Humans possess a remarkable balance between stability and flexibility, enabling them to quickly establish new plans and ...

No matter how much data they learn, why do artificial intelligence (AI) models often miss the mark on human intent?

From solving puzzles to masterfully playing a game of chess, current artificial intelligence tools have employed algorithms and generative responses to mimic human intelligence in ways that, at times, ...

Large language models already read, write, and answer questions with striking skill. They do this by training on vast libraries of text. Once that training ends, though, the model’s knowledge largely ...

Large language models (LLMs) deliver impressive results, but are they truly capable of reaching or surpassing human ...

The rise of the AI gig workforce has driven an important shift from commodity task execution to first-tier crowd contribution ...

In the realm of education, the integration of technology–and particularly artificial intelligence (AI)–with traditional human-led instruction is a topic of increasing relevance and debate. As ...

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 ...

Analyzing several major pathology AI models designed to diagnose cancer, the researchers found unequal performance in ...

As generative AI continues reshaping industries worldwide, enterprises are accelerating adoption across production, ...