As we head into 2020 and the third decade of the 21st Century, predictions from technologists abound, and one of the most written about topics is Artificial Intelligence, or AI. We tapped some of the top thought leaders in this space and asked them for their opinions about what’s hype and what’s hopeful at a NetEvents gathering in Silicon Valley this autumn.
You may find their responses enlightening!
Jeremiah Caron, Global Head of Research & Analysis, Technology Group, GlobalData said, “Defining AI is important as the term is broad. There is data science, there is machine learning. Computer vision is a big one. A recent global study of enterprise decision makers showed huge interest in these areas, and an appetite to invest. Huge expectation on spending money in these areas. Over 70 per cent of respondents have data science initiatives underway, with nearly 70 percent focused on machine learning, and over 60 per cent in computer vision applications.”
Ravi Chandrasekaran, SVP, Enterprise Networking Business, responsible for product development across Cisco's switching, routing, wireless, IoT, network automation and analytics portfolios said, “I think it all has to do with what we mean by AI. It's not going to take over everything we're trying to do. At Cisco, we have a very simple view. We view these as tools that assist in certain things which we will not otherwise be able to do. For example, when I talked about the closed loop system, there is a perception or perceived notion that automatically somehow AI's going to make the closed loop happen. We don't believe in that.”
“We need to get our terms straight,” Chandrasekaran continued. “For example, if you are responsible for looking at encrypted traffic, you need automation. AI helps, and while it is not nothing, but it is not yet the glory that people talking about. It's somewhere in between. We are starting to see some good results using AI embedded into the technology and services we provide today.”
Nick McMenemy, Renewtrak (a Renewals-as-a-Service provider that simplifies, automates and improves the support, maintenance & licensing renewal rates for technology organizations) said, “I think we've also come to use the term AI as a catch all for everything which is a machine is going to automate something. There is a place where automation in a smart way may have an impact in freeing up humans to do stuff they really want to do. Ultimately all this automation, all this machine learning stuff they're trying to do is to make what we do every day easier, faster, better, more accurate.”
“To some degree, AI is the flavor of the day,” McMenemy continued. “To a degree I have some skepticism, but I also believe there will be tremendous value created with AI. I don't have a hedge position. I'm not with CISCO, I'm with Arista. I can't go and buy another company just in case AI's the next big thing. To a degree I'm skeptical, but I'm also realistic that there are elements of what people are calling AI which are available in the industry. Certainly, what we do is - people are using it. It works and its machine led.”
Prof. David Cheriton, Stanford Professor, investor and entrepreneur said, “I've been at Stanford for about 38 years and worked with AI people, but I'm more of an AI sceptic. I think one of the advantages of being older is you've been through a bunch of cycles, business cycles and market cycles. Well, I've been through a bunch of AI hype cycles. Back in the '60s, the view was we're just on the edge of producing machine intelligence. That kind of died out, and then didn't go anyplace. In the late '80s, the view was well expert systems were going to take over the universe. There were some very impressive projects done at Stanford there. There was great concern that the Japanese with their fifth-generation computer projects – some of you might be old enough to remember that – were going to just dramatically leapfrog the US in technology.”
“What followed from all of these has been referred to as the AI winter,” Cheriton continued. “When people have asked me over the last 35 years in Stanford what I thought of AI, I say well it's a very promising technology. It's been promising ever since I encountered it and continues to promise. I think it suffers from being over promising. For me, this is, as Yogi Bear would say déjà vu all over again. You look at the excitement over AI, you look at all these articles and say well people are going to be thrown out of jobs and AI machines will take over the universe and so on. I've been there, seen that and then what follows is an AI winter. There's a certain basis for skepticism just on experience.”
Scott Raynovich, Futuriom analyst said, “AI works with very simple applications. Sometimes it doesn't work. Siri to me still doesn't ever work. Shazam is amazing to me because I'm a music fan. It seems to be flawless and recognizes a song within a number of seconds. As we move up in complexity, this is where AI seems to fall apart.”
“Then we get into cloud and the complexity increases by order of magnitudes,” Raynovich added. “You have machines talking to machines on different levels, different domains. Cloud domain, virtualisation domain, hardware domain. When you talk to IT people, their problem is getting things to talk to each other, and having the data sources interoperate so that you can apply the AI. Perhaps this is really about getting systems to interoperate and generate clean data so that we can build AI machines to actually do what we're talking about. That's not happening today.”
We’ll continue to follow and report on these experts’ points-of-view on AI as we evolve through the coming new year.
For more information, education, and networking opportunities around how businesses are leveraging AI and automation to improve existing business models and develop new ones, don’t miss the Future of Work Expo in Fort Lauderdale, Florida February 12-14, 2020. The event, part of the TechSuperShow, will explore how AI, machine learning, and automation are being used throughout a host of vertical markets and are rapidly shaping the future of business.
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