However, these complex tasks require increasingly complex neural networks; some with many billion parameters. This rapid growth of neural network size has put the technologies on an unsustainable path ...
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AI Researchers Are Confronting the Gap Between Neural Network Power and True Generalization
In 2026, neural networks are achieving unprecedented capabilities across industries, yet large-scale tests reveal persistent struggles with generalization. Researchers are exploring adaptive ...
Scientists propose a new way of implementing a neural network with an optical system which could make machine learning more sustainable in the future. The researchers at the Max Planck Institute for ...
The rapid ascent of large-scale artificial intelligence has provided neuroscience with a new set of powerful tools for modeling complex cognitive functions.
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A simple physics-inspired model sheds light on how AI learns
Artificial intelligence systems based on neural networks—such as ChatGPT, Claude, DeepSeek or Gemini—are extraordinarily ...
Researchers use statistical physics and "toy models" to explain how neural networks avoid overfitting and stabilize learning in high-dimensional spaces.
Contemporary artificial intelligence (AI) systems, such as the models underpinning the functioning of ChatGPT, image ...
Researchers at the Max Planck Institute for the Science of Light (MPISL), Erlangen, Germany, have developed a new approach to implementing a neural network with an optical system. They say that this ...
Spiking Neural Networks (SNNs) represent the "third generation" of neural models, capturing the discrete, asynchronous, and energy-efficient nature of ...
Scientists propose a new way of implementing a neural network with an optical system which could make machine learning more sustainable in the future. The researchers at the Max Planck Institute for ...
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