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CIO insights: What’s next for AI in the enterprise?

CIO Business Intelligence

CIOs are under increasing pressure to deliver AI across their enterprises – a new reality that, despite the hype, requires pragmatic approaches to testing, deploying, and managing the technologies responsibly to help their organizations work faster and smarter. The top brass is paying close attention.

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20 issues shaping generative AI strategies today

CIO Business Intelligence

Just look at the stats:Some 45% of 2,500 executives polled for a May 2023 report from research firm Gartner said the publicity around ChatGPT prompted them to increase their AI investments, 70% said their organization is already exploring gen AI, and 19% are in actual pilot or production mode.

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Banking on mainframe-led digital transformation for financial services

IBM Big Data Hub

Why mainframe application modernization stalls We’ve experienced global economic uncertainties in recent memory, from the 2008 “too big to fail” crisis to our current post-pandemic high interest rates causing overexposure and insolvency of certain large depositor banks.

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Celebrating Data Superheroes: The 2021 Data Impact Awards Winners

Cloudera

This allows for an omni-channel view of the customer and enables real-time data streaming and a safe zone to test machine learning models using Cloudera Data Science Workbench (CDSW). This, in turn, has had a positive impact on innovation and decision-making aimed at improving customer services and reporting. . Industry Transformation.

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Predicting Movie Profitability and Risk at the Pre-production Phase

Insight

I held out 20% of this as a test set and used the remainder for training and validation. Below is the result of a single XGBoost model trained on 80% of the data and tested on the unseen held-out 20%. Scatterplot of the predicted ROI vs. the true ROI for the hold-out test set. and even set their risk tolerance.

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