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IT leaders look beyond LLMs for gen AI needs

CIO Business Intelligence

Along with code-generating copilots and text-to-image generators, which leverage a combination of LLMs and diffusion processing, LLMs are at the core of most generative AI experimentation in business today. And the benefits of MakeShift’s use of AI are beginning to multiply. It’s fabulous.”

IT 131
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What LinkedIn learned leveraging LLMs for its billion users

CIO Business Intelligence

Fits and starts As most CIOs have experienced, embracing emerging technologies comes with its share of experimentation and setbacks. Here, it was believed an LLM would help, as an oft-touted benefit of LLMs is their speed, enabling them to complete complex steps rapidly. The initial deliverables “felt lacking,” Bottaro said.

IT 139
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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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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 104
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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

3) How do we get started, when, who will be involved, and what are the targeted benefits, results, outcomes, and consequences (including risks)? encouraging and rewarding) a culture of experimentation across the organization. It is important to realize that the usual “hype cycle” rules prevail in such cases as this.

Strategy 290
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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.