KDnuggets

8 LLM Inference Frameworks You Should Try in 2026

Compare LLM inference frameworks for production serving, request batching, KV cache management, and efficient deployment.
BIOENGINEER

New Methods Tame Bayesian Inference When Prior Covariances Lose Rank

Researchers have introduced new dimension and model reduction methods that extend optimal Bayesian inference to problems with ...
The Motley Fool

The AI Infrastructure Market Is Shifting to Inference. 5 Stocks to Play This Future $1.3 Trillion Market Opportunity

Nvidia and Cerebras both have SRAM-based solutions that could make them leaders in inference. AMD's chiplet design lets it package its chips with more HBM, a memory technology invented by memory ...
Scientific Research Publishing

Sivia, D. and Skilling, J. (2006) Data Analysis: A Bayesian Tutorial. Oxford University Press.

ABSTRACT: This work introduces a novel Bayesian inspired regression method for the simultaneous estimation of model parameters and data uncertainties. The key mathematical result of this framework is ...
GitHub

Bayesian Data Analysis for Statistical Causal Inference

This repository contains the material for tutorials on two topics constituting a paradigm shift for analyzing quantitative data from empirical studies: Statistical causal inference (SCI): a framework ...
bis.org

Quantum Bayesian inference: an exploration

We explore how quantum computation – a computing method based on the principles of quantum physics – could be applied to Bayesian inference – an approach to updating beliefs and making predictions ...
EDN

The truth about AI inference costs: Why cost-per-token isn’t what it seems

The AI industry has converged on a deceptively simple metric: cost per token. It’s easy to understand, easy to compare, and easy to market. Every new system promises to drive it lower. Charts show ...
TechCrunch

Startup Gimlet Labs is solving the AI inference bottleneck in a surprisingly elegant way

Stanford adjunct professor and successfully exited founder Zain Asgar just raised an $80 million Series A for a startup that solve the AI inference bottleneck problem in an astute way. The round was ...
Forbes

How AI Inference Costs Are Reshaping The Cloud Economy

While the tech world obsesses over headlines about the $100 million price tag to train GPT-4, the real economic story is happening in inference: the ongoing cost of actually running AI models in ...
marktechpost

A Coding Implementation of a Complete Hierarchical Bayesian Regression Workflow in NumPyro Using JAX-Powered Inference and Posterior Predictive Analysis

In this tutorial, we explore hierarchical Bayesian regression with NumPyro and walk through the entire workflow in a structured manner. We start by generating synthetic data, then we define a ...
Frontiers

A hierarchical Bayesian inference model for volatile multivariate exponentially distributed signals

Brain activities often follow an exponential family of distributions. The exponential distribution is the maximum entropy distribution of continuous random variables in the presence of a mean. The ...