Nature Machine Intelligence

Nature Machine Intelligence will publish high-quality original research and reviews in a wide range of topics in machine learning, robotics and AI. The journal will also explore and discuss the significant impact that these fields are beginning to have on other scientific disciplines as well as many aspects of society and industry. There are countless opportunities where machine intelligence can augment human capabilities and knowledge in fields such as scientific discovery, healthcare, medical diagnostics and safe and sustainable cities, transport and agriculture. At the same time, many important questions on ethical, social and legal issues arise, especially given the fast pace of developments Nature Machine Intelligence will provide a platform to discuss these wide implications — encouraging a cross-disciplinary dialogue — with Comments, News Features, News & Views articles and also Correspondence.

LLM use in scholarly writing poses a provenance problem

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Deciphering RNA–ligand binding specificity with GerNA-Bind

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A multimodal cell-free RNA language model for liquid biopsy applications

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Fully analogue reinforcement learning with memristors

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Actor–critic networks with analogue memristors mimicking reward-based learning

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Structure as an inductive bias for brain–model alignment

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Empowering artificial intelligence with homomorphic encryption for secure deep reinforcement learning

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What neuroscience can tell AI about learning in continuously changing environments

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