Train-to-Test scaling explained: How to optimize your end-to-end AI compute budget for inference

AI reasoning does not necessarily require spending huge amounts on frontier models. Instead, smaller models can yield ...
EDN

Purpose-built AI inference architecture: Reengineering compute design

Over the past several years, the lion’s share of artificial intelligence (AI) investment has poured into training infrastructure—massive clusters designed to crunch through oceans of data, where speed ...
JSTOR Daily

Multivariate Normal Inference based on Singly Imputed Synthetic Data under Plug-in Sampling

This is a preview. Log in through your library . Abstract In this paper we consider singly imputed synthetic data generated via plugin sampling under the multivariate normal model. Based on the ...
SiliconANGLE

Nvidia GTC 2026: Jensen Huang’s Groq ‘Mellanox moment’ and the inference land grab

Ahead of Nvidia Corp.’s GTC 2026 this week, we reiterate our thesis that the center of gravity in artificial intelligence is shifting from “How fast can you train?” to “How well can you serve?” ...
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 ...