Remove Experimentation Remove Technology Remove Uncertainty
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Business Strategies for Deploying Disruptive Tech: Generative AI and ChatGPT

Rocket-Powered Data Science

Third, any commitment to a disruptive technology (including data-intensive and AI implementations) must start with a business strategy. Another perspective on technology-induced business disruption (including ChatGPT deployments) is to consider the three F’s that affect (and can potentially derail) such projects.

Strategy 290
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What you need to know about product management for AI

O'Reilly on Data

Machine learning adds uncertainty. Underneath this uncertainty lies further uncertainty in the development process itself. There are strategies for dealing with all of this uncertainty–starting with the proverb from the early days of Agile: “ do the simplest thing that could possibly work.”

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How to Set AI Goals

O'Reilly on Data

Technical competence results in reduced risk and uncertainty. Results are typically achieved through a scientific process of discovery, exploration, and experimentation, and these processes are not always predictable. There’s a lot of overlap between these factors. Conclusion.

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Great Resignation 3.0? Rising workload and skills gap push workers to consider job changes

CIO Business Intelligence

A growing number of workers worldwide are considering changing employers within the next year due to rising workloads and the rapid pace of technological change, surpassing the levels seen during the “Great Resignation” of 2022, a report by PwC said. This sense of uncertainty appears to coincide with rising workloads.

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Why CIOs should invest in digital through economic headwinds

CIO Business Intelligence

But released the next day, the 2023 Gartner CIO and Technology Executive Survey revealed that EMEA-based CIOs expect IT budgets to increase 4.4% Invest in AI augmentation: Employees require tools and technologies that empower them and increase the impact of their work. on average over the next year, somewhat lower than the projected 6.5%

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Generative AI: now is the time to ‘learn by doing’

CIO Business Intelligence

And the technology and tooling will only get better. The pattern for success at learning how to create value safely and responsibly is a mindful culture of experimentation and thoughtful “learning by doing.” He specializes in removing fear, uncertainty, and doubt from strategic decision-making through empirical data and market sensing.

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AI Product Management After Deployment

O'Reilly on Data

Technologies and techniques—such as engineering specifically for GPU/TPU performance and caching—are important tools in the deployment process, but they are also additional components that can fail, and thus be responsible for the failure of an AI product’s core functionality.