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Take Lessons From 2020 ECC Conference a Step Farther

Joseph Gulla highlights key conference speakers from the 2020 ECC Conference.

Back in July, I posted two articles on the ECC Conference. The first covered Day 1, and the second focused on Day 2 of the virtual conference. At the time I wrote those articles, I wasn’t sure if the videos and presentations from the conference would be published but now that they have been put on the web, I want to focus on the main conference speakers. Now you can watch and listen to them for yourself.

Main Speakers Focused on AI and Quantum Computing

The conference themes this year were AI and machine learning, as well as quantum computing, so this explains the focus of the main speakers. As I mentioned in previous columns, the other sessions throughout the conference were much broader, including topics like security, COBOL®, mainframe skills, middleware and data virtualization.

A New Era in AI

Greg Lotko, general manager and senior vice president, mainframe software division at Broadcom, presented “Opportunity Unfolding: Tracking the Adoption of AI in IT Ops,” which I found it useful to watch a second time. The material is revealed in a straightforward and interesting way in a little more that 20 minutes. The speaker covered implementations of AI with IT operations, not limiting the examples and discussion to just the IT operations domain. For example, the presenter started with AI examples including travel, retail and personal investing. All were useful and compelling.
Relative to IT operations, Lotko indicated that organizations have been aware of the promise of AI and machine learning for advancing operations for years, but we’re now entering a new era where the explosion of data and evolving computing models are poised to take AI from niche use cases to widespread adoption, including on the mainframe. This use of AI in operations is made urgent by the volume of data and system and application complexity. And there is so much activity—so many people doing the same thing at the same time easily overwhelm the finite capacity of human operators.
Human and machine intelligence are coming together to make people, process and platforms more efficient, secure and productive than ever before. This opens opportunities for AI operations (AIOps) to detect infrastructure issues sooner, diagnose them faster and foster self-healing systems through outcome-driven automation. Lotko promotes a pragmatic approach in this presentation. This includes providing easy access to operational data, embedding domain-trained AI to drive outcomes and integrate breadth of visibility with depth of analysis and expertise.

Opportunities for Quantum

Scott Crowder, CTO and vice president, quantum computing, technical strategy and transformation for IBM Systems at IBM presented “Entering the Quantum Decade,” discussing how quantum is different from the computing that’s in wide-scale use today.
In about 25 minutes, Crowder shared that quantum is novel in that the technology can leverage quantum mechanics, scale exponentially and perform operations in parallel. He shared that IBM is making quantum computing resources available over the internet and this will speed adoption. There is also a software stack that’s available to support programming at both low and high levels depending on the problem to be solved.
As a tool, quantum can solve more problems than conventional computing. The problems to be solved by quantum are of significant value to society and business, including quantum material simulations, modeling physical processes of nature and obtaining better optimization solutions.

IBM/MIT/ Watson Lab Research in AI

John Cohn, IBM Fellow at the MIT-IBM Watson® AI Lab at IBM, presented “IBM/MIT/ Watson Lab Research in AI,” a video full of amazing facts and ideas.
Cohn is a most engaging speaker who has been with IBM for 39 years. In the presentation, he shared that this effort between IBM and MIT is the most exciting project he has ever worked on in his long career. Cohn’s main discussion in the 30-minute video included the evolution of AI, involving narrow AI (single task, single domain), broad AI (multitask, multi-domain) and general AI (cross-domain learning and reasoning).
Also discussed was a platform for AI lifecycle including compute, data and models, applications and workflow. The material had an industry and academia context. Cohn included many examples from the MIT-IBM Watson AI Lab such as large-scale video understanding and machine learning. Other examples include neural-symbolic AI and automated moral reasoning.
I invite you to look at other presentations from the conference. This includes 12 presentations from Day 1 and 20 presentations from Day 2. All of them can be found on the conference website.

Next Week

Next week, I will focus on IBM Db2®, starting with product editions and offerings.

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