Tech Times on MSN

Brain-like learning rule cracks convolutional networks: Sakana AI measures the biology tax

Biologically plausible learning now reaches 96.7% on MNIST and 61.7% on CIFAR-10 without backpropagation, as Sakana AI ...
Art of the Problem on MSNOpinion

The second computing revolution, why neural networks replaced 70 years of human-written rules

For decades, computers did exactly what humans told them, until a biologically inspired idea quietly made that approach ...
Ars Technica

How a stubborn computer scientist accidentally launched the deep learning boom

During my first semester as a computer science graduate student at Princeton, I took COS 402: Artificial Intelligence. Toward the end of the semester, there was a lecture about neural networks. This ...
eWeek

Deep Learning vs Generative AI: Understanding the Key Differences

AI success depends on whether enterprise data is ready, reachable, and close enough to the workloads that need it. In this eSpeaks episode, Dell Technologies’ Vrashank Jain explains why fragmented ...
Quanta Magazine

Novel Architecture Makes Neural Networks More Understandable

“Neural networks are currently the most powerful tools in artificial intelligence,” said Sebastian Wetzel, a researcher at the Perimeter Institute for Theoretical Physics. “When we scale them up to ...
TechnoSports

The Synaptic Leap: Neural Architecture Search (NAS) is Rewriting the Code of Intelligence

In the high-stakes laboratory of modern machine learning, the era of human-designed neural networks is rapidly drawing to a close. At TechnoSports, we have ...
Technology Networks

Deep Learning for Variant Calling: How DeepVariant and Neural Networks Are Improving Genomic Accuracy

Deep learning variant calling has transformed genomic accuracy. Discover how DeepVariant works, outperforms classical tools, ...