AlphaFold didn't accelerate biology by running faster experiments. It changed the engineering assumptions behind protein structure prediction.

From large language models to whole brain emulation, two rival visions are shaping the next era of artificial intelligence.

Even networks long considered "untrainable" can learn effectively with a bit of a helping hand. Researchers at MIT's Computer ...

This is where Collective Adaptive Intelligence (CAI) comes in. CAI is a form of collective intelligence in which the ...

A research team from the Xinjiang Astronomical Observatory (XAO) of the Chinese Academy of Sciences has developed an ...

From SOCs to smart cameras, AI-driven systems are transforming security from a reactive to a predictive approach. This ...

Rock-paper-scissors is usually a game of psychology, reverse psychology, reverse-reverse psychology, and chance. But what if ...

Machine learning techniques that make use of tensor networks could manipulate data more efficiently and help open the black ...

FLAMeS, a new convolutional neural network, enhances MS lesion segmentation accuracy using only T2-weighted FLAIR images, ...

We have explained the difference between Deep Learning and Machine Learning in simple language with practical use cases.

In this paper, we introduce R-NET, an end-to-end neural networks model for reading comprehension style question answering, which aims to answer questions from a given passage. We first match the ...

Machine learning is transforming many scientific fields, including computational materials science. For about two decades, ...