March 18, 2024, 5:35 p.m. | Dr. Tehseen Zia

Unite.AI www.unite.ai

As generative AI technology advances, there's been a significant increase in AI-generated content. This content often fills the gap when data is scarce or diversifies the training material for AI models, sometimes without full recognition of its implications. While this expansion enriches the AI development landscape with varied datasets, it also introduces the risk of […]


The post When AI Poisons AI: The Risks of Building AI on AI-Generated Contents appeared first on Unite.AI.

advances ai development ai-generated content ai models ai technology ai technology advances artificial intelligence building contents data data poisoning development expansion gap generated generative generative ai technology landscape material model collapse recognition risks technology training training material

More from www.unite.ai / Unite.AI

Data Architect

@ University of Texas at Austin | Austin, TX

Data ETL Engineer

@ University of Texas at Austin | Austin, TX

Lead GNSS Data Scientist

@ Lurra Systems | Melbourne

Senior Machine Learning Engineer (MLOps)

@ Promaton | Remote, Europe

Software Engineer, Data Tools - Full Stack

@ DoorDash | Pune, India

Senior Data Analyst

@ Artsy | New York City