James Kobielus

James Kobielus is @theCUBE and Wikibon lead analyst for AI, data, data science, deep learning and application development. Previously, Jim was IBM Corp.'s data science evangelist. He managed IBM's thought leadership, social and influencer marketing programs targeted at developers of big data analytics, machine learning and cognitive computing applications. Prior to his five-year stint at IBM, Jim was an analyst at Forrester Research, Current Analysis and the Burton Group. He is also a prolific blogger, a popular speaker and a familiar face from his many appearances as an expert on theCUBE and at industry events.

Latest from James Kobielus

Trip report: At Pentaho World 2017, Hitachi Vantara refocuses data portfolio on edge analytics

Most analytics solution providers now place open source at the heart of their go-to-market approach. But when pioneering open-source analytics vendor Pentaho was formed more than a decade ago, it was still a novel, untested business model. When Hitachi Data Systems acquired Pentaho two years ago, the complementary advantages from combining their respective portfolios were ...

As deep learning frameworks converge, automation possibilities unfold

From a developer’s standpoint, deep learning is usually a hands-on exercise conducted within a particular modeling framework. Typically, a developer has needed to adapt their own manual coding style to interfaces provided by a specific framework, such as TensorFlow, Apache MXNet, Microsoft Cognitive Toolkit (CNTK), Caffe, Caffe2, Torch and Keras. Getting productive on a new DL project ...

Modern infrastructure management: accelerating productivity through machine learning

This is a Wikibon Voice of the Community Report, sponsored by ExtraHop Networks Inc. Voice of the Community posts are identified paid posts that appear on all pages of SiliconANGLE.com, supporting editorial efforts. Premise Information technology infrastructure data can provide valuable intelligence for reducing business overhead, improving back-office and customer-facing processes and ensuring compliance with ...

Analysis: At Spark Summit, Databricks pushes Apache Spark where it needs to go

Invented eight years ago and intensively commercialized over the past several years, Apache Spark has become a core power tool for data scientists and other developers working sophisticated projects in machine learning, continuous stream computing and graph analytics. The open-source codebase’s worldwide customer base now includes more than 225,000 users, and it’s expanding rapidly. However, ...

Keeping cloud-native DevOps from spinning out of control

Cloud-native computing environments tend to become frightfully difficult to build, provision, monitor and control. This is especially true as more containerized apps are pushed into more distributed clusters that are running on more complex multiclouds. These environments are also quite fragile, as new containerized apps carry compliance risks and may, if they run afoul of ...

At Build, Microsoft delivers AI to mainstream software developers

Microsoft Corp. put the convergence of artificial intelligence and cloud at the center of this year’s Build, its annual conference for software developers. As emphasized in keynotes, breakouts, and demonstrations on the expo floor in Seattle, Microsoft’s goal is to “bring artificial intelligence to every developer.” Microsoft’s strategic direction aligns with Wikibon’s recent observation that data ...

Get ready for application modernization, Docker style

Containerization is eating software everywhere. Containers — simple, portable wrappers for applications — today are driving change in all major technology platforms, from the data center to the cloud to the Internet of Things. As both a beneficiary and catalyst of this trend, the Docker ecosystem continues to expand the range of platforms on which ...

Optimizing your application architecture at the ‘federated edge’

Optimizing applications for the sprawl we call the Internet of Things is a daunting challenge. To craft high-performance IoT apps, developers need a federated environment that distributes algorithmic capabilities for execution at IoT network endpoints, also known as “edge devices.” Federation is essential because many IoT edge devices — such as mobile phones — lack ...

Application decay and the burden of data-driven algorithm training

Application developers like to think that they produce gems. Many do, but their handiwork is not immune to the ravages of obsolescence. Application fitness is fragile. Like any eroding asset, applications must often be maintained in order to stay fit for their intended purpose. Application decay is the process under which the fitness of some ...