Foundation models for generalist medical artificial intelligence

M Moor, O Banerjee, ZSH Abad, HM Krumholz… - Nature, 2023 - nature.com
The exceptionally rapid development of highly flexible, reusable artificial intelligence (AI)
models is likely to usher in newfound capabilities in medicine. We propose a new paradigm …

Challenges and applications of large language models

J Kaddour, J Harris, M Mozes, H Bradley… - arXiv preprint arXiv …, 2023 - arxiv.org
Large Language Models (LLMs) went from non-existent to ubiquitous in the machine
learning discourse within a few years. Due to the fast pace of the field, it is difficult to identify …

Hyenadna: Long-range genomic sequence modeling at single nucleotide resolution

E Nguyen, M Poli, M Faizi, A Thomas… - Advances in neural …, 2024 - proceedings.neurips.cc
Genomic (DNA) sequences encode an enormous amount of information for gene regulation
and protein synthesis. Similar to natural language models, researchers have proposed …

ChatGPT, GPT-4, and other large language models: the next revolution for clinical microbiology?

A Egli - Clinical Infectious Diseases, 2023 - academic.oup.com
Abstract ChatGPT, GPT-4, and Bard are highly advanced natural language process–based
computer programs (chatbots) that simulate and process human conversation in written or …

The nucleotide transformer: Building and evaluating robust foundation models for human genomics

H Dalla-Torre, L Gonzalez, J Mendoza-Revilla… - BioRxiv, 2023 - biorxiv.org
Closing the gap between measurable genetic information and observable traits is a
longstand-ing challenge in genomics. Yet, the prediction of molecular phenotypes from DNA …

Opportunities and challenges for machine learning-assisted enzyme engineering

J Yang, FZ Li, FH Arnold - ACS Central Science, 2024 - ACS Publications
Enzymes can be engineered at the level of their amino acid sequences to optimize key
properties such as expression, stability, substrate range, and catalytic efficiency─ or even to …

A survey of techniques for optimizing transformer inference

KT Chitty-Venkata, S Mittal, M Emani… - Journal of Systems …, 2023 - Elsevier
Recent years have seen a phenomenal rise in the performance and applications of
transformer neural networks. The family of transformer networks, including Bidirectional …

State-specific protein–ligand complex structure prediction with a multiscale deep generative model

Z Qiao, W Nie, A Vahdat, TF Miller III… - Nature Machine …, 2024 - nature.com
The binding complexes formed by proteins and small molecule ligands are ubiquitous and
critical to life. Despite recent advancements in protein structure prediction, existing …

Scientists' Perspectives on the Potential for Generative AI in their Fields

MR Morris - arXiv preprint arXiv:2304.01420, 2023 - arxiv.org
Generative AI models, including large language models and multimodal models that include
text and other media, are on the cusp of transforming many aspects of modern life, including …

An interdisciplinary outlook on large language models for scientific research

J Boyko, J Cohen, N Fox, MH Veiga, JI Li, J Liu… - arXiv preprint arXiv …, 2023 - arxiv.org
In this paper, we describe the capabilities and constraints of Large Language Models
(LLMs) within disparate academic disciplines, aiming to delineate their strengths and …