IBM combines Power AI and Data Science Experience

The AI bandwagon is getting big fast. Gartner reports Global IT spending in 2018 will increase 4.3% over last year topping $3.7 trillion, driven by business strategies tied to varying degrees of digital transformation and more uses around artificial intelligence. AI actually comes out as Gartner’s #1 tech trend for 2018, with the company saying: The ability to use AI to enhance decision making, reinvent business models and ecosystems, and remake the customer experience will drive the payoff for digital initiatives through 2025.

IBM already has made cognitive computing, one of its myriad terms for AI, a strategic imperative. To underscore the point, on Oct. 10 the company announced integrating two key software tools for AI, PowerAI deep learning with the IBM Data Science Experience.  If you were dithering about how to get involved in AI or cognitive computing, here’s a way to start. The Data Science Experience is available through a per-user licensing model while Power AI is available for free, at least for now.

Rethinking the way work works

With this integration, data scientists will be able to develop AI models with the leading open source deep learning frameworks like TensorFlow or Caffe to unlock analytical insights. The Data Science Experience (DSX) is a collaborative workspace that enables users to develop machine learning models and manage their data and trained models. PowerAI adds topnotch deep learning libraries, algorithms, and capabilities from popular open-source frameworks. The deep-learning frameworks will be able to sort through all types of data – sound, text or visuals – to enhance learning models on DSX.

For example, banks today can leverage deep learning to make more informed predictions about clients who might default on credit or to better detect credit card fraud, or sense clients who are ready to switch bank, which would give the bank a chance to make an offer that might save the account and reduce churn.

In manufacturing, deep learning models can be trained to identify potential failures before they happen by analyzing historical data derived from the functioning of equipment. Through such AI-driven predictive analysis, the manufacturer can reduce downtime and boost productivity. As these learning models continuously evolve and get smarter over time, they become more sophisticated, or smarter, at identifying anomalies and can alert the team on site to take remedial action before a production line unexpectedly stops. It also can advise of specific actions to take.

The Distributed Deep Learning library included with PowerAI from IBM Research reduces deep learning training times from weeks to hours. By integrating such capabilities with DSX brings accelerated deep learning to DSX’s collaborative workspace environment, which further speeds the results.

The growth of deep learning and machine learning is fueled, at least in part, by a rapid rise in computing capability via accelerators like NVIDIA Tesla GPUs. IBM optimized the deep learning frameworks like TensorFlow in PowerAI for IBM Power Systems. For example, the company takes advantage of the industry’s only CPU to GPU implementation of the NVIDIA NVLink high-speed interconnect, which acts as a communications superhighway of sorts, to speed the results.

Frameworks like TensorFlow and Caffe democratize insights through AI. This is expected to result in better client experiences sooner and new business models. And now the PowerAI deep learning enterprise software distribution is integrated into the DSX, a collaborative workspace that helps data scientists to build, manage and deploy AI models from which everyone benefits, both the company and its customers, who enjoy a better customer experience.

The PowerAI libraries and algorithms are optimized for the IBM Power Systems S822LC for High Performance Computing, enabling users ranging from data scientists to business analysts to engage in machine and deep learning through the Data Science Experience collaborative environment. Data scientists are particularly well-positioned to look at deep learning to leverage data as a competitive differentiator and asset.

DSX and PowerAI are packaged as two separate software offerings but integrated and designed to work together.  PowerAI is available only on Power systems while DSX is available on IBM Cloud and on-premises through Power or x86.

As IBM puts it: When it comes to deep learning, faster is better, enabling enterprises of all types to tap into the unlimited potential of AI. If you are a Power shop, grab the free PowerAI deal while its available and then sign up at least a few of your users for DSX and see what you can do.

DancingDinosaur is Alan Radding, a veteran information technology analyst, writer, and ghost-writer. Please follow DancingDinosaur on Twitter, @mainframeblog. See more of his IT writing at and here.


One Response to “IBM combines Power AI and Data Science Experience”

  1. digital transformations Says:

    Wow! Finally I got a blog from where I know how to truly obtain useful information concerning my study
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