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10 most difficult-to-fill IT roles — and how to address the gap

CIO

CIO.com’s 2023 State of the CIO survey recently zeroed in on the technology roles that IT leaders find the most difficult to fill, with cybersecurity, data science and analytics, and AI topping the list. The 2022 ISC2 Cybersecurity Workforce Study calculated a cybersecurity workforce gap of 3.4 The net result?

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CIOs confront generative AI’s workplace X factor

CIO

In the rush to establish technical strategies for making good on the promise of generative AI, many CIOs find themselves running headlong into what may be their most challenging task yet: preparing their organization’s end-users — from knowledge workers and assembly line laborers to doctors, accountants, and lawyers — to co-exist with generative AI.

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Architect defense-in-depth security for generative AI applications using the OWASP Top 10 for LLMs

AWS Machine Learning - AI

Many customers are looking for guidance on how to manage security, privacy, and compliance as they develop generative AI applications. This post provides three guided steps to architect risk management strategies while developing generative AI applications using LLMs.

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Rethinking the IT talent pipeline

CIO

Amanda Merola had zero technical background when she came to The Hartford in 2015, despite a natural interest in computers and a proclivity for problem-solving. You used to be able to buy people or rely on the education system to pull people through so there was a ready supply of trained technical people.

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The rise of the data lakehouse: A new era of data value

CIO

The result is an emerging paradigm shift in how enterprises surface insights, one that sees them leaning on a new category of technology architected to help organizations maximize the value of their data. Enter the data lakehouse. You can intuitively query the data from the data lake.

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Technology Trends for 2024

O'Reilly Media - Ideas

That may or may not be advisable for career development, but it’s a reality that businesses built on training and learning have to acknowledge. 1 That makes sense, given the more technical nature of our audience. Data analysis and databases Data engineering was by far the most heavily used topic in this category; it showed a 3.6%

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