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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

The challenge of finding reliable AI performance benchmarks

Artificial intelligence can be extremely resource-intensive. Generally, AI practitioners seek out the fastest, most scalable, most power-efficient and lowest-cost hardware, software and cloud platforms to run their workloads. As the AI arena shifts toward workload-optimized architectures, there’s a growing need for standard …

How now, smart browser? AI takes up residence on the web client

Artificial intelligence is starting to live everywhere, especially in your browser. Browser-based AI has several advantages. Running AI in the browser can speed up some AI operations — such as sentiment analysis, hand gesture detection and style transfer — by executing them directly on the client. …

Serverless computing takes a big step into the multicloud world

Serverless computing has already invaded public cloud services in a big way. Now, it’s coming to private clouds as well. As discussed in this Wikibon report from last October, more open-source serverless frameworks are entering the market, providing options for enterprises that wish to deploy them …

AI is driving the evolution of hyperconverged cloud infrastructure

Artificial intelligence workloads are becoming central to cloud computing. AI is assuming a larger role in optimizing the hyperconverged infrastructures that underpin today’s multiclouds, as well as premises-based “true private clouds” that approximate the public cloud experience. AI-ready storage and compute integration …

AI’s automation flywheel spins greater human productivity

Artificial intelligence-driven automation is taking hold everywhere, though many people fear that this trend will put people out of jobs en masse. How realistic is this worry? Bear in mind that many automation-related vendor announcements highlight a “human-in-the-loop” capability that bodes well …

Bringing probabilistic programming into AI development

When you’re programming an artificial intelligence application, you’re usually building statistical models that output discrete values. Is that image a human face? Whose face is it? Is that face expressing a positive or negative emotion? Does that emotion fall outside the range …

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