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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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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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Agentic AI design: An architectural case study

CIO Business Intelligence

From obscurity to ubiquity, the rise of large language models (LLMs) is a testament to rapid technological advancement. Just a few short years ago, models like GPT-1 (2018) and GPT-2 (2019) barely registered a blip on anyone’s tech radar. That will help us achieve short-term benefits as we continue to learn and build better solutions.

Testing 135
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7 types of tech debt that could cripple your business

CIO Business Intelligence

CIOs perennially deal with technical debts risks, costs, and complexities. Using the companys data in LLMs, AI agents, or other generative AI models creates more risk. Build up: Databases that have grown in size, complexity, and usage build up the need to rearchitect the model and architecture to support that growth over time.

Risk 140
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12 AI predictions for 2025

CIO Business Intelligence

Small language models and edge computing Most of the attention this year and last has been on the big language models specifically on ChatGPT in its various permutations, as well as competitors like Anthropics Claude and Metas Llama models.

ROI 141
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Digital transformation 2025: What’s in, what’s out

CIO Business Intelligence

Transformational CIOs continuously invest in their operating model by developing product management, design thinking, agile, DevOps, change management, and data-driven practices. In 2025, CIOs should integrate their data and AI governance efforts, focus on data security to reduce risks, and drive business benefits by improving data quality.

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How to Set AI Goals

O'Reilly on Data

AI Benefits and Stakeholders. AI is a field where value, in the form of outcomes and their resulting benefits, is created by machines exhibiting the ability to learn and “understand,” and to use the knowledge learned to carry out tasks or achieve goals. AI-generated benefits can be realized by defining and achieving appropriate goals.