When AI models fail to meet expectations, the first instinct may be to blame the algorithm. But the real culprit is often the data—specifically, how it’s labeled. Better data annotation—more accurate, ...

Data labeling plays a pivotal role within the ever-expanding realm of AI. This intricate process involves the meticulous tagging and categorization of raw data, encompassing various formats such as ...

Simple data labeling is becoming obsolete as AI models require more complex training data, says Turing's CEO. AI training companies need to be a "proactive research partner" for major labs, Jonathan ...

Can MSPs afford to let data tagging fall behind when compliance, security, and customer trust are on the line? For Managed Service Providers (MSPs), messy ...

Data labeling has long been a critical component of helping data scientists to prepare data for machine learning (ML) and artificial intelligence (AI). In the modern era of generative AI, the role of ...

Two years ago, the entire world spent an estimated $800 million on data labeling: the painstaking process of annotating images and other information to train machine-learning and AI models. Now, the ...

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 ...

Basic data-labeling work — the kind built on tagging images or sorting text — is becoming obsolete, said the CEO of a $2.2 billion AI training firm. Jonathan Siddharth, the CEO of Turing, said on an ...

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Data labeling has long been a critical component of helping data ...