From Text To Tables: Why Structured Data Is AI’s Next $600B Frontier

Tabular foundation models are the next major unlock for AI adoption, especially in industries sitting on massive databases of ...

First-time use of AI for genetic circuit design demonstrated in a human cell line

There are hundreds of cell types in the human body, each with a specific role spelled out in their DNA. In theory, all it ...
Tech Xplore

Model steering is a more efficient way to train AI models

Training artificial intelligence models is costly. Researchers estimate that training costs for the largest frontier models ...
Phys.org

Enhancing machine-learning interatomic potentials for advanced materials modeling

Machine learning is transforming many scientific fields, including computational materials science. For about two decades, scientists have been using it to make accurate yet inexpensive calculations ...
News Medical

Machine learning models can help diagnose ALS earlier from a blood sample

Using machine learning models, researchers at Michigan Medicine have identified a potential way to diagnose amyotrophic lateral sclerosis, or ALS, earlier from a blood sample, a study suggests. The ...
The Lancet

Effective sample size for individual risk predictions: quantifying uncertainty in machine learning models

Copyright: © 2025 The Author(s). Published by Elsevier Ltd. Individual prediction uncertainty is a key aspect of clinical prediction model performance; however ...
InfoWorld

AI and machine learning outside of Python

In some ways, Java was the key language for machine learning and AI before Python stole its crown. Important pieces of the data science ecosystem, like Apache Spark, started out in the Java universe.
TheServerSide

Sample Questions for AWS' Machine Learning Associate Certification

Community driven content discussing all aspects of software development from DevOps to design patterns. The AWS Machine Learning Associate certification validates your ability to configure, build, and ...
C&EN

Extrapolation Techniques in Database Construction for Machine-Learning Potentials: Achieving Subchemical Accuracy in Sampling Conformal Funnels in Catalytic Processes

CNR-ICCOM, ConsiglioNazionale delle Ricerche, via Giuseppe Moruzzi 1, Pisa 56124, Italy ...
Scientific Research Publishing

Huang, A. A., & Huang, S. Y. (2023). Increasing Transparency in Machine Learning through Bootstrap Simulation and Shapely Additive Explanations. PLOS ONE, 18, e0281922.

ABSTRACT: Machine learning (ML) has revolutionized risk management by enabling organizations to make data-driven decisions with higher accuracy and speed. However, as machine learning models grow more ...