AI is ultimately a story about selfhood—and the answer will not be found in the machine, but in what mindful awareness allows ...

Modern neuroscience and the computational modeling of the activities of vast, integrated neural networks provide fruitful accounts of how our minds work and learn.

While standard models suffer from context rot as data grows, MIT’s new Recursive Language Model (RLM) framework treats ...

Like all AI models based on the Transformer architecture, the large language models (LLMs) that underpin today’s coding ...

Overview: Master deep learning with these 10 essential books blending math, code, and real-world AI applications for lasting ...

Implement Neural Network in Python from Scratch ! In this video, we will implement MultClass Classification with Softmax by making a Neural Network in Python from Scratch. We will not use any build in ...

Abstract: The present work focuses on the comprehensive implementation of gas/mixture identification employing chemometric analysis followed by on-chip realization. The chemometric analysis has been ...

A hunk of material bustles with electrons, one tickling another as they bop around. Quantifying how one particle jostles others in that scrum is so complicated that, beginning in the 1990s, physicists ...

The experimental model won't compete with the biggest and best, but it could tell us why they behave in weird ways—and how trustworthy they really are. ChatGPT maker OpenAI has built an experimental ...

When engineers build AI language models like GPT-5 from training data, at least two major processing features emerge: memorization (reciting exact text they’ve seen before, like famous quotes or ...

Abstract: In this paper, we consider the design of model predictive control (MPC) algorithms based on deep operator neural networks (DeepONets) (Lu et al. 2021). These neural networks are capable of ...