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THE ML ENGINEER 🤖 Issue #112   This week in Issue #112:   Misinformation: Tech & Solutions Metadata Management Systems Papers With Code Datasets AI & ML Platforms in 2021 AI Regulatory Proposals Featured OSS Production ML Libraries Awesome AI Guidelines to check out this week + more 🚀   Forward  email, or share the online version on 🐦 Twitter,  💼 Linkedin and  📕 Facebook!   If you would like to suggest articles, ideas, papers, libraries, jobs, events or provide feedback just hit reply or send us an email to a@ethical.institute! We have received a lot of great suggestions in the past, thank you very much for everyone's support!       Misinformation: Tech & Solutions This week we are organising an online meetup on "Misinformation and Bias", where Dr. Magdalena Liz will cover how are governments and companies tackling issues related to this topic. Dr. Magdalena is an advisor for the Centre for Data Ethics & Innovation, a body established by the government to advise on challenges & opportunities of AI.       Metadata Management Systems As companies embrace digital technologies to transform their operations and products, many are using best-of-breed software, open source tools, and software as a service (SaaS) platforms to rapidly and efficiently integrate new technologies which results in growing metadata sources - this blog post provides an overview of the ecosystem of metadata management systems.       Papers With Code Datasets PapersWithCode has launched their datasets component; they are now indexing 3000+ research datasets from machine learning. This enables users to find datasets by task and modality, compare usage over time, browse benchmarks, and more. You can now explore the live dataset in their new section.       AI & ML Platforms in 2021 A comprehensive analysis of machine learning platforms in 2021. This article dives into machine learning frameworks and plaforms across a broad range of quadrants, covering from cloud / onprem, to specialised / end-to-end.       AI Regulatory Proposals Synced has compiled a global list of proposals, rules and regulatory frameworks for AI introduced in 2020, covering Ai governance frameworks, whitepapers, executive orders and beyond.       OSS: GPU Accel. Frameworks   The topic for this week's featured production machine learning libraries is GPU Acceleration Frameworks. We are currently looking for more libraries to add - if you know of any that are not listed, please let us know or feel free to add a PR. The four featured libraries this week are:   Vulkan Kompute - Blazing fast, lightweight and mobile phone-enabled Vulkan compute framework optimized for advanced GPU data processing usecases. CuPy - An implementation of NumPy-compatible multi-dimensional array on CUDA. CuPy consists of the core multi-dimensional array class, cupy.ndarray, and many functions on it. Jax - Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more CuDF - Built based on the Apache Arrow columnar memory format, cuDF is a GPU DataFrame library for loading, joining, aggregating, filtering, and otherwise manipulating data.   If you know of any libraries that are not in the "Awesome MLOps" list, please do give us a heads up or feel free to add a pull request!        OSS: Awesome AI Guidelines   As AI systems become more prevalent in society, we face bigger and tougher societal challenges. We have seen a large number of resources that aim to takle these challenges in the form of AI Guidelines, Principles, Ethics Frameworks, etc, however there are so many resources it is hard to navigate. Because of this we started an Open Source initiative that aims to map the ecosystem to make it simpler to navigate. You can find multiple principles in the repo - some examples include the following:   AI & Machine Learning 8 principles for Responsible ML - The Institute for Ethical AI & Machine Learning has put together 8 principles for responsible machine learning that are to be adopted by individuals and delivery teams designing, building and operating machine learning systems An Evaluation of Guidelines - The Ethics of Ethics; A research paper that analyses multiple Ethics principles ACM's Code of Ethics and Professional Conduct - This is the code of ethics that has been put together in 1992 by the Association for Computer Machinery and updated in 2018 From What to How - An initial review of publicly available AI Ethics Tools, Methods and Research to translate principles into practices   If you know of any guidelines that are not in the "Awesome AI Guidelines" list, please do give us a heads up or feel free to add a pull request!        © 2018 The Institute for Ethical AI & Machine Learning