Today, frontier AI labs such as OpenAI and Anthropic are among its biggest and most strategically important customers. These companies need vast amounts of data to train foundation models. But that is ...

Context graphs, graph memory, and ontologies for AI are converging. What does this mean for enterprise AI in 2026?

Every AI model depends on labeled data. Data annotation is the process of tagging images, text, audio, or video so that ...

Its first exhibit translates rainforest data into a sumptuous audiovisual experience, but without a strong thesis about data ...

The Vector Institute today launched UnBias-Plus, a free, open-source AI tool built by Vector's AI Safety research scientists that helps detect, explain, and ...

Physical AI raised $10B+ in 2025, but robots still train on under 5,000 hours of real-world data. Who's funding the race to ...

SunTec India completed a major data labeling initiative for a government-backed infrastructure consulting firm, processing more than 3 million annotations with sustained 99% accuracy. The dataset will ...

Overview Explains ten major data labeling roles powering artificial intelligence across industries and applications worldwide ...

Unidata's CrowdArena scores Prolific, MTurk, Microworkers, SproutGigs, and Connect across 60+ operational parameters.

Human annotators in Brazil, Cambodia, and the Philippines are tracking every movement in the football tournament for teams, ...

Robotics startup Mecka AI secures $60M to build smarter machines trained on real-world human data gathered from wearable sensors and iPhones.

Abstract: As the scale of data grows for machine learning, annotating data accurately is extremely time-consuming and with high economic costs. To alleviate this dilemma, crowdsourcing has been widely ...