Editors Pick

Artificial intelligence (AI) researchers from Stanford University and Notbad AI Inc are striving to improve language models' AI capabilities in interpreting and generating nuanced, human-like text. Their project, called Quiet Self-Taught Reasoner (Quiet-STaR), embeds reasoning capabilities directly into language models. Unlike previous methods, which focused on training models using specific datasets for particular tasks, Quiet-STaR…

Computer vision, the field dealing with how computers can gain understanding from digital images or videos, has seen remarkable growth in recent years. A significant challenge within this field is the precise interpretation of intricate image details, understanding both global and local visual cues. Despite advances with conventional models like Convolutional Neural Networks (CNNs) and…

Scaling laws in artificial intelligence are fundamental in the development of Large Language Models (LLMs). These laws play the role of a director, coordinating the growth of models while revealing patterns of development that go beyond mere computation. With every new step, the models become more nuanced, accurately deciphering the complexities of human expression. Scaling…