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10 best practices when partnering for strategic skills

CIO

In addition to AI and machine learning, data science, cybersecurity, and other hard-to-find skills , IT leaders are also looking for outside help to accelerate the adoption of DevOps or product-/program-based operating models. Many of the new skills are in rare supply, as are team leaders experienced in this new development paradigm.”

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Extra Crunch roundup: Klaviyo EC-1, micromobility’s second wave, UiPath CFO interview, more

TechCrunch

“Whether you want to stack regulatory compliance on the vehicles, do safety features like ADAS or add mapping content, you kind of need this platform where you can actively develop and launch new apps on the vehicle without having to bring it back to the factory,” Meruva said. Scale quicker. Scale cheaper. Scale right.

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Seven Legal Questions for Data Scientists

O'Reilly Media - Ideas

Variants of artificial intelligence (AI), such as predictive modeling, statistical learning, and machine learning (ML), can create new value for organizations. Although many organizations wait until there’s an incident to call in legal help, compliance by design saves resources and reputations.

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How To Build A Fintech App In 2022

Existek

Fintech applications prevail in the financial sphere, but the process of their development doesn’t look easy at the first glance. What tech stack to choose to implement the trending functionality, and how to estimate the final development price? They are insurance, investment, lending, banking, and consumer finance apps.

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Machine Learning Project Checklist

DataRobot

Download the Machine Learning Project Checklist. Planning Machine Learning Projects. Machine learning and AI empower organizations to analyze data, discover insights, and drive decision making from troves of data. More organizations are investing in machine learning than ever before.

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What to Do When AI Fails

O'Reilly Media - Ideas

While incident response is a field that’s well developed in the traditional cybersecurity world, it has no clear analogue in the world of AI. And last is the probabilistic nature of statistics and machine learning (ML). What is an incident when it comes to an AI system? Second is AI’s tremendous complexity.

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