A significant shift is under way in artificial intelligence, and it has huge implications for technology companies big and small. For the past half-decade, most of the focus in AI has been on training ...

Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. Dany Lepage discusses the architectural ...

Abstract: Bayesian inference provides a methodology for parameter estimation and uncertainty quantification in machine learning and deep learning methods. Variational inference and Markov Chain ...

Animals survive in changing and unpredictable environments by not merely responding to new circumstances, but also, like humans, by forming inferences about their surroundings—for instance, squirrels ...

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 ...

Easily build Bayesian models from parts, abstract away the boilerplate, and tweak priors as you wish. Inspiration from Keras and Tensorflow Probability, but made specifically for Numpyro + Jax.

We cover a lot of debates on this program about policy, ethics, the law. Well, here's another one that draws strong opinions. Does listening to an audiobook count as reading? Andrew Limbong, host of ...

You’re reading Open Questions, Joshua Rothman’s weekly column exploring what it means to be human. What do you read, and why? A few decades ago, these weren’t urgent questions. Reading was an ...

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, ...