H100
H100 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 h100 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 h100, 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.
![Bart- A vintage llm [R]](https://preview.redd.it/27z2aamswclh1.png?width=640&crop=smart&auto=webp&s=ba36a31376435bcec7f675b732595ad9dd2641a7)
Bart- A vintage llm [R]
Unbounded Labs proudly introduces Bart, a 2.82B parameter LLM meticulously trained from scratch on a unique corpus of 20.1B tokens of English text predating 1931. After three months and a modest $800 investment, we’ve achieved a significant milestone: the best-performing vintage base model at its scale on Vintage CORE. Our research, detailed in a comprehensive article, explores the potential for LLMs to replicate historical scientific reasoning—a crucial step toward understanding AI originality. Explore Bart and our methodology at the links provided.

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.