In Part I of our Trailblazers interview, Serhad Doken, innovation and product realization at Verizon, discusses his career background and why fostering innovation, including renewing organization boundaries and groupthink, are vital to sparking new ideas.
In Part II, Doken discusses emerging technologies, including why computer vision algorithms are going to be on steroids, the power of quantum computing, and how eventually AI and machine learning will think like humans.
Dr. Burcin Kaplanoglu, vice president, Oracle Industries Innovation Lab, led the discussion.
There're a lot of horizontal and vertical technologies emerging. Extended reality (XR) is a term we use for the eventual merging of augmented reality and virtual reality. This will be a game changer.
Today, we don't have XR devices at the lowest price points in a pervasive fashion yet, but that's coming in a year or two. The problems to solve there are hard.
But in a nutshell, we should think about XR moving from a 2D world into a 3D world.
When you move into the 3D world, computer vision algorithms are going to be on steroids. We will have new content formats, user experiences, and user interfaces that we will be using with new XR devices and new applications.
Every user interface change reveals a new paradigm. We've seen that during the life cycle of different computing paradigms. XR is one of those. AI is such a core, influential, and horizontal technology that we will see implications in many industries.
Drones are flying robots. Robotics can apply to consumers, to manufacturing, industrial, construction, and engineering in general. Blockchain is a horizontal technology. It’s an enabler and will have a supporting role to change workflows.
You must integrate XR and AI into your existing or technology workflows. That's the best way to embrace them, but that shouldn't be enough.
You must also reimagine how you can redesign the workflows from scratch by removing the assumptions that you had while being aware of these new tools at your disposal. Once someone asked me, “How do you know you have a legacy system?”
Say you're given the budget, resources, and people to design a new or existing system. If you wouldn't design your existing system today exactly as it is deployed right now, then you know you have a legacy system.
If I tell you 5G, XR, AI, and blockchain are coming, and you say, “I can use all of them in this way, change my workflow, and design my system differently to how it is deployed in production today,” then you have a legacy system that must be changed.
We are in the very early days of AI. You’re seeing a lot of remote process automation right now. And so far, everything we've done is reliant on having very powerful computers.
Quantum computing is one of those other paradigms that removes the assumptions. It's not a black and white, one or zero world. It can be both one and zero at the same time.
This includes having a lot of processing power and training a lot of models with a very large data set. We're doing a lot of incredible work there. If you look at GP-3, those are incredible advances.
Once we look back, let's say in year 2030 or 2040, we're going to categorize where we are at today as in the realm of remote process automation.
There’s a lot of research and work going on here, modeling the computing paradigm after how the human brain thinks. Many people are doing significant work in neuromorphic computing.
Just think about the auto industry in the early 1900s. We had a bunch of auto brands and the gas consumption was not that efficient.
Look at the industry now - there are major players. Even compared to 20 years ago, the miles per gallon that your car gets is much better than what it was.
The existing state of the art AI systems are going to get perfected and AI will have real intelligence.
Let’s say I have this wonderful AI system and set of AI algorithms that gives me all the data with computing power before I spit out this answer. At the end, if I cannot explain how I arrived at my answer, business owners or decision-makers are not going to have their trust built into that system.
You must have the trust to give the reins of your business into an AI or machine learning system. The important way to achieve that is to be able to explain, “How did we get to this result?”
That explanation should be understood in 30 or 60 seconds. You come up with 20 different ways of solving a problem, and those all build up into a single final solution like E equals MC squared, and everybody gets it, because you really perfected it at that point.
That reminds me of a quote I heard when I was buying a car a couple of years ago. The salesman told me, “Here's your car, here's the brand, here's the model, and it's got everything you need and nothing you don't.”
When you look at AI and machine learning, we're in the early days. This is very exciting but there's a lot of work we must do.
Longer term, AI and machine learning are going to be thinking just like humans. Neuromorphic computing is very important. Some of those algorithms may run on new types of sensors. Obviously, quantum computing will also be helpful.
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Corie Cheeseman is a senior content marketing manager for Oracle Construction and Engineering.