Molecular machine learning (ML) underpins critical workflows in drug discovery, material science, and catalyst optimization ...

Rigorous study design and analytical standards are required to generate reliable findings in healthcare from artificial intelligence (AI) research. One crucial but often overlooked aspect is the ...

Manufacturing execution systems (MES) generate mountains of data. Deciphering the data, however, often consumes hours daily.

Models rewrite code to avoid being shut down. That’s why ‘alignment’ is a matter of such urgency.

Understanding how cities grow is vital for shaping sustainable urban futures—but mapping the true extent of urban expansion ...

SAVANA uses a machine learning algorithm to identify cancer-specific structural variations and copy number aberrations in long-read DNA sequencing data. The complex structure of cancer genomes means ...

Artificial intelligence and robotics are revolutionizing drug discovery by automating laboratory processes and enabling rapid ...

Google DeepMind's AlphaEvolve AI system breaks a 56-year-old mathematical record by discovering a more efficient matrix ...

Combining this information with current and historical satellite data, they trained a machine-learning algorithm to assess the history and extent of salt patches throughout the region. Sarupria ...

It can be relatively cheap to gather a lot of bio-signal data. To teach a machine-learning algorithm to find a relationship between bio-signals and health outcomes, however, you need to teach the ...

Predictive Model of Objective Response to Nivolumab Monotherapy for Advanced Renal Cell Carcinoma by Machine Learning Using Genetic and Clinical Data: The SNiP-RCC Study The use of real-world data ...

The system, dubbed Aardvark Weather, generates forecasts tens of times faster than traditional forecasting systems using a fraction of the computing power, researchers reported Thursday (March 20 ...