Remove Modeling Remove Risk Management Remove Testing Remove Uncertainty
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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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Optimizing Risk and Exposure Management – Roundtable Highlights

Cloudera

For financial institutions and insurers, risk and exposure management has always been a fundamental tenet of the business. Now, risk management has become exponentially complicated in multiple dimensions. . In this session we explored what firms are doing to approach the uncertainty with more predictability.

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How to Build Trust in AI

DataRobot

The first is trust in the performance of your AI/machine learning model. They all serve to answer the question, “How well can my model make predictions based on data?” How can identifying gaps or discrepancies in the training data help you build a more trustworthy model? Dimensions of Trust. How large is the data set?

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20 issues shaping generative AI strategies today

CIO Business Intelligence

As vendors add generative AI to their enterprise software offerings, and as employees test out the tech, CIOs must advise their colleagues on the pros and cons of gen AI’s use as well as the potential consequences of banning or limiting it. How has, say, ChatGPT hit your business model?” How is your business impacted by generative AI?

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Simulation for better decision making

Cloudera

Over the past decade, we have observed open source powered big data and analytics platforms evolve from large data storage containers to massively scalable advanced modeling platforms that seamlessly operate on-premises and in a multi-cloud environment. These examples are well covered by many others (e.g.,

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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). The Cloudera technology has also enabled Bank of the West to experiment and scale faster.

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Predicting Movie Profitability and Risk at the Pre-production Phase

Insight

My goal here is not to improve upon the current prediction algorithms but rather to describe a model I devised, called ReelRisk , that uses random resampling to generate a range of predictions which can then be used as a risk assessment tool to determine early on whether to fund a movie.

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