The New AI Factory Model: How to Scale Quality Training Data

Abstract: AI training data operations are a lot like the assembly lines of yesterday’s industrial factories. Data is your raw material, and it you have to get it through multiple processing and review steps before it’s ready for machine learning. If you want to develop a high-performing machine learning model, you need smart people, tools, and operations that reduce the need for rework. To accelerate and scale high-quality training data, you’ll need the right workforce.

In this ODSC session, hear from data-workforce experts and learn:
- What your data production line could look like;
- 3 critical elements for your data production line;
- How to strategically design your workforce-and-tool combination for high quality training data.

Bio: Philip Tester is Director of Business Development at CloudFactory. He leads the company's strategy related to partnerships, integrations, and professional services to help AI innovators find solutions for tough data-production problems. He holds a bachelor's degree in finance from Appalachian State University. He serves on World Relief’s Good Neighbor Team, which supports refugees and survivors on their journey to self-sufficiency.