

Closing Remarks

Closing Remarks
Ali Golshan
CEO and Cofounder, Gretel
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Join the community and discussion

Sessions will include interviews, panels, demos, and workshops that explore foundational concepts of synthetic generation, as well as synthetic data use cases in finance, health, Web3, and more. Attendees will also experience the excitement of generating their own data through hands-on synthesizing challenges and live collaborations with other synthesizers in the new Synthetic Data Community channel on Discord.
Join our discord
Synthesize 2023 Community
Community

FAQs