AI optimists envision a future where artificial general intelligence (AGI) surpasses human intelligence, but the path remains riddled with scientific and logistical hurdles.

To be human is, fundamentally, to be a forecaster. Occasionally a pretty good one. Trying to see the future, whether through the lens of past experience or the logic of cause and effect, has helped us ...

To prevent algorithmic bias, the authors call for multivariable modeling frameworks that jointly incorporate biological sex, genetic ancestry, and gender-related life-course exposures.

Lance Fortnow on the current status and future outlook of solving the P-NP problem.

Frontier models such as OpenAI's GPT depend mostly on increasing computing power rather than smarter algorithms, according to a new MIT report. Here's why that matters.

After building an AI prototype in six hours, John Winsor turned it into a full platform in two weeks—showing how AI is collapsing the gap between vision and execution.

AI’s biggest constraint isn’t algorithms anymore. It’s data…specifically, high-quality, forward-looking data. It is the “Rare ...

A new technique from Stanford, Nvidia, and Together AI lets models learn during inference rather than relying on static ...

During cardiac arrhythmia, the heart frequency is an important physiological parameter that can be identified by analyzing electrocardiogram (ECG) signals. However, the accuracy of the frequency ...

Abstract: Orthogonal Time Frequency Space (OTFS) modulation exhibits excellent bit error rate (BER) performance in high-speed mobile scenarios. However, the two ...