Issue #200 - THE ML ENGINEER ??
Alejandro Saucedo
Tech Executive @ Zalando | Chair/Advisor @ UN, ACM, LF, etc | Join 60k+ ML Newsletter
Today we celebrate together our 200th Issue ?? This is a big milestone as we also celebrate various achievements including:?
We want to thank YOU for supporting our work, we are looking forward to continue driving forward & contributing to the conversations of ML engineering ?? Bring on 200 more!
As always you can access the Web Newsletter Homepage as well as the Linkedin Newsletter Homepage where you can find all previous editions ??
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This week in the MLE #200:?
If you would like to suggest articles, ideas, papers, libraries, jobs, events or provide feedback just hit reply or send us an email to [email protected]! We have received a lot of great suggestions in the past, thank you very much for everyone's support!
The State of AI Report analyses the most interesting developments in AI. This report aims to trigger an informed conversation about the state of AI and its implication for the future. It includes fantastic insigths around revelopments and predictions across research, industry, politics and beyond.
Kubernetes is becoming a common substrate for AI that allows for workloads to be run either in the cloud or in its own data center, and to easily scale. Join us next week at the Kubernetes AI Day where we'll be doing the opening keynote, following a fantastic set of sessions on cloud native AI.
A brief but insightful twitter discussion involving DL Reseracher Sebastian Raschka highlights the astonishing developments in the NLP space which allows for almost any individual to easily achieve state-of-the-art-level perfromance on text classification tasks through available open pre-trained models. This example showcases astonishing results with truly minimal effort.
Engineering teams often face the redesign the data models & systems they use. In production environments, this might mean migrating millions of active objects and refactoring thousands of lines of code. Stripe provides a fantastic resource where they summarise their experience and lessons learned performing a large scale migration.
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OpenAI introduces an exciting new initiative through the codename "Whisper", a neural net that approaches human level robustness and accuracy on speech recognition. This article provides intuitive details on the approach, architecture and results.
Upcoming MLOps Events
The MLOps ecosystem continues to grow at break-neck speeds, making it ever harder for us as practitioners to stay up to date with relevant developments. A fantsatic way to keep on-top of relevant resources is through the great community and events that the MLOps and Production ML ecosystem offers. This is the reason why we have started curating a list of upcoming events in the space, which are outlined below.
Conferences we'll be speaking at:
Other relevant upcoming MLOps conferences:
Open Source MLOps Tools
Check out the fast-growing ecosystem of production ML tools & frameworks at the github repository which has reached over 10,000 ? github stars. 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. Four featured libraries in the GPU acceleration space are outlined below.
If you know of any open source and open community events that are not listed do give us a heads up so we can add them!
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:
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!
About us ? The Institute for Ethical AI & Machine Learning is a UK-based research centre that carries out world-class research into responsible machine learning.