AI podcasts for the summer. A teachable moment for dual-use. New deepfake regulations in China are a tool for social stability, but at what cost? Bringing artificial intelligence to business management. In vitro convolutional neural networks. Learning the missing channel. Neural Error Mitigation of Near-Term Quantum Simulations. Learning plastic matching of robot dynamics in closed-loop central pattern generators. Privacy debate obscures pandemic power shifts. Lessons from infant learning for unsupervised machine learning. Controllable protein design with language models. A framework for tool cognition in robots without prior tool learning or observation. Improving de novo molecular design with curriculum learning. Gradient-based learning drives robust representations in recurrent neural networks by balancing compression and expansion. A textile exomuscle that assists the shoulder during functional movements for everyday life. A soft touch for robots. A cautionary tale from the machine scientist. The promise and perils of using artificial intelligence to fight corruption. Functional mimicry of Ruffini receptors with fibre Bragg gratings and deep neural networks enables a bio-inspired large-area tactile-sensitive skin. A Long Short-Term Memory for AI Applications in Spike-based Neuromorphic Hardware. An interpretable deep learning workflow for discovering subvisual abnormalities in CT scans of COVID-19 inpatients and survivors. Tackling the perils of dual use in AI. The perils of machine learning in designing new chemicals and materials. Ethics methods are required as part of reporting guidelines for artificial intelligence in healthcare. Designing a strong test for measuring true common-sense reasoning. Barriers to academic data science research in the new realm of algorithmic behaviour modification by digital platforms. Deep-learning-based identification, tracking, pose estimation and behaviour classification of interacting primates and mice in complex environments. Combinatorial optimization with physics-inspired graph neural networks. Author Correction: Advancing COVID-19 diagnosis with privacy-preserving collaboration in artificial intelligence. Author Correction: Autoencoders on field-programmable gate arrays for real-time, unsupervised new physics detection at 40 MHz at the Large Hadron Collider. The graph connection Dual use of artificial-intelligence-powered drug discovery GRAPH-BASED MACHINE LEARNING Half a decade of graph convolutional networks Biological underpinnings for lifelong learning machines The transformational role of GPU computing and deep learning in drug discovery Reusability report: Capturing properties of biological objects and their relationships using graph neural networks Learning functional properties of proteins with language models Quantifying the spatial homogeneity of urban road networks via graph neural networks Large pre-trained language models contain human-like biases of what is right and wrong to do Optimizing quantum annealing schedules with Monte Carlo tree search enhanced with neural networks Asymmetric predictive relationships across histone modifications A transformer-based model to predict peptide-HLA class I binding and optimize mutated peptides for vaccine design Automatic strain sensor design via active learning and data augmentation for soft machines (vol 4, pg 84, 2022) Safe driving cars. FDA fosters innovative approaches in research, resources and collaboration. Human autonomy in the age of artificial intelligence. Potent antimalarial drugs with validated activities. Responsible artificial intelligence in agriculture requires systemic understanding of risks and externalities. Stable learning establishes some common ground between causal inference and machine learning. A soft thumb-sized vision-based sensor with accurate all-round force perception.