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5 hot IT budget investments — and 2 going cold

CIO

The numbers are higher from Foundry’s 2023 State of CIO survey , which finds that 91% of CIOs expect their tech budgets to either increase or stay the same in 2023. CIOs anticipate an increased focus on cybersecurity (70%), data analysis (55%), data privacy (55%), AI/machine learning (55%), and customer experience (53%).

Budget 218
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See clearly, spend wisely: The power of data platform observability

Xebia

Diverse User Roles and Decentralized Teams: Amplifying the Cost Challenge One of the greatest strengths of modern data platforms is their ability to support a wide variety of usersdata engineers, analysts, scientists, and even business stakeholders. This approach ensures that decisions are made with both performance and budget in mind.

Data 130
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See clearly, spend wisely: The power of data platform observability

Xebia

Diverse User Roles and Decentralized Teams: Amplifying the Cost Challenge One of the greatest strengths of modern data platforms is their ability to support a wide variety of usersdata engineers, analysts, scientists, and even business stakeholders. This approach ensures that decisions are made with both performance and budget in mind.

Data 130
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Galileo emerges from stealth to streamline AI model development

TechCrunch

After all, AI is costly — Gartner predicted in 2021 that a third of tech providers would invest $1 million or more in AI by 2023 — and debugging an algorithm gone wrong threatens to inflate the development budget. ” Chatterji has a background in data science, having worked at Google for three years at Google AI.

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TinyML: The challenges and opportunities of low-power ML applications

O'Reilly Media - Data

Pete Warden has an ambitious goal: he wants to build machine learning (ML) applications that can run on a microcontroller for a year using only a hearing aid battery for power. Turning off the radio inverts our models for machine learning on small devices. And it draws 1.6 And why do we want to build them?

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What is DataOps? Collaborative, cross-functional analytics

CIO

DataOps (data operations) is an agile, process-oriented methodology for developing and delivering analytics. It brings together DevOps teams with data engineers and data scientists to provide the tools, processes, and organizational structures to support the data-focused enterprise. What is DataOps?

Analytics 195
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AI Chihuahua! Part I: Why Machine Learning is Dogged by Failure and Delays

d2iq

Going from a prototype to production is perilous when it comes to machine learning: most initiatives fail , and for the few models that are ever deployed, it takes many months to do so. As little as 5% of the code of production machine learning systems is the model itself. Adapted from Sculley et al.