Remove Off-The-Shelf Remove Open Source Remove Scalability
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Bank of America’s big bet on AI started small

CIO

Bank of America will invest $4 billion in AI and related technology innovations this year, but the financial services giants 7-year-old homemade AI agent, Erica, remains a key ROI generator , linchpin for customer and employee experience , and source of great pride today. We are not writing essays with Erica. Gopalkrishnan says.

Banking 170
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Open-Sourcing Metaflow, a Human-Centric Framework for Data Science

Netflix Tech

by David Berg , Ravi Kiran Chirravuri , Romain Cledat , Savin Goyal , Ferras Hamad , Ville Tuulos tl;dr Metaflow is now open-source! Get started at metaflow.org. Netflix applies data science to hundreds of use cases across the company, including optimizing content delivery and video encoding.

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Interpreting predictive models with Skater: Unboxing model opacity

O'Reilly Media - Data

There is also a trade off in balancing a model’s interpretability and its performance. We recognize the need for human interpretability, and we recently open sourced a Python framework called Skater as an initial step to enable interpretability for researchers and applied practitioners in the field of data science.

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Open-Sourcing Metaflow, a Human-Centric Framework for Data Science

Netflix Tech

by David Berg , Ravi Kiran Chirravuri , Romain Cledat , Savin Goyal , Ferras Hamad , Ville Tuulos tl;dr Metaflow is now open-source! Get started at metaflow.org. Netflix applies data science to hundreds of use cases across the company, including optimizing content delivery and video encoding.

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Black Box Machine Learning in the Cloud

Erik Bernhardsson

Focusing on a particular niche makes it easier to build something that works off the shelf. In a year’s time there will be open source libraries with pre-trained models for image classification that are on par with anything you can get through an API (probably better). Then there’s a ton of startups: PredictionIO ($2.7M

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MLOps and DevOps: Why Data Makes It Different

O'Reilly Media - Ideas

This is both frustrating for companies that would prefer making ML an ordinary, fuss-free value-generating function like software engineering, as well as exciting for vendors who see the opportunity to create buzz around a new category of enterprise software. The new category is often called MLOps. However, the concept is quite abstract.

DevOps 145
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Black Box Machine Learning in the Cloud

Erik Bernhardsson

Focusing on a particular niche makes it easier to build something that works off the shelf. In a year’s time there will be open source libraries with pre-trained models for image classification that are on par with anything you can get through an API (probably better). Then there’s a ton of startups: PredictionIO ($2.7M