Discover how CoreWeave’s bare-metal GPU clusters and new AI workloads could drive massive growth. Find out more about the ...

A reader objects to a defense of disparate-impact theory.

Health researchers need to fully understand the underlying assumptions to uncover cause and effect. Timothy Feeney and Paul Zivich explain Physicians ask, answer, and interpret myriad causal questions ...

You train the model once, but you run it every day. Making sure your model has business context and guardrails to guarantee reliability is more valuable than fussing over LLMs. We’re years into the ...

Statistical models predict stock trends using historical data and mathematical equations. Common statistical models include regression, time series, and risk assessment tools. Effective use depends on ...

Abstract: The debiased estimator is a crucial tool in statistical inference for high-dimensional model parameters. However, constructing such an estimator involves estimating the high-dimensional ...

If the hyperscalers are masters of anything, it is driving scale up and driving costs down so that a new type of information technology can be cheap enough so it can be widely deployed. The ...

AI inference uses trained data to enable models to make deductions and decisions. Effective AI inference results in quicker and more accurate model responses. Evaluating AI inference focuses on speed, ...

Expertise from Forbes Councils members, operated under license. Opinions expressed are those of the author. We are still only at the beginning of this AI rollout, where the training of models is still ...

ABSTRACT: This study explores the application of Bayesian econometrics in policy evaluation through theoretical analysis. The research first reviews the theoretical foundations of Bayesian methods, ...

A food fight erupted at the AI HW Summit earlier this year, where three companies all claimed to offer the fastest AI processing. All were faster than GPUs. Now Cerebras has claimed insanely fast AI ...