The unreasonable effectiveness of synthetic data with Daeil Kim
10.15.2020 - By Gradient Dissent - A Machine Learning Podcast by W&B
Supercharging computer vision model performance by generating years of training data in minutes.
Daeil Kim is the co-founder and CEO of AI.Reverie(https://aireverie.com/), a startup that specializes in creating high quality synthetic training data for computer vision algorithms. Before that, he was a senior data scientist at the New York Times. And before that he got his PhD in computer science from Brown University, focusing on machine learning and Bayesian statistics. He's going to talk about tools that will advance machine learning progress, and he's going to talk about synthetic data.
0:00 Diversifying content
1:00 From liberal arts to synthetic data
8:48 What is synthetic data?
11:24 Real world examples of synthetic data
16:16 Understanding performance gains using synthetic data
21:32 The future of Synthetic data and AI.Reverie
23:21 The composition of people at AI.reverie and ML
28:28 The evolution of ML tools and systems that Daeil uses
33:16 Most underrated aspect of ML and common misconceptions
34:42 Biggest challenge in making synthetic data work in the real world
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