This overview of artificial intelligence (AI) by disruptive technology expert Andrew Burgess demystifies AI and explains a lot of its specialized vocabulary. Aptly named an “executive guide,” it is exceptionally clear and will be useful to anyone who wants a handle on AI. The introduction addresses business issues and the book’s framework offers a useful […]
Read on this article to learn comprehensive introduction to AI technologies and how to implement them. Semantic technologies are a core component of intelligent machines. Learn how to align the work of data scientists and subject matter experts to increase the business value of your data lake.
Data is the lifeblood of artificial intelligence and deep learning (AI and DL). Vast quantities of training data enhance accuracy in the search for potentially predictive relationships. Here are eight specific storage requirements of AI and DL applications and why they demand the data management capabilities supplied by enterprise object storage solutions.
Why buy fancy AI processors if you already have decent CPUs? Sebastian Moss talks to Intel about its plan to stop you turning to a competitor.
Machine learning will increase the demands on data center performance, leading to new ways to cool and power the systems there, reports Peter Judge.
But with AI’s rapid growth, it is easy to have missed some of the terminology behind the field of study, with its many subsets and different approaches. To help out, here’s a quick intro by DCD.
There are many use cases for AI in the data center, including improved safety and reliability, greater efficiency, and reduced energy consumption. By collecting information from infrastructure, AI can predict faults and respond in milliseconds.
We have an almost mystical faith in the ability of artificial intelligence (AI) to understand and solve problems. It’s being applied across many areas of our daily lives and, as a result, the hardware to enable this is starting to populate our data centers. Data centers in themselves present an array of complex problems, including […]
Inside this article, you will find among others, information about: When Machine Learning meets Marketing Automation Ways to use Machine Learning in Marketing Automation The channels of recommendation delivery The new face of Marketing Automation
Artificial intelligence for IT Operations (AIOps) is widely defined as the result of big data and artificial intelligence (AI) / machine learning (ML). It’s a framework designed to help CIOs master today’s dynamic IT landscape and answer questions such as: Where to place workloads for optimal performance and cost? How to connect apps to infrastructure […]