DigitalToday

Stanford, Meta develop AI inference technique to boost speed and cut costs

A research team from Stanford University, Together AI, the University of Illinois Urbana-Champaign and Meta introduced a new AI inference technique that processes intermediate reasoning in an internal ...
BIOENGINEER

When Do Gene Network Maps Hold Up? New Study Maps the Robustness Rules of Omics Inference

A systematic reusability study of the CORNETO framework reveals that multi-sample biological network inference operates in ...
Medical Xpress

Local ancestry inference method could improve accuracy of genetic testing and patient diagnoses

Researchers at Texas Children's Neurological Research Institute (NRI) and Baylor College of Medicine have developed a powerful new tool within the Genome Aggregation Database (gnomAD) to sharpen the ...

ReplaySSM: A New Inference Optimization Technique to Resolve Memory Bandwidth Bottlenecks

What you will learn in this article・ How ReplaySSM resolves memory bandwidth bottlenecks in hybrid architectures such as ...
Diginomica

How causal analysis and AI intersect - methods of causal inference

Our foray into causal analysis is not yet complete. Until we define the methods of causal inference, we can't get to the deeper insights that causal analysis can provide. This article details many of ...
VentureBeat

DeepMind and UC Berkeley show how to make the most of LLM inference-time compute

Given the high costs and slow speed of training large language models (LLMs), there is an ongoing discussion about whether spending more compute cycles on inference can help improve the performance of ...
BMJ

Causal inference in physical activity epidemiology research: an opportunity for better evidence

Decades of research have established a significant link between physical activity and health, influencing agenda setting, policy making and community awareness.1–4 However, the field continues to ...
CU Boulder News & Events

Causal inference under selection on observables in operations management research: Matching methods and synthetic controls

The majority of recent empirical papers in operations management (OM) employ observational data to investigate the causal effects of a treatment, such as program or policy adoption. However, as ...
umass

Do observational causal inference methods really work?

Over the past several decades, multiple statistical methods have been developed to infer the existence and magnitude of causal effects by analyzing observational data. These methods have been widely ...