Artificial intelligence systems are only as powerful as the data they are trained on. High-quality labeled datasets determine whether a model performs with precision or fails in production.

Data science and machine learning teams face a hidden productivity killer: annotation errors. Recent research from Apple analyzing production machine learning (ML ...

Below is a curated list of machine learning development providers that stand out in 2026 for their ability to build enterprise-grade ML solutions tailored to complex business environments.

Bitget, a leading crypto exchange and web3 company, is pleased to announce the listing of AIT, the native token of AIT Protocol. AIT Protocol is a cutting-edge platform designed for data annotation ...

New data classification feature transforms how enterprises build high-quality training data, delivering up to 80% faster results and 25% improvement in consistency, without sacrificing quality SAN ...

Forbes contributors publish independent expert analyses and insights. Writes about the future of finance and technology, follow for more. We live in a world where machines can understand speech, ...

When developing machine learning models to find patterns in data, researchers across fields typically use separate data sets for model training and testing, which allows them to measure how well their ...

TP.ai Data Services strengthens position through acquisition of AI-enabled crowdsourcing platform for on-demand, highly skilled experts NEW YORK, June 18, 2025 /PRNewswire/ -- Global digital services ...

Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered ...