Li et al. show that recurrent neural networks optimized for free recall discover diverse, human-like memory strategies beyond classical temporal context models, with top models using an index-based me...

What if we could predict how cells would react to a new drug even before testing it in the laboratory? A radically different and promising approach now on the cover of Nature Machine Intelligence.

Nature Machine Intelligence - Human–AI interactions reshape the self and our social networks

Browse all the issues in Volume 8 of Nature Machine Intelligence

AI copilots are integrated into brain–computer interfaces, enabling a paralysed participant to achieve improved control of computer cursors and robotic arms. This shared autonomy approach offers a promising path to increase BCI performance and clinical viability.

An interpretability framework that compares how humans and deep neural networks process images has been presented. Their findings reveal that, unlike humans, deep neural networks focus more on visual ...

Nature Machine Intelligence - LLMs as all-in-one tools to easily generate publication-ready citation diversity reports

Fed the right information, large language models can match what the brain sees when it takes in an everyday scene such as children playing or a big city skyline, a new study led by Ian Charest finds.

Doerig, Kietzmann and colleagues show that the brain’s response to visual scenes can be modelled using language-based AI representations. By linking brain activity to caption-based embeddings from lar...

The integration of AI into mental health and wellness domains has outpaced regulation and research.

Recurrent neural networks are efficient and capable agents for discovering new peptides with strong self-organizing capabilities.

Understanding how people perceive and interpret uncertainty from large language models (LLMs) is crucial, as users often overestimate LLM accuracy, especially with default explanations. Steyvers et al...

Sharp distinctions often drawn between machine and biological intelligences have not tracked advances in the fields of developmental biology and hybrid robotics. We call for conceptual clarity driven ...

Large language model-based agentic systems can process input information, plan and decide, recall and reflect, interact and collaborate, leverage various tools and act. This opens up a wealth of oppor...