Add topical organization for Sep 16

Author: anssiko

agenda/README.md

@@ -14,34 +14,48 @@
 
 [💡 "Opportunities and Challenges" discussion topics](https://github.com/w3c/machine-learning-workshop/issues?q=is%3Aissue+is%3Aopen+label%3A%22Opportunities+and+Challenges%22+sort%3Acomments-desc):
 
+## Improving existing web platform capabilities
+
 ℹ️ [WebGPU fitness for ML frameworks #66](https://github.com/w3c/machine-learning-workshop/issues/66) - @jasonmayes @Kangz @grorg
 - ❓ Does WebGPU expose the right API surface to support ML frameworks interactions with GPUs?
 - ✔️ Proposal: New WebGPU extensions for subgroups, cooperative matrix multiply.
 
+ℹ️ [Support for Float16 in JS & Wasm environments #64](https://github.com/w3c/machine-learning-workshop/issues/64) - @cynthia @jasonmayes
+- ❓ Lack of support for float16 in JS and Wasm environments problematic for quantized models.
+- ✔️ Proposal: TBD
+
+ℹ️ [Memory copies #93](https://github.com/w3c/machine-learning-workshop/issues/93) - @aboba @wchao1115
+- ❓ Machine learning apps within the browser using the media pipeline trigger many more memory copies compared with native applications hindering performance.
+- ✔️ Proposal: Introduce a more direct way to feed a video frame, possibly captured from a camera, to a ML model.
+
+ℹ️ [Permission model for Machine Learning APIs #72](https://github.com/w3c/machine-learning-workshop/issues/72) - @cynthia @dontcallmedom @anssiko
+- ❓ How to design a forward-looking permission model for ML APIs?
+- ✔️ Proposal: TBD
+
+## Extending beyond the browser
+
 ℹ️ [Applicability to non-browser JS environments #62](https://github.com/w3c/machine-learning-workshop/issues/62) - @jasonmayes @phoddie @huningxin @WenheLI
 - ❓ Pay attention to the applicability of the browser-targeted work to non-browser JS environments, in particular Node.js.
 - ✔️ Proposal: Extend W3C coordination to TC53 and non-browser projects.
 
+ℹ️ [Targeting WASI-NN and WebNN together #96](https://github.com/w3c/machine-learning-workshop/issues/96) - @mehmetoguzderin @mingqiusun @abrown
+- ❓ Should libraries for browsers and/or Wasm execution environments be able to target WebNN and WASI-NN together?
+- ✔️ Proposal: TBD
+
+## Considerations for creating and deploying models
+
 ℹ️ [Protecting ML models #67](https://github.com/w3c/machine-learning-workshop/issues/67) - @jasonmayes @tidoust @pyu10055 @jbingham
 - ❓ Some ML providers need to ensure their ML models cannot be extracted from a browser app.
 - ✔️ Proposal: Investigate existing access control mechanisms for video, learnings from 3D assets.
 
-ℹ️ [Support for Float16 in JS & Wasm environments #64](https://github.com/w3c/machine-learning-workshop/issues/64) - @cynthia @jasonmayes
-- ❓ Lack of support for float16 in JS and Wasm environments problematic for quantized models.
-- ✔️ Proposal: TBD
+ℹ️ [ML model format #74](https://github.com/w3c/machine-learning-workshop/issues/74) - @cynthia @jbingham @wchao1115
+- ❓ There is no standard format for packaging and shipping ML models, model formats evolve rapidly.
+- ✔️ Proposal: Initially focus on defining a Web API for accelerating established reusable ML operations instead of standardizing a model format.
 
 ℹ️ [In-browser training #82](https://github.com/w3c/machine-learning-workshop/issues/82) and [Training across devices #83](https://github.com/w3c/machine-learning-workshop/issues/83) - @irealva @cynthia
 - ❓ The current in-browser efforts are focused on inference rather than training.
 - ✔️ Proposal: Understand successful real-world usages (e.g. Teachable Machine) and target transfer learning as the initial training use case for related browser API work.
 
-ℹ️ [Memory copies #93](https://github.com/w3c/machine-learning-workshop/issues/93) - @aboba @wchao1115
-- ❓ Machine learning apps within the browser using the media pipeline trigger many more memory copies compared with native applications hindering performance.
-- ✔️ Proposal: Introduce a more direct way to feed a video frame, possibly captured from a camera, to a ML model.
-
-ℹ️ [Permission model for Machine Learning APIs #72](https://github.com/w3c/machine-learning-workshop/issues/72) - @cynthia @dontcallmedom @anssiko
-- ❓ How to design a forward-looking permission model for ML APIs?
-- ✔️ Proposal: TBD
-
 ## September 22, 2020, 2pm UTC [🗓️](https://www.timeanddate.com/worldclock/fixedtime.html?iso=20200922T14)
 
 >🔎 **Scope:** Web Platform Foundations for Machine Learning