Nature

Causal Inference and Bayesian Network Learning

The past decade has witnessed significant advances in causal inference and Bayesian network learning, two intertwined disciplines that allow researchers to discern underlying cause‐and‐effect ...
ascopubs.org

Postprediction Inference for Clinical Characteristics Extracted With Machine Learning on Electronic Health Records

Real-world data (RWD) derived from electronic health records (EHRs) are often used to understand population-level relationships between patient characteristics and cancer outcomes. Machine learning ...

What is inference? Explaining the massive new shift in AI computing

The focus of artificial-intelligence spending has gone from training models to using them. Here’s how to understand the ...
ascopubs.org

Assessing Large Language Models for Oncology Data Inference From Radiology Reports

Comparative Analysis of Generative Pre-Trained Transformer Models in Oncogene-Driven Non–Small Cell Lung Cancer: Introducing the Generative Artificial Intelligence Performance Score We analyzed 203 ...
Forbes

The Inference Difference: Why Clunky Data Engineering Unhinges AI

Forbes contributors publish independent expert analyses and insights. I track enterprise software application development & data management. AI has a shiny front end. As everyone who’s used an ...
VentureBeat

Together AI's ATLAS adaptive speculator delivers 400% inference speedup by learning from workloads in real-time

Enterprises expanding AI deployments are hitting an invisible performance wall. The culprit? Static speculators that can't keep up with shifting workloads. Speculators are smaller AI models that work ...

The Future Of AI Privacy: How Federated Learning Is Revolutionizing Data Security

In an era where data breaches make headlines weekly and privacy regulations tighten globally, artificial intelligence faces a fundamental challenge: how to learn from data without compromising privacy ...