Researchers at Tsinghua University have posted their preprint on arXiv addressing one of AI interpretability's most persistent scaling problems: the inability to label millions of sparse autoencoder ...

Unidata has built stations designed to capture egocentric data for robotics: depth, touch, full-body and hand motion, ...

South Korea AI training data audit: the Board of Audit and Inspection found $1.1 billion spent over seven years building 908 government AI datasets produced many too contaminated by annotation errors ...

Spread the loveWhen the world shifted online, Zoom became an indispensable tool for everything from family catch-ups to corporate board meetings. But for educators, its true potential lies in its ...

Allergy labels, whether for vaccines, drugs (notably antibiotics), foods, or perioperative agents, are among the most common and consequential pieces of ...

Worrying about Google Glassholes almost feels quaint in comparison.

A South Korean audit found duplication, labeling errors and unusable records in public AI training data built with more than $1.1 billion.

Google DeepMind has shipped a sign-language-to-text model, SL2T, inside two consumer Android products, the first time sign language AI has reached a shipping phone feature. The model powers ...

A significant portion of the data built by the government and public institutions to train AI (artificial intelligence) has been found to be of low quality, either unusable for training or capable of ...

Mathieu Aubry will give a quick overview of his past and ongoing projects which could be used to establish links between artworks and historical documents, including repeated patterns discovery in ...

Autonomous mobility is often treated as a specialized vertical. It should be treated as an early warning system.

AI systems can’t learn without context. Data annotation services are important. They convert raw input into labeled, structured data. This data is usable for machine learning models. Industries use da ...