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Marsh McLennan IT reorg lays foundation for gen AI

CIO Business Intelligence

It’s a full-fledged platform … pre-engineered with the governance we needed, and cost-optimized. The team opted to build out its platform on Databricks for analytics, machine learning (ML), and AI, running it on both AWS and Azure. This costs me about 1% of what it would cost” to license the technology through Microsoft.

IT 122
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Banks bet on AI to deliver digital efficiencies

CIO Business Intelligence

The Global Banking Benchmark Study 2024 , which surveyed more than 1,000 executives from the banking sector worldwide, found that almost a third (32%) of banks’ budgets for customer experience transformation is now spent on AI, machine learning, and generative AI.

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Security In Automated Document Processing: Ensuring Data Integrity And Confidentiality

Smart Data Collective

Among these innovations is the world of document processing where automation has revolutionized traditional methods. The Rise Of Automated Document Processing You’ve likely come across automated document processing in your industry endeavors. Not everyone in your organization needs to access every document.

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An AI Data Platform for All Seasons

Rocket-Powered Data Science

In deep learning applications (including GenAI, LLMs, and computer vision), a data object (e.g., document, image, video, audio clip) is reduced (transformed) to a condensed vector representation using deep neural networks. Second question: What about technical debt and the cost of “lift and shift” to these new AI-ready architectures?

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Marsh McLellan IT reorg lays foundation for gen AI

CIO Business Intelligence

It’s a full-fledged platform … pre-engineered with the governance we needed, and cost-optimized. The team opted to build out its platform on Databricks for analytics, machine learning (ML), and AI, running it on both AWS and Azure. This costs me about 1% of what it would cost” to license the technology through Microsoft.

IT 105
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Have we reached the end of ‘too expensive’ for enterprise software?

CIO Business Intelligence

Before LLMs and diffusion models, organizations had to invest a significant amount of time, effort, and resources into developing custom machine-learning models to solve difficult problems. In many cases, this eliminates the need for specialized teams, extensive data labeling, and complex machine-learning pipelines.

Software 128
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Introducing Cloudera Fine Tuning Studio for Training, Evaluating, and Deploying LLMs with Cloudera AI

Cloudera

Here are just a few examples of the benefits of using LLMs in the enterprise for both internal and external use cases: Optimize Costs. These enable customer service representatives to focus their time and attention on more high-value interactions, leading to a more cost-efficient service model. Increase Productivity.