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Researchers from Stanford and Cornell Introduce APRICOT: A Novel AI Approach that Merges LLM-based Bayesian Active Preference Learning with Constraint-Aware Task Planning

In the rapidly evolving field of household robotics, a significant challenge has emerged in executing personalized organizational tasks, such as arranging groceries in a refrigerator. These tasks require robots to balance user preferences with physical constraints while avoiding collisions and maintaining stability. While Large Language Models (LLMs) enable natural language communication of user preferences, this…

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NeuroFly: An AI Framework for Whole-Brain Single Neuron Reconstruction

Neuroscience has advanced significantly, allowing us to understand the mapping of neurons in the brain. Neurons have dendrites and axons, branch-like structures connecting the neurons. Understanding these mappings is crucial for uncovering how the brain processes information, supports cognition, and controls movement, which have implications in neuroscience research and neurological disorder treatment. Mesoscale imaging is…

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