Self-driving laboratories (SDLs) promise an accelerated application of the scientific method.
Through the automation of experimental workflows, along with autonomous experimental …

We envision" AI scientists" as systems capable of skeptical learning and reasoning that
empower biomedical research through collaborative agents that integrate AI models and …

The generation of plausible crystal structures is often the first step in predicting the structure
and properties of a material from its chemical composition. However, most current methods …

Before we start thinking about (deep) generative modeling, let us consider a simple
example. Imagine we have trained a deep neural network that classifies images (x∈ ℤ D) of …

We evaluate the effectiveness of pretrained and fine-tuned large language models (LLMs)
for predicting the synthesizability of inorganic compounds and the selection of precursors …

Large language models (LLMs) have emerged as powerful tools in chemistry, significantly
impacting molecule design, property prediction, and synthesis optimization. This review …

This is the interim publication of the first International Scientific Report on the Safety of
Advanced AI. The report synthesises the scientific understanding of general-purpose AI--AI …

Abstract Language models are playing an increasingly important role in many areas of
artificial intelligence (AI) and computational biology. In this primer, we discuss the ways in …

Large language models (LLMs) have been employed in various intelligent educational tasks
to assist teaching. While preliminary explorations have focused on independent LLM …

Adsorption energy is a reactivity descriptor that must be accurately predicted for effective
machine learning application in catalyst screening. This process involves finding the lowest …