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To understand the risks posed by AI, follow the money

O'Reilly on Data

Others retort that large language models (LLMs) have already reached the peak of their powers. It’s difficult to argue with David Collingridge’s influential thesis that attempting to predict the risks posed by new technologies is a fool’s errand. We ought to heed Collingridge’s warning that technology evolves in uncertain ways.

Risk 221
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Gen AI without the risks

CIO Business Intelligence

Developing and deploying successful AI can be an expensive process with a high risk of failure. How can CIOs deliver accurate, trustworthy AI without the energy costs and carbon footprint of a small city? Retraining creates expert models that are more accurate, smaller, and more efficient to run. Not at all. But do be careful.

Risk 132
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CIOs weigh where to place AI bets — and how to de-risk them

CIO Business Intelligence

Amid the turbulence of AI, technologies are emerging rapidly, startups are clamoring for attention, and hyperscalers are scrambling to corral market share. Brian Hopkins, vice president for emerging technology at Forrester Research, agrees. There are a lot of risks and a lot of land mines to navigate,” says the analyst.

Risk 133
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How to get your CFO to buy into a better model for IT funding

CIO Business Intelligence

And they want to know exactly how much return on investment (ROI) can be expected when IT leaders make technology-related changes. Continuous and dependable funding facilitates IT leaders’ ability to deliver leading-edge technology solutions while not increasing technical debt. Meanwhile, CIOs want certainty when it comes to funding.

Modeling 124
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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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4 hidden risks of your enterprise cloud strategy

CIO Business Intelligence

While cloud risk analysis should be no different than any other third-party risk analysis, many enterprises treat the cloud more gently, taking a less thorough approach. Interrelations between these various partners further complicate the risk equation. That’s where the contract comes into play.

Risk 131
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How to use foundation models and trusted governance to manage AI workflow risk

IBM Big Data Hub

As more businesses use AI systems and the technology continues to mature and change, improper use could expose a company to significant financial, operational, regulatory and reputational risks. It includes processes that trace and document the origin of data, models and associated metadata and pipelines for audits.

Risk 79