Overview Curated list highlights seven impactful books covering fundamentals, tools, machine learning, visualization, and industry.Guides beginners and professi ...

Epshtein argues that a deeper understanding of generalization and principled use of prior knowledge are essential to building ...

Ad fraud is no longer a fringe issue. It is a systemic threat to digital advertising, and its scale demands a technological ...

Detecting behavioural signatures of depression from everyday digital traces is a central challenge in computational psychiatry. Real-world datasets from smartphones and wearables often suffer from ...

This article digs into how machine learning (ML) and artificial intelligence (AI) contribute to the optimization of green energy systems and electric vehicles (EVs).

Long-term lithium therapy remains the most effective maintenance treatment for bipolar disorder, yet it poses a significant risk of progressive renal impairment in a subset of patients. Early ...

Yet, traditional ITSM frameworks often rely heavily on manual processes that create inefficiencies, accuracy issues, and slow resolution times. As organizations scale and user demands grow more ...

This article explores how multiomics integration, imaging, and bioinformatics are advancing biomarker discovery, revealing ...

The first act of the current AI boom was defined by prediction. LLMs were trained to predict the next word in a sentence, acting as sophisticated statistical mirrors of the internet. But for the ...

Shallem, Greg Ravikovich and Eitan Har-Shoshanim examine how AI addresses the challenge of data overload in solar PV.

Do you prefer hype or rationality? Artificial general intelligence offers only a hazy, overzealous goal. Enter SAI, a ...