Annotations
Annotations on Beyond Market Intelligence: a running collection of 2 stories we have gathered and hand-picked because they are worth your time. Every post here touches on annotations in some way — the news, the analysis, the deep dives, and the occasional surprise find. Acme AI is the next-generation, AI-powered spreadsheet platform built to replace Excel and redefine how analysts, data scientists, and enterprise teams work with data. New stories are added to this page as we find them, so check back if you want to keep up with what is happening around annotations, or subscribe to the RSS feed to get them as soon as they are published. Browse the collection below, or head back to the homepage to see everything Beyond Market Intelligence is covering right now.
Are HMMs still used for unsupervised tasks? [D]
Hidden Markov Models (HMMs) remain a valuable baseline for unsupervised dataset exploration, particularly when seeking to uncover structure within unstructured data. While deep learning has advanced significantly, HMMs offer a robust, interpretable approach to identifying underlying patterns without annotations. Modern methods certainly exist, but HMMs' clarity and efficiency make them a worthwhile starting point. For those seeking to quantify uncertainty in their models, consider exploring Bayesian Neural Networks, as discussed in our article, "Beyond Point Predictions."
How To Build Your Own LLM Runtime From Scratch
Ever wondered what it takes to build an LLM inference runtime from the ground up? This comprehensive guide details that journey, walking you through the creation of a small runtime called annotated-llm-runtime, all while running on an H100. We explore the intricacies of managing weights and CUDA graphs, highlighting three key bugs that shaped the development process. Delve into the complexities of AI infrastructure—as explored further in "OpenAI’s AI spending spree has ballooned to $750B"—and empower yourself with a deeper understanding of LLM technology.