The New Frontier Of LLM Inference: Where The Next Tenfold Gains Will Come From

This brute-force scaling approach is slowly fading and giving way to innovations in inference engines rooted in core computer ...

Zero‑Trust AI: The New Security Model For Enterprise LLMs

LLMs change the security model by blurring boundaries and introducing new risks. Here's why zero-trust AI is emerging as the ...
JSTOR Daily

A BAYESIAN GRAPHICAL MODELING APPROACH TO MICRORNA REGULATORY NETWORK INFERENCE

It has been estimated that about 30% of the genes in the human genome are regulated by microRNAs (miRNAs). These are short RNA sequences that can down-regulate the levels of mRNAs or proteins in ...

New ‘Test-Time Training’ method lets AI keep learning without exploding inference costs

By allowing models to actively update their weights during inference, Test-Time Training (TTT) creates a "compressed memory" that solves the latency bottleneck of long-document analysis.
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 ...
TechRadar

What is AI inference at the edge, and why is it important for businesses?

AI inference at the edge refers to running trained machine learning (ML) models closer to end users when compared to traditional cloud AI inference. Edge inference accelerates the response time of ML ...