New research shows that AI doesn’t need endless training data to start acting more like a human brain. When researchers ...

While AI models may exhibit addiction-like behaviors, the technology is also proving to be a powerful ally in combating real ...

The future of AI depends on systems that can earn trust—not with marketing slogans, but with technical rigor. That future is ...

DeepSeek’s research doesn’t claim to solve hardware shortages or energy challenges overnight. Instead, it represents a quieter but important improvement: making better use of the resources already ...

This study presents SynaptoGen, a differentiable extension of connectome models that links gene expression, protein-protein interaction probabilities, synaptic multiplicity, and synaptic weights, and ...

In a striking leap toward safer self-driving cars, researchers at Texas A&M University College of Engineering and the Korea Advanced Institute of Science and Technology have unveiled a new artificial ...

Large language models often lie and cheat. We can’t stop that—but we can make them own up. OpenAI is testing another new way to expose the complicated processes at work inside large language models.

Researchers at Google Cloud and UCLA have proposed a new reinforcement learning framework that significantly improves the ability of language models to learn very challenging multi-step reasoning ...

Engineers combine measured data, multi-level behavioral models, and simulation tools to predict real-world performance across complex RF and wireless systems. Modern RF and wireless systems push the ...

A new study by Shanghai Jiao Tong University and SII Generative AI Research Lab (GAIR) shows that training large language models (LLMs) for complex, autonomous tasks does not require massive datasets.

Abstract: Power amplifier (PA) behavioral modeling and digital predistortion (DPD) are well-established and widely accepted processes. These processes involve selecting a model or DPD structure ...