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Interview with: Sankar Narayanan, Chief Practice Officer at Fractal Analytics

Corinium

Fractal’s recommendation is to take an incremental, test and learn approach to analytics to fully demonstrate the program value before making larger capital investments. There is usually a steep learning curve in terms of “doing AI right”, which is invaluable. What is the most common mistake people make around data?

Insurance 250
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NLP Isn’t Enough. Leading Financial Services Companies Are Now Moving to Conversational AI.

CIO Business Intelligence

The very best conversational AI systems come close to passing the Turing test , that is, they are very difficult to distinguish from a human being. . NLP technologies need to be thoughtfully trained and tested thoroughly to ensure they don’t have any biases. The answer depends on the scope of the application and throughput needs.

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Choosing the right Machine Learning Framework

Domino Data Lab

Here are several key considerations you should take into account when selecting a machine learning framework for your project. When you start your search for a machine learning framework, ask these three questions: Will you use the framework for deep learning or classic machine learning algorithms? Tensorflow 2.0,

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AI in marketing: How to leverage this powerful new technology for your next campaign

IBM Big Data Hub

Audience segmentation: AI helps businesses intelligently and efficiently divide up their customers by various traits, interests and behaviors, leading to enhanced targeting and more effective marketing campaigns that result in stronger customer engagement and improved ROI.

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Getting ready for artificial general intelligence with examples

IBM Big Data Hub

Beyond cost savings, organizations seek tangible ways to measure gen AI’s return on investment (ROI), focusing on factors like revenue generation, cost savings, efficiency gains and accuracy improvements, depending on the use case. A key trend is the adoption of multiple models in production. What are the types of AGI?

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What you need to know about product management for AI

O'Reilly on Data

This has serious implications for software testing, versioning, deployment, and other core development processes. Product recommendations are easy; nobody is injured if you recommend products that your customers don’t want, though you won’t see much ROI. What delivers the greatest ROI? Managing Machine Learning Projects” (AWS).

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The most valuable AI use cases for business

IBM Big Data Hub

AIOps is one of the fastest ways to boost ROI from digital transformation investments. AI platforms can use machine learning and deep learning to spot suspicious or anomalous transactions. A manual approach to development and testing could lead to calculation errors and require a huge volume of resources.