This AI Model Can Intuit How the Physical World Works

Researchers have developed an AI system that learns about the world via videos and demonstrates a notion of “surprise” when ...

Building an AI Driven Portfolio Management System: From Machine Learning Basics to Advanced Implementation

Two important architectures are Artificial Neural Networks and Long Short-Term Memory networks. LSTM networks are especially useful for financial applications because they are designed to work with ...
Tech Xplore

Overparameterized neural networks: Feature learning precedes overfitting, research finds

Modern neural networks, with billions of parameters, are so overparameterized that they can "overfit" even random, ...
IEEE

Implementing Holographic Reduced Representations for Spiking Neural Networks

Abstract: Neuromorphic Computing surpasses conventional von Neumann architectures in terms of energy efficiency, parallelisation, scalability, and stochasticity. Given the inherent structure of ...
GitHub

A comprehensive HDL toolchain for compiling Loihi-style spiking neural networks onto affordable FPGA platforms, implementing the Neuromorphic-FPGA architecture presented at ...

This project provides an end-to-end pipeline for deploying neuromorphic computing models on commodity FPGAs, bridging the gap between high-level SNN frameworks and low-level hardware implementations.
Nature

What is the future of intelligence? The answer could lie in the story of its evolution

The advent of artificial intelligence might be just the latest stage in a guiding biological process that has produced ever more complex, mutually dependent organisms over the history of life.
IEEE

Real-Time Implementation of Neural-Network Post-Filters for 4K 60fps VVC Videos

Abstract: This study investigates the practical performance of neural-network post-filters standardized in ITU-T H.274. We implement neural-network models on a Field-Programmable Gate Array (FPGA), ...