As companies shift critical AI workloads toward owned or more controlled infrastructure, several accounting dynamics may ...

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, ...

A new crowd-trained way to develop LLMs over the internet could shake up the AI industry with a giant 100 billion-parameter model later this year. Flower AI and Vana, two startups pursuing ...

The artificial intelligence industry is obsessed with size. Bigger algorithms. More data. Sprawling data centers that could, in a few years, consume enough electricity to power whole cities. This ...

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 ...

AI’s future doesn’t depend on ever-larger models but on better, human-curated data. AI risks bias, hallucinations and irrelevance without expert oversight and high-quality training sets. AI is a paper ...

It seems like everyone wants to get an AI tool developed and deployed for their organization quickly—like yesterday. Several customers I’m working with are rapidly designing, building and testing ...

Artificial intelligence (AI) systems are now widely used by millions of people worldwide, as tools to source information or tackle specific tasks more rapidly and efficiently. Today, some of the most ...