Decomposition
Decomposition 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 decomposition 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 decomposition, 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.
Presentation: From DVDs to Global Streaming: How Netflix’s Commerce Architecture Actually Evolved
Join us as Kasia Trapszo illuminates Netflix’s remarkable journey, transforming from a U.S.-based DVD service to a global streaming powerhouse. This presentation details the evolution of their commerce architecture, navigating complex international payments, regulatory hurdles, and the shift from monolithic systems to domain-driven design. Discover how Netflix re-architected its infrastructure to handle massive live-event demand, demonstrating the enduring principle that exceptional systems thrive through continuous adaptation. For deeper insights into flexible data workflows, explore "AWS Introduces Specification Driven Composition."
ExTernD: Expanded-Rank Ternary Decomposition Ternary LLM PTQ with Accuracy Approaching Any Quantization Level [P]
ExTernD introduces a novel approach to Post-Training Quantization (PTQ) for Large Language Models, resolving a critical limitation of traditional ternary quantization. Unlike fixed-size methods that plateau in accuracy, ExTernD decomposes matrices into ternary components alongside a scalable diagonal scaling matrix. This innovative architecture allows for arbitrarily fine-grained accuracy control with a minimal increase in VRAM—often comparable to existing quantization techniques. Explore the full details of this transformative method in the arXiv paper: [https://arxiv.org/pdf/2607.13511](https://arxiv.org/pdf/2607.13511).