RFC: Creating SIG TF.js

rfcs/20200916-sig-tf-js.md

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+# Creating SIG TF.js
+
+| Status        | Proposed      |
+:-------------- |:---------------------------------------------------- |
+| **RFC #**     | 
+| **Author(s)** | Ping Yu (piyu@google.com), Sandeep Gupta (sandeepngupta@google.com) |
+| **Sponsor**   | Thea Lamkin (thealamkin@google.com)                  |
+| **Updated**   | 2020-09-16                                           |
+
+## Objective
+
+We propose to create a Tensorflow SIG to facilitate community-contributed components 
+to tensorflow/tfjs. This document outlines the context goals, and engagement plan for 
+the proposed Special Interest Group.
+
+## Context
+
+JavaScript is a very versatile and widely-used language. With TensorFlow.js, web application 
+developers and JS developers can now use Machine Learning with TensorFlow in their JS 
+applications. TensorFlow.js is the leading framework for ML in JavaScript with huge user growth 
+(2.1M npm downloads, more than 2x YoY growth in the number of avg daily downloads). With the 
+growth of the library, we now support an increasing number of use cases across a variety of 
+platforms and backends, with many more models, use-cases, and applications. 
+
+The core TensorFlow.js engineering team has been working on building the infrastructure and 
+tooling to enable ML to run in JavaScript powered applications, as well as adding support for 
+more types of models. TensorFlow.js has more than 220 contributors on GitHub which include many 
+passionate contributors (individual developers, GDEs, and enterprise users) who have been active 
+participants in the TensorFlow.js ecosystem. We want to accelerate the community involvement in 
+the project to help continue meet the needs and help drive new directions for the project. 
+
+## Goals & Objectives
+
+We welcome community contributions on any area of TensorFlow.js, but the SIG will be focused on 
+the following goals:
+- Driving TensorFlow.js features for Server-side execution with tfjs-node. This will include 
+building tooling and infra for end to end, production-ready ML with TensorFlow.js. 
+- Developing features for specific platforms and deployments (eg. React Native, IoT and embedded 
+devices, etc); 
+- Building workflows for Transfer learning features for customizing models
+- Adding support for newer models and application areas (eg. NLP, RL, etc), and data analysis 
+algorithms
+- Conducting research and implementing prototypes for client-side, privacy preserving ML and 
+Federated Learning. 
+- Identifying performance issues, tradeoffs, and requirements.
+- Model benchmarking across browsers, hardware and devices.
+- Model encryption.
+- Model visualization.
+- These projects will move towards community ownership as work streams mature. 
+
+
+## Membership
+
+We encourage any developers working at the intersection of machine learning and web/JS 
+applications to join and participate in the activities of the SIG. Whether you are working on 
+advancing the platform, prototyping or building specific applications, or authoring new libraries, 
+we welcome your feedback on and contributions to Tensorflow.js and its tooling, and are eager to hear 
+about any downstream results, implementations, and extensions. 
+
+We have multiple channels for participation, and publicly archive discussions in our user group and 
+announcements mailing lists:
+- tfjs@tensorflow.org -- our general mailing list that all are welcome to join ([archive group](https://groups.google.com/a/tensorflow.org/g/tfjs))
+- tfjs-announce@tensorflow.org -- Announcement only mailing list for TF.js community ([archive group](https://groups.google.com/a/tensorflow.org/g/tfjs-announce))
+
+We will create a new mailing list for TensorFlow.js SIG members. 
+
+### Other Resources 
+- Repository: https://github.com/tensorflow/tfjs
+- Documentation: https://www.tensorflow.org/js
+
+## Organization and Governance
+SIG project leads will be added to a SIG TF.js maintainers team on GitHub to streamline their 
+contributions to tensorflow/tfjs. As specific ideas and work streams develop, we will explore creating 
+new, community-owned repos that the SIG will drive.
+
+## Contacts
+### Project Lead(s):
+- Ping Yu (Google)
+- Sandeep Gupta (Google)
+- Ton Ngo (IBM): 
+  - Server side support (GPU, training)
+  - End-to-end pipeline on Kubernetes (Kubeflow)
+- Ricky Cao (Alibaba)
+  - Building tooling and infra for end to end, production-ready ML with TensorFlow.js.
+  - Pipeline with transfer learning
+  - Model Encryption
+- Ningxin Hu (Intel)
+  - Benchmarking and performance optimization
+- Gant Laborde (Infinite Red)
+  - Platforms (React and React Native)
+  - Adding support for newer models and application areas (eg. NLP, RL, etc),
+  - Model visualization
+
+### SIG members: 
+- Adam Bouhenguel (Tesserai)
+- Clément Walter (IBM)
+- Eric Li (Alibaba)
+- Mrinal Mathur (ARM)
+- Patrick Haralabidis (Carlisle Homes)
+- Paul Van Eck (IBM)
+- Saswat Samal (Student)
+- Shivay Lamba (Metvy)
+- Ted Chang (IBM)
+- Va Barbosa (IBM)
+- YiHong Wang (IBM)
+- Zebai (Alibaba)
+
+### Administrative questions: 
+- Thea Lamkin (Google): thealamkin at google dot org 
+- Joana Carrasqueira (Google): joanafilipa at google dot org
+- tf-community at tensorflow dot org
+
+### Meeting cadence: TBD