In the intricate dance of balancing efficiency and performance within AI projects, the selection among sparse, small and large models isn't just a technical decision—it's a strategic imperative that ...

When choosing a large language model (LLM) for use in a particular task, one of the first things that people often look at is the model's parameter count. A vendor might offer several different ...

Abstract: Assumptions play a pivotal role in the selection and efficacy of statistical models, as unmet assumptions can lead to flawed conclusions and impact decision-making. In both traditional ...

Machine learning (ML) is a subset of artificial intelligence (AI) that involves using algorithms and statistical models to enable computer systems to learn from data and improve performance on a ...

This important study introduces a new biology-informed strategy for deep learning models aiming to predict mutational effects in antibody sequences. It provides solid evidence that separating ...