Daily Excelsior

Machine Learning Methods Used for Portfolio Optimization and Risk Management

Machine learning is reshaping the way portfolios are built, monitored, and adjusted. Investors are no longer limited to ...
Learn With Jay on MSN

Neural network Python from scratch with softmax

Implement Neural Network in Python from Scratch ! In this video, we will implement MultClass Classification with Softmax by ...
NextBigFuture

Analog in-memory Computing Attention Mechanism for Fast and Energy-efficient Large Language Models

A Nature paper describes an innovative analog in-memory computing (IMC) architecture tailored for the attention mechanism in large language models (LLMs). They want to drastically reduce latency and ...
IEEE

Hardware-Efficient SoftMax Architecture With Bit-Wise Exponentiation and Reciprocal Calculation

Abstract: The SoftMax function is one of the activation functions used in deep neural networks (DNN) to normalize input values to the range of (0,1). With the advent of DNN models including the ...
marktechpost

Enhancing Artificial Intelligence Reasoning by Addressing Softmax Limitations in Sharp Decision-Making with Adaptive Temperature Techniques

The ability to generate accurate conclusions based on data inputs is essential for strong reasoning and dependable performance in Artificial Intelligence (AI) systems. The softmax function is a ...
marktechpost

FlashSigmoid: A Hardware-Aware and Memory-Efficient Implementation of Sigmoid Attention Yielding a 17% Inference Kernel Speed-Up over FlashAttention-2 on H100 GPUs

Large Language Models (LLMs) have gained significant prominence in modern machine learning, largely due to the attention mechanism. This mechanism employs a sequence-to-sequence mapping to construct ...