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Submit ReviewAlex 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:
Every Thursday I send out the most useful things I’ve learned, curated specifically for the busy machine learning engineer. Sign up here: https://www.cyou.ai/newsletter
Follow Charlie on Twitter: https://twitter.com/CharlieYouAI
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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:
NetFlix Cancels Recommendation Contest After Privacy Lawsuit
Improving massively imbalanced datasets in machine learning with synthetic data
Deep dive on generating synthetic data for Healthcare
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:
Every Thursday I send out the most useful things I’ve learned, curated specifically for the busy machine learning engineer. Sign up here: https://www.cyou.ai/newsletter
Follow Charlie on Twitter: https://twitter.com/CharlieYouAI
Subscribe to ML Engineered: https://mlengineered.com/listen
Comments? Questions? Submit them here: http://bit.ly/mle-survey
Take the Giving What We Can Pledge: https://www.givingwhatwecan.org/
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:
NetFlix Cancels Recommendation Contest After Privacy Lawsuit
Improving massively imbalanced datasets in machine learning with synthetic data
Deep dive on generating synthetic data for Healthcare
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