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Featured Articles
How We Develop Standardized Protocols for Data Labeling Projects
Character.AI Joins Forces with Pareto.AI to Improve Conversational AI Models
Should You Pay Per Task or By Hour? Optimizing Worker Productivity for High-Quality Data
Reinforcement Learning from Human Feedback: Everything You Need to Know
Equitable Pay for All: Understanding Geographic Wage Disparity in Remote Work
The Future of Crowd Work: Q&A with Dr. Mark Whiting
Text annotation is a game-changer for generative AI and machine learning models. Learn how it's used in various fields to make technology understand us better.
Learn the multifaceted challenges inherent in managing data labeling projects and get a preview of our solutions!
Discover how semantic segmentation transforms image analysis by classifying each pixel for detailed scene understanding. Explore tools and techniques for enhancing AI models and achieving precise object recognition.
Let's break down AI bias: what it is, why it happens, and how we help companies fine-tune their language models to eliminate it.
Uncover the powerful technique of adversarial training, crucial for shielding AI models from deceptive attacks. This in-depth blog delves into its workings, applications, and ethical considerations, empowering you to build robust and secure AI systems.
Diffusion models are a category of latent variable generative models that includes diffusion probabilistic models and score-based generative models. Understand their structure, limitations, and applications.
Dive deep into an important conversation around challenges in the current crowd work ecosystem, worker incentive design, and the future of crowd work with Dr. Mark Whiting.
Expert labelers favor payment per task over hourly wages for high-quality data annotation despite published research. Gain insights into the contrasting influence of pay-per-task and hourly wage compensation structures for data labeler productivity.
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