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Large Language Models and Data Management

Ontotext

I did some research because I wanted to create a basic framework on the intersection between large language models (LLM) and data management. But there are also a host of other issues (and cautions) to take into consideration. LLM is by its very design a language model. The technology is very new and not well understood.

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Your New Cloud for AI May Be Inside a Colo

CIO Business Intelligence

Many companies whose AI model training infrastructure is not proximal to their data lake incur steeper costs as the data sets grow larger and AI models become more complex. The cloud is great for experimentation when data sets are smaller and model complexity is light. Potential headaches of DIY on-prem infrastructure.

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DS Smith sets a single-cloud agenda for sustainability

CIO Business Intelligence

Its digital transformation began with an application modernization phase, in which Dickson and her IT teams determined which applications should be hosted in the public cloud and which should remain on a private cloud. Energy optimization is another key aspect of DS Smith’s data and sustainability pipeline, the CIO says.

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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. trillion on retail businesses through 2029.

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CIOs sharpen cloud cost strategies — just as gen AI spikes loom

CIO Business Intelligence

“Awareness of FinOps practices and the maturity of software that can automate cloud optimization activities have helped enterprises get a better understanding of key cost drivers,” McCarthy says, referring to the practice of blending finance and cloud operations to optimize cloud spend. It depends on what business model you’re in.

Strategy 140
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Getting ready for artificial general intelligence with examples

IBM Big Data Hub

While these large language model (LLM) technologies might seem like it sometimes, it’s important to understand that they are not the thinking machines promised by science fiction. Most experts categorize it as a powerful, but narrow AI model. A key trend is the adoption of multiple models in production.

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What you need to know about product management for AI

O'Reilly on Data

But there’s a host of new challenges when it comes to managing AI projects: more unknowns, non-deterministic outcomes, new infrastructures, new processes and new tools. For machine learning systems used in consumer internet companies, models are often continuously retrained many times a day using billions of entirely new input-output pairs.