The latest generative AI models such as OpenAI's ChatGPT-4 and Google's Gemini 2.5 require not only high memory bandwidth but also large memory capacity. This is why generative AI cloud operating ...

When someone starts a new job, early training may involve shadowing a more experienced worker and observing what they do ...

More information: Yi Teng et al, Solving the fractional quantum Hall problem with self-attention neural network, Physical Review B (2025). DOI: 10.1103/PhysRevB.111.205117.

TITLE: Dynamic Classification Using the Adaptive Competitive Algorithm for Breast Cancer Detection AUTHORS: Maryam Deldadehasl, Mohsen Jafari, Mohammad R. Sayeh KEYWORDS: Breast Cancer, Real-Time ...

Researchers introduced QINCo, a novel vector quantization method that employs neural networks to dynamically generate codebooks, significantly improving data compression and vector search accuracy.

This paper presents a new technique for designing a jointly optimized residual vector quantizer (RVQ). In conventional stage-by-stage design procedure, each stage codebook is optimized for that ...

Hidden geometry of learning: Neural networks think alike Date: March 27, 2024 Source: University of Pennsylvania School of Engineering and Applied Science Summary: Engineers have uncovered an ...

Efficiency of Large Language Models (LLMs) is a focal point for researchers in AI. A groundbreaking study by Qualcomm AI Research introduces a method known as GPTVQ, which leverages vector ...

Training algorithm breaks barriers to deep physical neural networks Date: December 7, 2023 Source: Ecole Polytechnique Fédérale de Lausanne Summary: Researchers have developed an algorithm to ...

The general definition of quantization states that it is the process of mapping continuous infinite values to a smaller set of discrete finite values. In this blog, we will talk about quantization in ...