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THE ML ENGINEER 🤖
Issue #90
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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!
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Join us the following week at our online AI, Data & Ethics event, where Prof. Joanna Bryson will share her insights on AI, Data & Ethics in 2020, as well as on her research around accountability for and transparency in AI, technological impact on human cooperation, and beyond.
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OpenAI has published new research showing how they've applied reinforcement learning from human feedback to train language models that are better at summarization. They mention how their models generate summaries that are better than summaries from 10x larger models trained only with supervised learning.
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Recently new research showcased how you can transform the face of a video to look as if it was saying dynamically provided text, with only a sample of audio required. This is a great post that provides a brief overview of the recent paper (and surprising video) "A lip sync expert is all you need for speech to lip generation in the wild".
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Often getting started with ML can be quite challenging due to the sheer amount of resources available. The resource GettingStartedWithML is a community-driven effort to curate a set of tools for individuals to dive into the ML world.
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AI Operations is a topic that has been more widely discussed recently due to the importance of automated monitoring and observability of (and with) machine learning. Superwise.AI CEO Ofer Razon joins this week's Data Exchange podcast to discuss key insights in this space, such as solutions to evaluate models, receive alerts, validate insights, etc.
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The topic for this week's featured production machine learning libraries is Model Serving 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:
- KFServing - Serverless framework to deploy machine learning models in Kubernetes with KNative
- Seldon Core - Open source platform for deploying and monitoring models in kubernetes with rich DAG structures
- Cortex - Cortex is an open source platform for deploying machine learning models—trained with nearly any framework—as production web services.
- Tensorflow Serving - High-performant framework to serve Tensorflow models via grpc protocol able to handle 100k requests per second per core
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© 2018 The Institute for Ethical AI & Machine Learning
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The Institute for Ethical AI & Machine Learning
