Modern Engineering Marvels on MSN

Neural Pathways for Memory and Logic in AI Now Mapped Separately

What if a model could forget without losing its mind?” That question now has a technical foothold, thanks to new research from Goodfire.ai that reveals a clean architectural split between memorization ...
Nature

Hopfield Neural Networks and Logic Satisfiability

Hopfield Neural Networks (HNNs) constitute a class of recurrent neural networks that function as associative memory systems, adept at converging towards stable states that represent optimised ...

Researchers isolate memorization from problem-solving in AI neural networks

The researchers discovered that this separation proves remarkably clean. In a preprint paper released in late October, they ...
pv magazine International

Artificial neural networks and fuzzy logic for fault detection in PV systems

Researchers from the Zhengzhou University in China have created a new electrical fault detection system for PV systems by using the Adaptive Neuro-Fuzzy Inference System (ANFIS) methodology, which is ...
The Scientist

Artificial Neural Networks: Learning by Doing

Article reviewed by Grace Lindsay, PhD from New York University. Scientists design ANNs to function like neurons. 6 They write lines of code in an algorithm such that there are nodes that each contain ...
Forbes

1000X More Efficient Neural Networks: Building An Artificial Brain With 86 Billion Physical (But Not Biological) Neurons

What if in our attempt to build artificial intelligence we don’t simulate neurons in code and mimic neural networks in Python, but instead build actual physical neurons connected by physical synapses ...

Plush neuron makes AI approachable, simplifies neural networks for middle schoolers

A team at Carnegie Mellon University is helping kids understand artificial intelligence with a soft, squishy, LED-lit neural ...