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

ANALYSIS

Chef extends DevOps deeper into Kubernetes multiclouds

DevOps is a pipeline for rapidly deploying changes to infrastructure and application components. It also involves continuous verification of application compliance with relevant policies and mandates. Speed is the essence of DevOps success, as long as application quality and compliance are not compromised. Unfortunately, most DevOps professionals spend far too long getting their apps released into production. ...
ANALYSIS

Informatica keeps the momentum rolling in hybrid cloud management

Informatica LLC has become synonymous with enterprise data management. Now in its 25th year, it has become one the premier providers of enterprise-grade data solutions in on-premises and cloud environments. Informatica’s Intelligent Data Platform solution portfolio supports sophisticated requirements of data managers, data engineers, data scientists, data curators and other professionals working in private, public and ...
DEEP DIVE

Pushing AI performance benchmarks to the edge

You can’t optimize your artificial intelligence applications unless you’ve benchmarked their performance on a range of target hardware and software infrastructures. As I discussed recently, the AI industry is developing benchmarking suites that will help practitioners determine the target environment in which their machine learning, deep learning or other statistical models might perform best. Increasingly, these ...
DEEP DIVE

Hybrid clouds: building out orchestration, middleware, DevOps and management tooling

Hybrid clouds are a necessary step, but often a transitional one, for enterprises that are evolving toward more complete reliance on public clouds. If you sifted through vendor announcements from the recent Red Hat Summit, you’ll find ample corroboration of this trend. In their efforts to help customers converge their investments in hybrid-cloud platforms, tooling and ...
ANALYSIS

Blockchain startups are trying to grab a piece of the video streaming market

Nothing attracts startups like a market with big, healthy cash cows. That describes the video streaming market, in which a few high-profile brands have risen to the top of the media and entertainment industry. Even the back-end video distribution services are highly consolidated among the largest public cloud services providers. Startups are now flooding into the ...
ANALYSIS

How client-side training is moving from the fringes to the center of AI development

Model training is where artificial intelligence models are readied for production deployment. Traditionally, machine learning, deep learning and other AI models are trained in clouds, server clusters and other high-performance computing environments. However, Wikibon has recently noticed a surge in AI training environments that operate at the network’s edge. In other words, these environments evaluate ...
ANALYSIS

Crossing the uncanny valley without losing our grip on AI’s value

Science fiction has been announcing the coming of artificial intelligence and robotics for longer than most people have been alive. Our 21st century culture has been immersed in these visions for so long that we take them as manifest destiny. Over the past week, however, several AI industry announcements sent shivers down our collective backbones, ...
DEEP DIVE

Blockchain isn’t ready for enterprise primetime. Here’s what will get it there

Blockchain is rapidly rising up the enterprise priority stack, though as we noted recently, it’s still got a way to go before it’s widely deployed in business. Some longtime information technology industry observers predict that blockchain digital ledger will totally disrupt business as we know it within a few years. More blockchain pilots are making the transition to ...
ANALYSIS

Anything but artificial, AI is evolving into anticipatory intelligence

Prediction is becoming cheaper, faster, more automated and more ubiquitous in our lives, and we have artificial intelligence to thank for that. AI is essentially a predictive technology. No matter what its algorithmic underpinnings, its core function is to make sophisticated inferences about what’s likely to happen based on myriad variables that have been distilled ...
ANALYSIS

The big takeaway at I/O: Google updates its mobile AI roadmap

Artificial intelligence was the dominant theme of Google’s latest developer conference in Mountain View, just as it was at Microsoft Corp.’s equivalent shindig happening this same week in Seattle. In late March, Google LLC held a very technical AI developer summit where it made many important announcements in the evolution of its TensorFlow framework for ...