awesome-annual-reviews-and-trends

A curated list of awesome year-in-review and annual trends / predictions for 2022, 2023 and beyond 🚀

https://github.com/ethicalml/awesome-annual-reviews-and-trends

Science Score: 52.0%

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CITATION.cff file
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Organization ethicalml has institutional domain (ethical.institute)
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Low similarity (10.5%) to scientific vocabulary

Last synced: 7 months ago · JSON representation ·

Repository

A curated list of awesome year-in-review and annual trends / predictions for 2022, 2023 and beyond 🚀

Basic Info

Host: GitHub
Owner: EthicalML
License: mit
Default Branch: main
Size: 83 KB

Statistics

Stars: 36
Watchers: 4
Forks: 3
Open Issues: 0
Releases: 0

Created about 3 years ago · Last pushed about 3 years ago

Metadata Files

Readme Contributing License Citation

Awesome Annual Tech Reviews & Predictions

This repository contains a curated list of awesome resources on year-in-review and tech predictions for 2022, 2023 and beyond 🚀

This list is a work in progress and would love your support adding more resources, please add any further suggestions as an issue or read the CONTRIBUTING.md to add as a PR!

Quick links to sections in this page

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🐰 2022-2023

Year-in-Review

🏢 Tech Companies

This section includes posts from renowned tech companies providing insights on technology fields, industry as a whole or specialised research fields (not products / promotions - as outlined in the CONTRIBUTING.md).

🔍 OSS Projects

This section contains year-in-review lists from Open Source Projects, as we hope to promote the great efforts and content that these projects provide. The ordering and selection for this list can be found in the CONTRIBUTING.md page - if there's any missing please add a pull request!

🤖 OSS Projects: AI & Data

Airflow - The Airflow Year in Review 2022

📜 OSS Projects: GameDev

Godot - Godot 2022: A Retrospective

🎅 OSS Projects: General Tech

🔒 OSS Projects: Security

Kubernetes - 2022 Kubernetes Vulnerabilities – Main Takeaways

💡 Thought Leaders and Non-Profits (TLaNP)

This section includes posts from renowned thought leaders and non-profits providing insights on technology fields, industry as a whole or specialised research fields (not products / promotions - as outlined in the CONTRIBUTING.md).

🤖 TLaNP: AI & Data

Algorithm Watch - The year automated systems might have been regulated: 2022 in review
Chip Huyen - MLOps Learners Discord: 2022 in review
Elvis Saravia - 2022: A Year in Review (ML Papers Edition)
Gradient Flow - Top Pics
Jesper Dramsch - Top ML Links in 2022
Louis Bouchard - 2022: A Year Full of Amazing AI papers- A Review 🚀
The Batch - Top AI Stories of 2022
State of AI - State of AI Report

🎅 TLaNP: General Programming

Chip Huyen - Books that made me think (as an engineer)
Eugene Yan - 2022 in Review & 2023 Goals
Sebastian Raschka - Year in Review

Predictions

This section on predictions is still a work in progress (hence not many resources yet), help us find further predictions from renwoned organisations and thought leaders for 2022-2023!

Casey Newton, Founder, Platformer - 13 predictions for tech platforms in 2023
Dr. Werner Vogels, VP and CTO at Amazon - 5 tech predictions for 2023 and beyond, according to Amazon CTO Dr. Werner Vogels

Owner

Name: The Institute for Ethical Machine Learning
Login: EthicalML
Kind: organization
Email: a@ethical.institute
Location: United Kingdom

Website: http://ethical.institute
Twitter: EthicalML
Repositories: 8
Profile: https://github.com/EthicalML

The Institute for Ethical Machine Learning is a think-tank that brings together with technology leaders, policymakers & academics to develop standards for ML.

Citation (CITATION.cff)

# This CITATION.cff file was generated with cffinit.
# Visit https://bit.ly/cffinit to generate yours today!

cff-version: 0.0.1
title: Awesome Annual Reviews and Trends
message: 'If you use this list in your publication, please cite it as follows.'
type: dataset
authors:
  - given-names: Alejandro
    family-names: Saucedo
repository-code: >-
  https://github.com/EthicalML/awesome-production-machine-learning
abstract: >-
  This repository contains a curated list of awesome resources on year-in-review and tech predictions for 2022, 2023 and beyond 🚀 
license: MIT

GitHub Events

Total

Watch event: 2

Last Year

Watch event: 2

Issues and Pull Requests

Last synced: about 1 year ago

All Time

Total issues: 0
Total pull requests: 1
Average time to close issues: N/A
Average time to close pull requests: about 2 hours
Total issue authors: 0
Total pull request authors: 1
Average comments per issue: 0
Average comments per pull request: 1.0
Merged pull requests: 1
Bot issues: 0
Bot pull requests: 0

Past Year

Issues: 0
Pull requests: 0
Average time to close issues: N/A
Average time to close pull requests: N/A
Issue authors: 0
Pull request authors: 0
Average comments per issue: 0
Average comments per pull request: 0
Merged pull requests: 0
Bot issues: 0
Bot pull requests: 0