Therefore, parallel computing and acceleration techniques have become crucial in the research and application of neural networks, as they can significantly enhance the performance and efficiency of ...

A new machine learning tool can reduce errors in national flood prediction programming, resulting in more accurate ...

Overview: Machine learning tools simplify and speed up AI development.Options include open-source frameworks and cloud AI ...

A landmark has been reached in the field of physics and artificial intelligence with the successful resolution of a ...

'Underwater' car trade-ins are at a 4-year high: What that means when buying a new vehicle 'I like not-working better': A ...

Abstract: Phase-change memory (PCM) is a novel type of nonvolatile memory and offers low power consumption, high integration, and significant plasticity, making it suitable for neural synapses. In ...

An AI-driven digital-predistortion (DPD) framework can help overcome the challenges of signal distortion and energy ...

Forget quantum — neuromorphic AI could be the real disruptor, reshaping everything from medicine to warfare while cutting ...

This is a general purpose aimbot, which uses a neural network for enemy/target detection. The aimbot doesn't read/write memory from/to the target process. It is essentially a "pixel bot", designed ...

For more than eighty years, deep learning has relied on a simplified model of brain function. Now, a Pittsburgh startup ...

This repository contains a time series forecasting project using the Google Play Store dataset. It systematically compares RNN, LSTM, and GRU models, optimized via Keras Tuner, to predict future app ...