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Diving Deep into Synthetic Data with Alex Watson of Gretel.ai
Episode 2820th April 2021 • Machine Learning Engineered • Charlie You
00:00:00 01:19:10

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Alex Watson is the co-founder and CEO of Gretel.ai, a startup that offers APIs for creating anonymized and synthetic datasets. Previously he was the founder of Harvest.ai, whose product Macie, an analytics platform protecting against data breaches, was acquired by AWS.

Learn more about Alex and Gretel AI:

http://gretel.ai

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Timestamps:

02:15 Introducing Alex Watson

03:45 How Alex was first exposed to programming

05:00 Alex's experience starting Harvest AI, getting acquired by AWS, and integrating their product at massive scale

21:20 How Alex first saw the opportunity for Gretel.ai

24:20 The most exciting use-cases for synthetic data

28:55 Theoretical guarantees of anonymized data with differential privacy

36:40 Combining pre-training with synthetic data

38:40 When to anonymize data and when to synthesize it

41:25 How Gretel's synthetic data engine works

44:50 Requirements of a dataset to create a synthetic version

49:25 Augmenting datasets with synthetic examples to address representation bias

52:45 How Alex recommends teams get started with Gretel.ai

59:00 Expected accuracy loss from training models on synthetic data

01:03:15 Biggest surprises from building Gretel.ai

01:05:25 Organizational patterns for protecting sensitive data

01:07:40 Alex's vision for Gretel's data catalog

01:11:15 Rapid fire questions


Links:

Gretel.ai Blog

NetFlix Cancels Recommendation Contest After Privacy Lawsuit

Greylock - The Github of Data

Improving massively imbalanced datasets in machine learning with synthetic data

Deep dive on generating synthetic data for Healthcare

Gretel’s New Synthetic Performance Report

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Snow Crash

The MurderBot Diaries

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