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5 questions CIOs must ask after Southwest Airlines’ failure

CIO

IT and infrastructure from the 1990s,” said Casey A. In 2017, Fast Company wrote that Southwest Airlines’ digital transformation “takes off” with an $800 million technology overhaul, but only $300 million was dedicated to new technology for operations. While weather may have been the root cause, the 16,000 flights canceled between Dec.

Airlines 361
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Should you build or buy generative AI?

CIO

In the shaper model, you’re leveraging existing foundational models, off the shelf, but retraining them with your own data.” Whether it’s text, images, video or, more likely, a combination of multiple models and services, taking advantage of generative AI is a ‘when, not if’ question for organizations.

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Don’t queue for the ski jump if you don’t know how to ski

The Agile Manager

As a learning exercise, it is fantastic. Deploy some fintech and get these people off the payroll already. I keep a record of what I do on individual stones, on how I configure machines and the maintenance I perform on them, and for the totality of activities I do in the workshop each day. But mistakes are expensive.

How To 40
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Legacy Modernization

The Agile Manager

Decades of poor architecture guidelines and lax developer discipline resulted in the commercial-off-the-shelf components of an ERP becoming inseparable from the custom code built around it. The exercise of assessing, modeling and dispositioning the landscape does offer valuable new ways of looking at legacy assets.

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

Netflix Tech

About two years ago, we, at our newly formed Machine Learning Infrastructure team started asking our data scientists a question: “What is the hardest thing for you as a data scientist at Netflix?” Our job as a Machine Learning Infrastructure team would therefore not be mainly about enabling new technical feats.

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MLOps and DevOps: Why Data Makes It Different

O'Reilly Media - Ideas

As with many burgeoning fields and disciplines, we don’t yet have a shared canonical infrastructure stack or best practices for developing and deploying data-intensive applications. The new category is often called MLOps. However, the concept is quite abstract. What does a modern technology stack for streamlined ML processes look like?

DevOps 142
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FSI Member Spotlight Episode #17 – Matt Beecher

Praxent

Then from there, we employ really three microservice products off of Fineuron. FSI Member Spotlight Episode #17: Challenges and opportunities surrounding banking data architecture and the pressures of digital transformation initiatives. Tim Hamilton: Matt, tell us what is Neocova, and the suite of products that you all have developed?

Banking 52