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5 questions CIOs must ask after Southwest Airlines’ failure

CIO

CIOs know that tech issues get the trigger finger of blame when businesses experience operational disasters, but we also know there are culture and process issues that can be primary and often untold contributors — both well within the CIO’s purview. While weather may have been the root cause, the 16,000 flights canceled between Dec.

Airlines 361
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Buying advice for CIOs as low-code/no-code spending rises

CIO

A broad spectrum of tools has arisen to facilitate software development in the enterprise, from no-code platforms like Bubble and low-code drag-and-drop tools , both stand-alone and integrated into enterprise applications, to intelligent tools that use machine learning to suggest lines of code to professional developers as they work.

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Supporting Diverse ML Systems at Netflix

Netflix Tech

Berg , Romain Cledat , Kayla Seeley , Shashank Srikanth , Chaoying Wang , Darin Yu Netflix uses data science and machine learning across all facets of the company, powering a wide range of business applications from our internal infrastructure and content demand modeling to media understanding.

System 90
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What you need to know about product management for AI

O'Reilly Media - Ideas

If you’re already a software product manager (PM), you have a head start on becoming a PM for artificial intelligence (AI) or machine learning (ML). A lot to learn, but worthwhile to access the unique and special value AI can create in the product space. Why AI software development is different.

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Revolutionizing Business Operations with Future-Fit Software

Tandem

With the ever-expanding set of emerging technologies — big data, machine learning (ML), artificial intelligence (AI), next-gen user experiences (UI/UX), edge computing, the Internet-of-things (IoT), microservices, and Web3 — there is a huge surface area to address. Swift reconfiguration necessitates a shift in mindset and culture.

UI/UX 59
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7 data trends on our radar

O'Reilly Media - Ideas

Increasing focus on building data culture, organization, and training. In a recent O’Reilly survey , we found that the skills gap remains one of the key challenges holding back the adoption of machine learning. For most companies, the road toward machine learning (ML) involves simpler analytic applications.

Trends 86
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Managing machine learning in the enterprise: Lessons from banking and health care

O'Reilly Media - Ideas

As companies use machine learning (ML) and AI technologies across a broader suite of products and services, it’s clear that new tools, best practices, and new organizational structures will be needed. What cultural and organizational changes will be needed to accommodate the rise of machine and learning and AI?