Morning Overview on MSN

Scientists pinpoint neural roots of schizophrenia and bipolar disorder

For decades, schizophrenia and bipolar disorder have been diagnosed from the outside in, through behavior, mood, and memory ...
Drives & Controls

Neural networks halve distance measurement errors

The German sensor-maker Leuze claims that it has been able to cut measurement errors in demanding industrial applications by ...
Beebom

What is Deep Learning in AI? Understanding How AI Really Works

Deep learning uses multi-layered neural networks that learn from data through predictions, error correction and parameter adjustments. It started with the ...
WinBuzzer

Google Unveils ‘Titans’ Architecture, Enabling AI to Memorize 2 Million Tokens in Real-Time

Google Research has unveiled Titans, a neural architecture using test-time training to actively memorize data, achieving effective recall at 2 million tokens.
The New York Times

Cloudflare Says It Has Resolved Outage That Disrupted Parts of the Internet

Services from Cloudflare, a software company, underpin thousands of websites, including X, Spotify and OpenAI. The company said a crash in a software system was to blame. By Victor Mather Cloudflare, ...
Frontiers

An AI methodology to reduce training intensity, error rates, and size of neural networks

Massive computing systems are required to train neural networks. The prodigious amount of consumed energy makes the creation of AI applications significant polluters ...
Hosted on MSN

20 Activation Functions in Python for Deep Neural Networks – ELU, ReLU, Leaky-ReLU, Sigmoid, Cosine

Explore 20 different activation functions for deep neural networks, with Python examples including ELU, ReLU, Leaky-ReLU, Sigmoid, and more. #ActivationFunctions #DeepLearning #Python What the US ...
IEEE

FPGA Implementation of Fractional-Order Hopfield Neural Network With Multi-Activation Functions

Abstract: To enable accurate and resource-efficient hardware implementation of fractional-order neural networks for neuromorphic computing, an optimized hardware architecture for field programmable ...
Scientific Research Publishing

Adaptive Artificial Neural Network (ADALINE) Dynamic Phase Error Estimation Based on the Average Correlation Coefficient ()

Department of Electrical Engineering, School of Engineering, University of Zambia, Lusaka, Zambia. Yuval Abraham Regev et al. [19] deployed Long Short Term Memory (LSTM) and Convolutional Neural ...
Scientific Research Publishing

Leshno, M., Lin, V.Y., Pinkus, A. and Schocken, S. (1993) Multilayer Feedforward Networks with a Nonpolynomial Activation Function Can Approximate Any Function. Neural Networks ...

ABSTRACT: We explore the performance of various artificial neural network architectures, including a multilayer perceptron (MLP), Kolmogorov-Arnold network (KAN), LSTM-GRU hybrid recursive neural ...