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What LinkedIn learned leveraging LLMs for its billion users

CIO Business Intelligence

During the summer of 2023, at the height of the first wave of interest in generative AI, LinkedIn began to wonder whether matching candidates with employers and making feeds more useful would be better served with the help of large language models (LLMs). Cost considerations One aspect that Bottaro dubbed “a hurdle” was the cost.

IT 139
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Ferrovial puts AI at the heart of its transformation

CIO Business Intelligence

With the aim to accelerate innovation and transform its digital infrastructures and services, Ferrovial created its Digital Hub to serve as a meeting point where research and experimentation with digital strategies could, for example, provide new sources of income and improve company operations.

IT 105
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13 IT resolutions for 2024

CIO Business Intelligence

What benefit does AI serve to that department? Bring the whole organization on the AI journey CIOs also see the need to bring everyone along on that AI journey, something that takes a well-articulated narrative about the benefits AI can bring to those who are and will be impacted by the technology. We’re piloting, PoC-ing.

IT 144
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7 steps for turning shadow IT into a competitive edge

CIO Business Intelligence

Ask IT leaders about their challenges with shadow IT, and most will cite the kinds of security, operational, and integration risks that give shadow IT its bad rep. That’s not to downplay the inherent risks of shadow IT. There are ample reasons why 77% of IT professionals are concerned about shadow IT, according to a report from Entrust.

IT 137
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Business Strategies for Deploying Disruptive Tech: Generative AI and ChatGPT

Rocket-Powered Data Science

While generative AI has been around for several years , the arrival of ChatGPT (a conversational AI tool for all business occasions, built and trained from large language models) has been like a brilliant torch brought into a dark room, illuminating many previously unseen opportunities.

Strategy 289
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Your New Cloud for AI May Be Inside a Colo

CIO Business Intelligence

Enterprises moving their artificial intelligence projects into full scale development are discovering escalating costs based on initial infrastructure choices. Many companies whose AI model training infrastructure is not proximal to their data lake incur steeper costs as the data sets grow larger and AI models become more complex.

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What Is Model Risk Management and How is it Supported by Enterprise MLOps?

Domino Data Lab

Model Risk Management is about reducing bad consequences of decisions caused by trusting incorrect or misused model outputs. Systematically enabling model development and production deployment at scale entails use of an Enterprise MLOps platform, which addresses the full lifecycle including Model Risk Management.