AI Paper Summary

The phenomenon of "model collapse" represents a significant challenge in artificial intelligence (AI) research, particularly impacting large language models (LLMs). When these models are continually trained on data created by earlier versions of similar models, they lose their ability to accurately represent the underlying data distribution, deteriorating in effectiveness over successive generations. Current training methods of…

The rapid development of Transformer models in natural language processing (NLP) has brought about significant challenges, particularly with memory requirements for the training of these large-scale models. A new paper addresses these issues by presenting a new methodology called MINI-SEQUENCE TRANSFORMER (MST) which optimizes memory usage during long-sequence training without compromising performance. Traditional approaches such as…

Large language models (LLMs) act as powerful tools for numerous tasks but their utilization as general-purpose decision-making agents poses unique challenges. In order to function effectively as agents, LLMs not only need to generate plausible text completions but they also need to show interaction and goal-directed behaviour to complete specific tasks. Two critical abilities required…

The alarming phenomenon of AI model collapse, which occurs when AI models are trained on datasets that contain their outputs, has been a major concern for researchers. As such large-scale models are trained on ever-expanding web-scale datasets, concerns have been raised about the degradation of model performance over time, potentially making newer models ineffective and…

Precision psychiatry combines psychiatry, precision medicine, and pharmacogenomics to devise personalized treatments for psychiatric disorders. The rise of Artificial Intelligence (AI) and machine learning technologies has made it possible to identify a multitude of biomarkers and genetic locations associated with these conditions. AI and machine learning have strong potential in predicting the responses of patients to…

Researchers from IBM Research Europe, the Institute of Computational Life Sciences at Zürich University of Applied Sciences, and Yale School of Medicine have evaluated the progress of computational models which predict TCR (T cell receptor) binding specificity, identifying potential for improvement in immunotherapy development. TCR binding specificity is key to the adaptive immune system. T cells…