Why AI Models Fail: The Critical Need for Real Human Data Over Synthetic Training Sets

TCAST: The Future of Data & AI

TARTLE's Alexander McCaig and Jason Rigby discuss why AI companies are struggling with model accuracy and how real-time human feedback (RTHF) provides the solution to synthetic data limitations. Key insights include why AI models collapse at 50% synthetic data usage, the importance of demographic diversity in training sets, and how TARTLE's zero-party data approach ensures both compliance and quality across global markets.

The episode explores:

• Why public and synthetic data lead to increasing error rates
• The competitive advantage of real human behavioral data
• How TARTLE's API enables 45-minute integration for accelerated AI development
• Global compliance across GDPR, CCPA, and HIPAA through zero-party data
• The methodology for reducing algorithmic bias through diverse demographic sampling

  TCAST: A Tech and Data Podcast

  Hosted by: Alexander McCaig and Jason Rigby

  About:

  TCAST is a tech and data podcast exploring the most exciting trends in Big Data, Artificial Intelligence, and Humanity. Join Alexander and Jason as they fearlessly examine the latest developments in digital transformation and innovation.

  Each episode features insightful interviews with data scientists, thought leaders, and industry pioneers who are shaping the skills and technologies we need for human progress.

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  What's your data worth? Find out at https://tartle.co/