Category: History - Page 3
Quality Control for Multimodal Generative AI Outputs: Human Review and Checklists
Human review and structured checklists are essential for catching hidden errors in multimodal AI outputs that automated systems miss. Learn how to implement proven frameworks in biopharma, manufacturing, and regulated industries.
Benchmarking Bias in Image Generators: How Diffusion Models Reinforce Gender and Race Stereotypes
Diffusion models like Stable Diffusion amplify racial and gender stereotypes in generated images, underrepresenting women in leadership and overrepresenting Black individuals in low-status roles. Real-world harm is already happening in hiring and education.
Document Intelligence Using Multimodal Generative AI: PDFs, Charts, and Tables
Multimodal generative AI now reads PDFs, charts, and tables together-understanding how text, images, and data connect. Learn how it outperforms old OCR systems and where it's being used today.
Autonomous Agents in Generative AI for Business Processes: From Plans to Actions
Autonomous agents in generative AI are transforming business processes by planning and executing tasks without human intervention. Learn how they work, who's using them, and how to get started in 2025.
State-Level Generative AI Laws in the United States: California, Colorado, Illinois, and Utah
California has passed the most comprehensive generative AI laws in the U.S., requiring transparency, consent, and accountability. Colorado, Illinois, and Utah have taken narrower approaches - focusing on insurance, deepfakes, and privacy, respectively. Businesses must comply with California’s rules if they serve its residents.
