#model scaling

'Study finds DINOv3 models trained on billions of natural images align with human cortical responses across space and time, driven by model size, training amount, and image type'

Researchers from Edinburgh, Cohere, and Meta demonstrate that large sparse models can outperform smaller dense models for long-context LLMs by leveraging sparse attention, offering new scaling laws and standardized methods.