IBM Research’s Chief Scientist Talks AI for Cloud Migration

Part of the future is already here as AI increases its influence on hybrid cloud and the digital transformation equation, according to Ruchir Puri.

As enterprises consider how they might take advantage of adopting a hybrid cloud approach, AI may be poised to accelerate and shake up the possibilities, says Ruchir Puri, chief scientist with IBM Research. Known for his work with IBM Watson, Puri discussed with InformationWeek how IBM is approaching the digital era, hybrid cloud, and AI. This includes evolving AI technology born out of Watson and teaching AI to essentially speak code.

Puri’s team works on AI

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Data in Motion Drives Enterprise Change

Data in motion involves several different situations that might require different architectures, applications and management techniques. Here’s what you need to know.

Image: TAW4 –

Previously, collected data remained in one place. It arose from a transaction system, went to a warehouse or mart, and remained there for users to access and analyze. Today, however, data is often in motion. It may originate in a sensor on a moving vehicle, then is aggregated, sent to the cloud, into a data lake, then out into the world to guide actions and decisions. Sometimes action is taken on this data at

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Scale Your Machine Learning with MLOps

When it is time for your machine learning pilot programs to graduate and take on the real world, you need to start looking at MLOps.

A few years ago, everyone was trying to figure out how to get started with artificial intelligence and one of its components, machine learning. But today many organizations have put together pilot programs, identified promising use cases, and even turned around some value for their organizations.

After you’ve won those initial successes, it’s time to expand that value to other use cases and other parts of the organization. But with each of your initial use

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Data Analytics Without a Plan is Like Panning for Gold

Without a strategy in place to analyze and act upon your data, you’ll get bogged down, sifting for worthy nuggets.

Data is being generated and collected at an astonishing rate. Companies hoping to duplicate the success of data-first organizations like Amazon are jumping on the bandwagon, collecting every scrap of information they can. But without a plan to analyze and act upon this data, it is easy to get bogged down by minutiae with no real impact.

The first (and often skipped) step in creating an analytics strategy is mapping it to business goals. Dazzled by the wealth of available

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How to Create a Successful AI Program

Artificial intelligence can be promising and valuable, but you need to focus on a few best practices to get your program moving in the right direction.

Lots of people are interested in artificial intelligence, and there are plenty of stories about the amazing strides that are being enabled by AI, in business, in medicine, and in any number of other areas. But the stories of wild successes hide a very different part of the AI process — all the hard work that comes before that success.

Justin Nguyen, director of data science and AI and Sense Corp., likens those

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