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AI Researchers Are Confronting Neural Networks’ Reasoning Gaps Despite Rapid Advances

In 2026, neural networks are achieving unprecedented efficiency, multimodal integration, and workflow comprehension, yet benchmarks like MLRegTest reveal persistent struggles with formal rule learning ...
InfoWorld

The most popular neural network styles and how they work

Learn about the most prominent types of modern neural networks such as feedforward, recurrent, convolutional, and transformer networks, and their use cases in modern AI. Neural networks are the ...
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 ...
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AI Researchers Are Shifting From Expanding Capabilities to Understanding Core Limits

In 2026, AI research is moving from simply scaling models toward probing their fundamental limits, with benchmarks like MLRegTest revealing gaps in logical generalization and causal reasoning.
Scientific American

An Alternative to Conventional Neural Networks Could Help Reveal What AI Is Doing behind the Scenes

ChatGPT has triggered an onslaught of artificial intelligence hype. The arrival of OpenAI’s large-language-model-powered (LLM-powered) chatbot forced leading tech companies to follow suit with similar ...