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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. Development velocity grinds to a halt.

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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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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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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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LLMOps for Your Data: Best Practices to Ensure Safety, Quality, and Cost

Speaker: Shreya Rajpal, Co-Founder and CEO at Guardrails AI & Travis Addair, Co-Founder and CTO at Predibase

Large Language Models (LLMs) such as ChatGPT offer unprecedented potential for complex enterprise applications. However, productionizing LLMs comes with a unique set of challenges such as model brittleness, total cost of ownership, data governance and privacy, and the need for consistent, accurate outputs.

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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.

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What to expect from AI in the enterprise in 2025

CIO Business Intelligence

This is particularly true with enterprise deployments as the capabilities of existing models, coupled with the complexities of many business workflows, led to slower progress than many expected. Foundation models (FMs) by design are trained on a wide range of data scraped and sourced from multiple public sources.

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Supply Chain Network Design Use Cases; From Lowering Cost to Going Green

Speaker: Aanand Pandey and Catalina Perez

Need to lower your supply chain costs, speed up delivery times or decrease carbon emissions? Modeling carbon cost. In 30 minutes, we’ll cover the supply chain challenge(s), how AIMMS Network Design solved them and the business outcomes and benefits. Start optimizing your supply chain!