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Tag: Transformers

  • Longer AI Contexts Weaken Privacy and Accuracy
    Artificial Intelligence

    Longer AI Contexts Weaken Privacy and Accuracy

    by Rohail T.February 18, 2026
  • Ai’s ‘attention’ System Understood, Paving the Way for Limitless Context Processing
    Artificial Intelligence

    Ai’s ‘attention’ System Understood, Paving the Way for Limitless Context Processing

    by Rohail T.February 13, 2026
  • Neural Networks Demonstrate Bayesian Uncertainty Tracking Via Implicit EM with Distances
    Artificial Intelligence

    Neural Networks Demonstrate Bayesian Uncertainty Tracking Via Implicit EM with Distances

    by Rohail T.January 7, 2026
  • Spiking Neuromorphic Transformer Achieves Attention Via Synaptic Plasticity, Reducing Energy Costs Beyond 0.49
    Science

    Spiking Neuromorphic Transformer Achieves Attention Via Synaptic Plasticity, Reducing Energy Costs Beyond 0.49

    by Rohail T.November 20, 2025
  • Researchers Achieve 17-fold Speed-up in Materials Science with Universal MLIPs and 6% Accuracy
    Artificial Intelligence

    Researchers Achieve 17-fold Speed-up in Materials Science with Universal MLIPs and 6% Accuracy

    by Quantum NewsSeptember 1, 2025
  • HyDRA Architecture Improves Wireless Device Recognition Using VMD, CNNs, Transformers, and Mamba
    Artificial Intelligence

    HyDRA Architecture Improves Wireless Device Recognition Using VMD, CNNs, Transformers, and Mamba

    by Quantum NewsJuly 17, 2025
  • MambaNeXt-YOLO: Efficient Real-time Object Detection with State Space Models.
    Artificial Intelligence

    MambaNeXt-YOLO: Efficient Real-time Object Detection with State Space Models.

    by Quantum NewsJune 6, 2025
  • Transformers: A Novel Framework for Efficient Uncertainty Quantification Using In-Context Learning & Conformal Prediction
    Artificial Intelligence

    Transformers: A Novel Framework for Efficient Uncertainty Quantification Using In-Context Learning & Conformal Prediction

    by Quantum NewsApril 24, 2025
  • The Rise of Generative AI: How Machines Learned to Create
    Artificial Intelligence

    The Rise of Generative AI: How Machines Learned to Create

    by Quantum NewsApril 21, 2025
  • Transformers Without Normalization: Replaced By Dynamic Tanh For Improved Performance In Machine Learning
    Artificial Intelligence, Machine Learning

    Transformers Without Normalization: Replaced By Dynamic Tanh For Improved Performance In Machine Learning

    by Quantum NewsMarch 18, 2025
  • Design Knowledge Boosts Accuracy in Large Language Models
    Artificial Intelligence

    Design Knowledge Boosts Accuracy in Large Language Models

    by Quantum NewsNovember 26, 2024
  • Revolutionising Language Models: MatMul-Free Method Achieves High Performance with 61% Less Memory Usage
    Artificial Intelligence

    Revolutionising Language Models: MatMul-Free Method Achieves High Performance with 61% Less Memory Usage

    by Quantum NewsJune 9, 2024
  • Japan Unveils Fugaku-LLM: Supercomputer-Trained Language Model Revolutionising AI Research and Business
    Artificial Intelligence

    Japan Unveils Fugaku-LLM: Supercomputer-Trained Language Model Revolutionising AI Research and Business

    by Quantum NewsMay 15, 2024
  • Large-scale machine-learning methods have shown a surprising ability to forecast chaotic systems beyond typical predictability horizons. These methods, such as transformers or recurrent neural networks, outperform specialised methods grounded in dynamical systems theory, like reservoir computers or neural ordinary differential equations, especially when there is a lot of data available. However, in data-limited settings, physics-based hybrid methods retain an advantage due to their strong inductive biases. The study, conducted by William Gilpin (The University of Texas at Austin, Austin, Texas) also found that the Lyapunov exponent, a measure of chaos, does not correlate with the accuracy of different forecasting methods.
    Artificial Intelligence, Physics, Technology News

    Large-Scale Machine Learning Models Outperform Physics-Based Methods in Forecasting Chaos Revealed in New Study

    by Physics NewsDecember 22, 2023

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