hierarchical structure
hierarchical structure 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 hierarchical structure 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 hierarchical structure, 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.
![[R] Using AI as a spatial software generator to create 3D objects that are inherently programmable](https://external-preview.redd.it/q3evP6JeDpAC2MdSQHWYxnCYTqbJkElIQsLFqVSdkss.png?width=640&crop=smart&auto=webp&s=de730fbf7ecace6df0036b21470c16a2d4feacfb)
[R] Using AI as a spatial software generator to create 3D objects that are inherently programmable
Our research explores a transformative approach to 3D object creation: leveraging AI as a spatial software generator. This work, co-authored by myself, establishes a foundational understanding of 3D structures born from LLMs through spatial programming—a paradigm shift away from static mesh generation. Discover how these inherently programmable objects, demonstrated at [https://nova3d.xyz/](https://nova3d.xyz/), enable animation and adaptive performance across diverse computing environments. As LLMs refine spatial coding, expect significant disruption in industrial design, game development, and immersive technologies—a concept further explored in "Is Agentic AI Just Automation?".
My OCR model mislabels section titles as body text. Is a CRF the right fix, or am I overcomplicating it? [P]
Addressing OCR mislabeling of section titles as body text presents a common challenge in document structure extraction. Given the inconsistencies in DeepSeek-OCR’s labeling and the hierarchical nature of your legal documents, a Conditional Random Field (CRF) appears a reasonable, albeit potentially complex, solution. Leveraging both textual content and geometric features—like indentation, alignment, and numbering patterns—within a sequence labeling framework offers a robust approach to refining title detection beyond simple heuristics. Consider evaluating a CRF against a rule-based system to determine optimal performance.