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Beyond “Prompt and Pray”

O'Reilly on Data

This approach delivers substantial benefits: consistent execution, lower costs, better security, and systems that can be maintained like traditional software. This fueled a belief that simply making models bigger would solve deeper issues like accuracy, understanding, and reasoning. Its quick to implement and demos well.

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7 ways gen AI can create more work than it saves

CIO Business Intelligence

One is going through the big areas where we have operational services and look at every process to be optimized using artificial intelligence and large language models. But a substantial 23% of respondents say the AI has underperformed expectations as models can prove to be unreliable and projects fail to scale.

IT 141
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How will AI agents be priced? CIOs need to pay attention

CIO Business Intelligence

So far, no agreement exists on how pricing models will ultimately shake out, but CIOs need to be aware that certain pricing models will be better suited to their specific use cases. Lots of pricing models to consider The per-conversation model is just one of several pricing ideas.

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Marsh McLennan IT reorg lays foundation for gen AI

CIO Business Intelligence

It’s a full-fledged platform … pre-engineered with the governance we needed, and cost-optimized. One of the world’s largest risk advisors and insurance brokers launched a digital transformation five years ago to better enable its clients to navigate the political, social, and economic waves rising in the digital information age.

IT 122
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Cost, security, and flexibility: the business case for open source gen AI

CIO Business Intelligence

Travel and expense management company Emburse saw multiple opportunities where it could benefit from gen AI. To solve the problem, the company turned to gen AI and decided to use both commercial and open source models. Both types of gen AI have their benefits, says Ken Ringdahl, the companys CTO.

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The key to operational AI: Modern data architecture

CIO Business Intelligence

Recent research shows that 67% of enterprises are using generative AI to create new content and data based on learned patterns; 50% are using predictive AI, which employs machine learning (ML) algorithms to forecast future events; and 45% are using deep learning, a subset of ML that powers both generative and predictive models.

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CIOs face mounting pressure as AI costs and complexities threaten enterprise value

CIO Business Intelligence

CIOs are under increasing pressure to deliver meaningful returns from generative AI initiatives, yet spiraling costs and complex governance challenges are undermining their efforts, according to Gartner. hours per week by integrating generative AI into their workflows, these benefits are not felt equally across the workforce.