Nature

Neural Networks and Inverse Scattering Problems

Recent advances at the intersection of neural networks and inverse scattering problems have transformed traditional approaches to imaging and material characterisation. Inverse scattering involves ...
Open Access Government

Reconstructing the three-dimensional structure of star-forming cores with the help of neural networks

A machine learning approach shows promise in helping astronomers infer the internal structure of stellar nurseries from ...
Crypto BriefingOpinion

Connor Leahy: We lack understanding of intelligence and neural networks, the unpredictability of AI could lead to loss of control, and GPT models have revolutioni…

The unpredictability of AI could lead to a future where humans lose control over AI systems. Neural networks differ ...
Visual Studio Magazine

Create a Working Neural Network Prediction System with C#

Many "AI experts" have sprung up in the machine learning space since the advent of ChatGPT and other advanced generative AI constructs late last year, but Dr. James McCaffrey of Microsoft Research is ...
EurekAlert!

KAIST proposes a new way to circumvent a long-time frustration in neural computing

The human brain begins learning through spontaneous random activities even before it receives sensory information from the external world. The technology developed by the KAIST research team enables ...
Ars Technica

Neural networks: How difficult is the XOR problem?

It's a long time since I last worked on neural nets, and I'm working on one now for a new project.<BR><BR>I'm testing it using the good ol' XOR problem. 2 inputs, one neuron in a hidden layer, one ...
SDxCentral

AI has a long-term memory problem (how to make neural networks less forgetful)

Generative artificial intelligence (AI) — such as ChatGPT and Dalle-2 — is undoubtedly one of the most groundbreaking and discussed technologies in recent history. Its applications and related issues ...