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Conversational AI use cases for enterprises

IBM Big Data Hub

The emergence of NLG has dramatically improved the quality of automated customer service tools, making interactions more pleasant for users, and reducing reliance on human agents for routine inquiries. Machine learning (ML) and deep learning (DL) form the foundation of conversational AI development.

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12 most popular AI use cases in the enterprise today

CIO Business Intelligence

Airbnb is one company using AI to optimize pricing on AWS, utilizing AI to manage capacity, to build custom cost and usage data tools, and to optimize storage and computing capacity. For other companies, AI use in customer service has also been driven by consumer’s increased expectations.

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Bringing an AI Product to Market

O'Reilly on Data

It’s often difficult for businesses without a mature data or machine learning practice to define and agree on metrics. Fair warning: if the business lacks metrics, it probably also lacks discipline about data infrastructure, collection, governance, and much more.) Agreeing on metrics.

Marketing 362
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The InnoGraph Artificial Intelligence Taxonomy

Ontotext

This post describes our approach to developing such a taxonomy by integrating and coreferencing data from numerous sources. The official (first) repo is tensorflow/tensor2tensor that has topics: machine-learning reinforcement-learning deep-learning machine-translation tpu. has 260,491 topics and is 15 levels deep.

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Responsible AI Relies on Data Literacy

DataRobot

Data literacy is a key component for any organization to be able to scale responsible and trusted artificial intelligence technology. Achieving that level of governance at scale requires a common understanding of AI and data concepts. What Is Data Literacy? How Can Organizations Cultivate Data Literacy?

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

IBM Big Data Hub

From customized content creation to task automation and data analysis, AI has seemingly endless applications when it comes to marketing, but also some potential risks. More accurate measurement of KPIs: Digital campaigns generate more data than humans can keep up with, which can make measuring the success of marketing initiatives difficult.

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Artificial Intelligence: Implications On Marketing, Analytics, And You

Occam's Razor

Perhaps you now see why I’ve pivoted my career to Storytelling with data over the last couple of years. :). Invest in continuous learning. The most conservative estimate is that AI driven changes are expected to replace 25% of jobs across the world, by 2026. Deep Learning is a specific ML technique.