Researchers at Cold Spring Harbor Laboratory (CSHL) have developed a machine learning model for artificial neurons that can receive real-time feedback, improving efficiency and energy-saving. This model mimics the human brain's information processing, leading to more efficient AI systems. Additionally, Dmitri Chklovskii and colleagues at Flatiron Institute's Center for Computational Neuroscience (FlatironCCN) have created a new computational model of real neurons, which could lead to better AI tools. Meanwhile, a research team at Stanford’s Wu Tsai Neurosciences Institute has developed an AI algorithm that replicates the brain's sensory organization, advancing virtual neuroscience. Furthermore, a new computational tool elucidates how deep neural networks interpret genomic data.
AI Algorithm Replicates Brain's Sensory Organization for Virtual Neuroscience A research team at Stanford’s Wu Tsai Neurosciences Institute has developed an AI algorithm that replicates how the brain organizes sensory information to make sense of the world, opening new frontiers… https://t.co/dN5T0Nyzl0
A new computational model of real neurons developed by #FlatironCCN's Dmitri Chklovskii (@chklovskii) and colleagues could lead to better #AI tools. https://t.co/bfPXQbTdwl #neuroscience
📰 Researchers at @CSHL have created a machine learning model for artificial neurons to receive real-time feedback, improving efficiency & energy-saving. This model mimics the human brain's information processing for more efficient #AI systems. https://t.co/jYiTPHHPuD
A new computational model of real neurons developed by #FlatironCCN's Dmitri Chklovskii (@chklovskii) and colleagues could lead to better #AI tools. #neuroscience @FlatironInst https://t.co/GYst5N811p
New Computational Tool Elucidates How Deep Neural Networks Interpret Genomic Data #DL #AI #ML #DeepLearning #ArtificialIntelligence #MachineLearning #ComputerVision #AutonomousVehicles #NeuroMorphic #Robotics https://t.co/Ls1R8iyc9T