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AI

AI/ML - Are We Using It in the Right Context?

There used to be a distinct, technical separation between terms such as AI and machine learning (ML) – but only while these technologies remained largely theoretical. As soon as they became practical in the real world, and then commodifiable into products, the marketers stepped in. Widespread overuse of the terms AI/ML in marketing have managed to thoroughly confuse the meanings of these words.

Machine Data is Business Intelligence for Digital Companies

Software has eaten the world and every company today is a software company. This is because every company today is more and more serving its customers digitally. That service can be a spectrum, such as offering traditional physical products and services through digital channels on one end to offering entirely new digital products on the other end. Regardless of where on the spectrum a company is, it does not change the fact that its primary interface with its customers has become its software.

Monitoring Machine Learning Models Built in Amazon SageMaker

Many data science discussions focus on model development. But as any data scientist will tell you, this is only a small—and often relatively quick—part of the data science pipeline. An important, but often overlooked, component of model stewardship is monitoring models once they’ve been released to the wild. Here we’ll aim to convince any unbelievers that monitoring deployed models is as important as any other task in the data science workflow.

AppDynamics: Empowering the Enterprise With Real-Time Visibility Into the Application Environment

The world is changing. Today, people and devices are more connected than ever before, raising the bar for performance and the customer experience alike. At AppDynamics, we’re unified in our mission to empower the enterprise with an AI-powered application performance monitoring solution that provides visibility and insight into the IT environment, as well as unified monitoring down to the network, so you can make mission critical and strategic decisions that drive business forward in real-time.

5G is Rolling Out: Here's How Cognitive Analytics Will Take Part in the Revolution

5G is here and is widely expected to be a transformative communications technology for the next decade. This new data network will enable never-before-seen data transfer speeds and high-performance remote computing capabilities. Such vast, fast networks will need dedicated tools and practices to be managed, including AI and machine learning processes that will ensure efficient management of network resources and flexibility to meet user demands.

Deep Learning for Time Series Data (O'Reilly Artificial Intelligence Conference)

Arun Kejariwal and Ira Cohen, both thought leaders in the deep learning space, share a novel two-step approach for building more reliable prediction models by integrating anomalies in them. They then walk you through marrying correlation analysis with anomaly detection, discuss how the topics are intertwined, and detail the challenges you may encounter based on production data. Present at the 2019 O'Reilly Artificial Intelligence Conference.

GTC 2019 Accelerating AI Performance, Ease of Use with Ubuntu and NVIDIA DGX

Carmine Rimi of Canonical and Tony Paikeday, NVIDIA, discuss the need for flexibility, performance, and ease of use in AI development solutions. They continue to address how NVIDIA's DGX platforms and Ubuntu emphasize accessibility for these data scientists and engineers, allowing them to get up and running quickly with familiar technology.

An Introduction to Artificial Intelligence and Machine Learning - Everything You Need to Know

AI and ML adoption in the enterprise is exploding from Silicon Valley to Wall Street. Ubuntu is becoming the premier platform for these ambitions — from developer workstations, to racks, to clouds and to the edge with smart connected IoT. But with new developer trends comes a plethora of new technologies and terminologies to understand.