Digital transformation involves not just organizational change but platforms, ecosystems, and technologies that enable organizations to use data in new ways. This video explains the link between cognitive computing (IBM Watson) and digital transformation.
Shanker Ramamurthy is Global Managing Partner for Business Analytics and Strategy at IBM Global Business Services (GBS).
Anurag Harsh is an entrepreneur, a company executive at Ziff-Davis, a digital and management guru, a blogger, published author of several books.
Michael Krigsman is an industry analyst and host of CXOTALK.
For more information, see: https://www.cxotalk.com/episode/cognitive-computing-digital-transformation
From the transcript:
(03:37) We are at that stage in the evolution of computing capability where machines are able to understand, reason, learn and interact with us. And, the way they’re able to do that is quite different to traditional ways of interaction. So, historically, you had to train a computer using programming. So, you program a computer using a series of […] rules, and those rules would create a small amount of data, and the data would become the system of truth.
(04:13) Now, we live in a world where there’s virtually a finite amount of data, and computers are at that stage in their evolution where they can actually be trained to look at the data and then discern patterns and understand insights. And it’s not just structured data. We’re talking about textual data, video, voice, and other kinds of sound; all sorts of interesting information. And, if you can apply machine learning to that information, then you move to a paradigm where data creates rules as opposed to computer programs creating data. And, when you are on that type of model, fundamentally new applications and fundamentally new ways of doing business emerge from that capability.
(06:59) Also, cognitive computing is here. So, machine learning is not tomorrow’s technology, it’s today’s technology. And, interestingly, with every new type of technology, it takes society a couple of decades to actually figure out how to completely take advantage of that capability. And, we are at that point where cognitive computing is here, it’s being implemented by the early adopters really broadly and very widely. Anurag talked about, for example, the health care industry where cognitive is being applied. For example, IBM has been working with Memorial Sloan-Kettering and it’s got a whole bunch of its own data. And together, IBM, along with some of the smartest brains in the world, are looking at how to solve oncology.
(07:46) And, this is about … Cognitive technology is all about augmenting human intelligence. It’s not … You know, there was a book written by a couple of MIT professors which was titled “Race Against the Machine.” We think of cognitive computing as “race with the machine.” How do you this […] of computing capability and human capability to solve some of the most complex problems that we are dealing with in society and in business?
(08:44) Now think about how profound that statement is. It’s man and machine, which is all … really what it’s about. It’s IBM’s philosophy. It’s not man or machine. And, you know, Shanker was talking about data. I mean, data is at the core of this, right? I mean, we all know about big data, and now Elon Musk is obviously talking about connecting the human brain to a computer. And a lot of people think it’s about … Cognitive computing and machine learning and AI are about trying to figure out how the human brain works and replicating that. It’s not. That’s not what it’s about. You know, we only use a certain percentage of our brain. And so, the idea is to be able to figure out and taxonomize, and make sense of all the data that’s on the internet.
(09:32) Now here’ the thing: the majority of the data. Right now, 80%; in the next three years could be close to 90%; of all data that’s out there is on the dark web. It’s deep web. It’s not accessible. It’s inside firewalls, it’s, you know, everything that people are talking about within your email networks, and it’s where the government operates, where academia operates; it’s inaccessible. And, to be able to get a hold of that data, to be able to, in a manner, to then make sense of it, and understand, and use that data to inform a supercomputer like Watson to then learn from it; and every single iteration it gets better, and better, and better; that’s what this is about, right? It’s a new Moore’s Law that is going to be written in the next several years. And so, I think that it’s about changing outcomes, you know? That’s what this whole thing is about.