Remove Experimentation Remove Modeling Remove Risk Remove Unstructured Data
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3 key digital transformation priorities for 2024

CIO Business Intelligence

Many technology investments are merely transitionary, taking something done today and upgrading it to a better capability without necessarily transforming the business or operating model. Improving search capabilities and addressing unstructured data processing challenges are key gaps for CIOs who want to deliver generative AI capabilities.

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Retailers can tap into generative AI to enhance support for customers and employees

IBM Big Data Hub

With the rise of highly personalized online shopping, direct-to-consumer models, and delivery services, generative AI can help retailers further unlock a host of benefits that can improve customer care, talent transformation and the performance of their applications. The impact of these investments will become evident in the coming years.

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Enterprise IT moves forward — cautiously — with generative AI

CIO Business Intelligence

OpenAI’s text-generating ChatGPT, along with its image generation cousin DALL-E, are the most prominent among a series of large language models, also known as generative language models or generative AI, that have captured the public’s imagination over the last year. And, he says, using generative AI for coding has worked well.

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Why Choose a Hybrid Data Cloud in Financial Services?

Cloudera

As I meet with our customers, there are always a range of discussions regarding the use of the cloud for financial services data and analytics. Customers vary widely on the topic of public cloud – what data sources, what use cases are right for public cloud deployments – beyond sandbox, experimentation efforts.

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Belcorp reimagines R&D with AI

CIO Business Intelligence

Belcorp operates under a direct sales model in 14 countries. As Belcorp considered the difficulties it faced, the R&D division noted it could significantly expedite time-to-market and increase productivity in its product development process if it could shorten the timeframes of the experimental and testing phases in the R&D labs.

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Tech leaders weigh in on the upside and flipside of generative AI

CIO Business Intelligence

But, as with any big new wave, there is a risk of once-promising projects being washed up and there are clear and obvious concerns over governance, quality and security. We ran workshops with every division of our business, educating them on the accelerating innovation in this area, brainstorming opportunities and risks.

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Hey Siri, What’s My Forecasted EBITDA Look Like?

Jedox

There are many reasons why such technology isn’t available yet—insufficient data, unstructured data and some human knowledge that is not yet transferable to machine. Experimental” Technology. Is AI truly experimental technology? How: Start small with a specific data source that can be validated.