Holding signs and banners reading Stop the AI Race and Don’t Build Skynet, the protesters marched through the city and gave ...

Can a handful of atoms outperform a much larger digital neural network on a real-world task? The answer may be yes. In a ...

The leader at the forefront of de-extinction is also building Astromech, a platform designed to predict how biological ...

Messenger RNA (mRNA) therapeutics have moved from a promising idea to clinical reality, accelerating vaccine development and opening new paths ...

Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. Soroosh Khodami discusses why we aren't ready ...

Carnegie Mellon University’s Center for AI-Driven Biomedical Research (AI4BIO) chose its first research projects that will use artificial intelligence and machine learning to unlock the complex ...

ABSTRACT: This paper proposes a hybrid machine learning framework for early diabetes prediction tailored to Sierra Leone, where locally representative datasets are scarce. The framework integrates ...

Traditional QSRR models are limited to single-column predictions, hindering adaptability across diverse LC setups in pharmaceutical settings. The new ML-based approach predicts retention times using ...

However, NGD faces several challenges associated with gamma-ray generation and attenuation complexities. Unlike GGD, which utilizes 0.662 MeV monoenergetic γ rays from a 137 Cs source, NGD employs ...

This project implements state-of-the-art deep learning models for financial time series forecasting with a focus on uncertainty quantification. The system provides not just point predictions, but ...

Tumor Site–Specific Radiation-Induced Lymphocyte Depletion Models After Fractionated Radiotherapy: Considerations of Model Structure From an Aggregate Data Meta-Analysis Lymphocytes play critical ...