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Revolutionizing Multimodal AI: A Breakthrough in Efficient Neural Networks with Advanced Attention Mechanisms
Explore a revolutionary neural network architecture integrating Multi-Query, Multi-Head, and Grouped-Query Attention, enhancing efficiency and adaptability in multimodal tasks while reducing computational costs and memory usage.
AI pioneers win the Nobel Prize in Physics
John Hopfield and Geoffrey Hinton, two pioneers of machine learning and artificial neural networks, have won the Nobel Prize in Physics.
NEOLAF: Introducing a Never-Ending Learning Framework for Intelligent Agents
Introducing NEOLAF: A novel Neural-Symbolic Cognitive Architecture revolutionizing AI. Enhanced explainability, efficiency, and self-improvement redefine intelligent agent construction. Dive into its advanced learning capabilities and transformative potential.
Exploring Geometry-Informed Neural Networks: A Data-Free Approach to Shape Generation
Geometry-Informed Neural Networks (GINNs) transform shape generation by using geometric constraints and neural fields, enabling data-free training and diverse solutions across computer graphics, engineering, and medical imaging.
Unlocking the power of exascale supercomputers
Exascale supercomputers to transform deep neural networks and online data analysis
Connecting neural and symbolic AI networks
US Office of Naval Research funding may help make AI more reliable and transparent
Researchers predict what a mouse sees by decoding its brain signals
Could enable new advanced brain-machine interfaces
Physical neural network learns and remembers ‘on the fly’ like neurons for low-energy machine intelligence
Neuromorphic nanowire networks outperfom conventional artificial neural networks, avoiding heavy memory and energy usage
Babies Beat Bots
Infants outperform AI in detecting what motivates other people’s actions: new study