Machine learning models are usually complimented for their intelligence. However, their success mostly hinges on one fundamental aspect: data labeling for machine learning. A model has to get familiar ...

Recent advancements in large generative models have resulted in widespread interest in their ability to act on complex instructions. These so-called foundational large language models (LLMs), e.g., ...

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More HumanSignal, the firm behind the widely used open source Label Studio for ...

Data labeling software is crucial in developing artificial intelligence (AI) systems. It is designed to label and annotate data in a consistent and standardized manner, just like in a commonly known ...

Data annotation, or the process of adding labels to images, text, audio and other forms of sample data, is typically a key step in developing AI systems. The vast majority of systems learn to make ...

Earlier this summer Meta made a US $14.3 billion bet on a company most people had never heard of before: Scale AI. The deal, which gave Meta a 49 percent stake, sent Meta’s competitors—including ...

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 ...

Big data has become a big challenge for space scientists analyzing vast datasets from increasingly powerful space instrumentation. To address this, a team has developed a machine learning tool to ...

While artificial intelligence threatens many traditional careers, a new profession is emerging with six-figure salaries and ...

Data labeling is a critical part of AI. This essential process takes not only more than 25% of time and effort going into an ML project, but also requires an ever-growing amount of specialization and ...