Update README.md

README.md

@@ -9,7 +9,7 @@ massive thank you to [@silveroxides](https://huggingface.co/silveroxides) for ph
 > [!IMPORTANT]
 > # MIR (Machine Intelligence Resource)<br><br>A naming schema for AIGC/ML work.
 
-The MIR schema seeks to standardize and complete a hyperlinked network of model information, improving accessibility and reproducibility across the AI community.<br>
+The MIR classification format seeks to standardize and complete a hyperlinked network of model information, improving accessibility and reproducibility across the AI community.<br>
 The work is inspired by:
 - [AIR-URN](https://github.com/civitai/civitai/wiki/AIR-%E2%80%90-Uniform-Resource-Names-for-AI) project by [CivitAI](https://civitai.com/)
 - [Spandrel](https://github.com/chaiNNer-org/spandrel/blob/main/libs/spandrel/spandrel/__helpers/registry.py) library's super-resolution registry
@@ -21,9 +21,9 @@ Example:
 
 
 ```
- mir : model .    lora      .    hyper       :   flux-1
-  ↑      ↑         ↑               ↑               ↑
- [URI]:[Domain].[Architecture].[Implementation]:[Compatibility]
+ mir : model .    lora      .    hyper    :   flux-1
+  ↑      ↑         ↑               ↑            ↑
+ [URI]:[Domain].[Architecture].[Series]:[Compatibility]
 ```
 
 ## Definitions:
@@ -36,7 +36,7 @@ Like other URI schema, the order of the identifiers roughly indicates their spec
 `info`:  Static global neural network attributes, metadata with an identifier in the database<br>
 
 ### Architecture
-Generative or deep learning system architectures.
+Broad and general terms for system architectures.
 `dit`: Diffusion transformer, typically Vision Synthesis
 'unet': Unet diffusion structure
 `art` : Autoregressive transformer, typically LLMs
@@ -44,11 +44,11 @@ Generative or deep learning system architectures.
 `vae`: Variational Autoencoder
 etc
 
-### Implementation
-A broad definition spanning the field of techniques
+### Series
+Foundational network and technique types.
 
 ### Compatability
-Details of implementation based on version-breaking changes, configuration inconsistencies, or other conflicting indicators
+Implementation details based on version-breaking changes, configuration inconsistencies, or other conflicting indicators that have practical application.
 
 ### Goals
 - Standard identification scheme for **ALL** fields of ML-related development
@@ -59,13 +59,12 @@ Details of implementation based on version-breaking changes, configuration incon
 
 > <details> <summary>Why not use `diffusion`/`sgm`, `ldm`/`text`/hf.co folder-structure/brand or trade name/preprint paper/development house/algorithm</summary>
 >
-> - Exact frameworks (SGM/LDM/RectifiedFlow) includes too few
-> - Diffusion/Transformer are too broad, share and overlap resources
-> - Multimodal models mix and complicate content terms (Text/Image/Vision/etc)
-> - HF.CO names do all of this & become inconsistent across folders/files, neglect many important developments
+> - The format here isnt finalized, but overlapping resource definitions or complicated categories that are difficult to narrow have been pruned
+> - Likewise, definitions that are too specific have also been trimmed
+> - HF.CO become inconsistent across folders/files and often the metadata enforcement of many important developments is neglected
 > - Development credit often shared, [Paper heredity tree](https://www.connectedpapers.com/search?q=generative%20diffusion), super complicated
 > - Algorithms (esp application) are less common knowledge, vague, ~~and I'm too smooth-brain.~~
-> - Impartiality
+> - Overall an attempt at impartiality and neutrality with regards to brand/territory origins
 > </details>
 
 > <details><summary>Why `unet`, `dit`, `lora` over alternatives</summary>
@@ -73,12 +72,13 @@ Details of implementation based on version-breaking changes, configuration incon
 > - UNET/DiT/Transformer are shared enough to be genre-ish but not too narrowly specific
 > - Very similar technical process on this level
 > - Functional and efficient for random lookups
+> - Short to type
 > </details>
 
 > <details><summary>Roadmap</summary>
 > 
-> - Decide on `@` (like @8cfg for an indistinguishable 8 step lora that requires cfg)
-> -- crucial spec element, or an optional, MIR app-determined feature?
+> - Decide on `@` or `:` delimeters (like @8cfg for an indistinguishable 8 step lora that requires cfg)
+> - crucial spec element, or an optional, MIR app-determined feature?
 > - Proof of concept generative model registry 
 > - Ensure compatability/integration/cross-pollenation with [OECD AI Classifications](https://oecd.ai/en/classification)
 > - Ensure compatability/integration/cross-pollenation with [NIST AI 200-1 NIST Trustworthy and Responsible AI](https://www.nist.gov/publications/ai-use-taxonomy-human-centered-approach)