Tag Archive: Machine learning

Evaluation Survey Insights

In September 2023 we conducted a survey with the MLOps Community on evaluating LLM systems. More than 115 people participated. All of the response data is free for anyone to look at and examine. We encourage you to dig into... View article

Become the Maestro of your MLOps Abstractions

The MLOps ecosystem is evolving into a sophisticated symphony, composed of diverse tools, methodologies, and cultures. This diversity, while beneficial, also introduces a complexity reminiscent of the challenges encountered in Big Data systems. Data experts had to navigate through immense data... View article

AI Tidbits 2023 SOTA Report

Looking back at 2023’s advancements to gauge how far we’ve come since 2022 Note: “SOTA” stands for state-of-the-art, referring to the most advanced and effective models currently available in the field. Exactly a year ago, ChatGPT was one month old,... View article

ML Proverbs

Model Maxims & Data DogmasThis article was originally published on Leonard’s Substack. In the same vein as Rob Pike’s Go Proverbs, engineers relish a good aphorism. I’ve tried to consolidate these frequent murmurs of the ML/AI community into somewhat tangible anchors:... View article

Explainable AI: Visualizing Attention in Transformers

And logging the results in an experiment-tracking tool In this article, we explore one of the most popular tools for visualizing the core distinguishing feature of transformer architectures: the attention mechanism. Keep reading to learn more about BertViz and how... View article

Is AI/ML Monitoring just Data Engineering? 🤔

While the future of machine learning and MLOps is being debated, practitioners still need to attend to their machine learning models in production. This is no easy task, as ML engineers must constantly assess the quality of the data that... View article

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