One of the stand-out characteristics of Artificial Intelligence (AI) is its ability to learn, for better or for worse. It’s this ongoing effort that distinguishes AI from static, code-dependent software. It’s also precisely this ability that makes high-quality annotated data a crucial element in training representative, successful, and bias-free AI models.

In this episode, we sit down with Jason Liang, VP of Business Development and Co-founder of SuperAnnotate. This AI lifecycle platform provides annotation services and training data for machine learning models. With over a decade of experience in finance, corporate, and tech startups, Jason brings a unique perspective to the conversation. We start by exploring Jason's background, including his experience at Lehman Brothers and his time in the tech world at SAP's mobile division. From there, we dive into the SuperAnnotate platform and how it helps companies build high-quality datasets for machine learning. Jason explains how SuperAnnotate uses professionally managed annotation teams instead of crowdsourcing to ensure high data quality.

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Founder Bio:

Jason Liang is the VP of Business Development and a Co-founder of SuperAnnotate where his goal is to help every organization radically improve the way they build, manage, and leverage datasets for machine learning unlocking limitless value in their data. Jason has a decade of experience leading go-to-market activities for ML companies such as Qeexo and DataRobot. Jason also spent time at SAP, as the Executive Director for Global Solutions. Jason began his career in investment banking at Lehman Brothers. He has an MBA from UC Berkeley's Haas School of Business and a bachelor's degree from MIT. Jason is also an advisor for a number of startups and is a go-to-market advisor for Berkeley's SkyDeck incubator.

Time Stamps:

00:00 Jason's background: from finance to AI startup founder

03:30 Exploring data annotation and labeling with super annotate

06:15 Leveraging professional annotation teams to streamline data labeling processes

09:50 Data engineering solutions for AI companies of all sizes

12:23 Data annotation and machine learning workflows for fortune 500 companies

13:53 Managing data for fortune 500 companies: challenges and solutions

17:11 AI development consulting services

18:16 Exploring go-to-market strategies for early-stage startups in computer vision and NLP

22:13 Leveraging software and training to outperform specialized agronomists

23:29 AI adoption and SuperAnnotate fundraising journey

26:00 Potential of generalized machine learning and AI infrastructure

29:32 Regulations and ethics in artificial intelligence deployment

31:32 Discussing data security and compliance

32:55 How to get in contact with the SuperAnnotate team

Resources:

Company website: https://www.superannotate.com/ Facebook: https://www.facebook.com/superannotate LinkedIn: https://www.linkedin.com/company/superannotate/ Twitter: https://twitter.com/superannotate