Artificial intelligence platforms, applications, programs, tools, functions, systems, whatever one wants to call them, have been the buzzword of technology for some time now. In fact, AI is considered one of the great enablers for the upcoming 5G ecosystem.
However, knowing what I know about this technology, I have taken a rather conservative opinion, in my writings, of just how much faith has been put in AI to solve the world’s problems.
Google, Microsoft, Amazon, and others have put AI into our everyday lives with AI-enabled devices such as Siri and Echo, but peeling back the layers, such implementations are still on the basic scale, even though their creators would have you believe they are the future. Not quite true, but it follows much of the AI hype we have been hearing for the last couple of years.
In that vein, I recently received a report by an organization called Riot Research. They claim the AI bubble is about to burst and bring forth a new era of AI development and implementation. Digging down a bit, I found, not altogether, a shortage of opinions supporting this.
One of their points is that the AI hype has generated unrealistic expectations of what AI is, and will be, capable of – at least for the next five years. Interesting point. Let us look at some of the data that supports the Riot observation.
First of all, it’s true AI cannot happen without deep learning and neural networks. The integration is often referred to as machine intelligence. (See my recent PowerPoint presentation on these technologies.) This, again, plays to the 5G ecosystem where much of the intelligence will be distributed and require a high level of intelligence at places like the edge. To be effective (due to the overwhelming integration of platforms, technologies, applications, and the like), AI will have to be able to become self-aware to some degree. So far, that is not the case, for either 5G or other platforms.
A classic case of that is the reference to AI (deep learning) recognizing an object. An oft-used example is of a cat. A few years ago, AI (in this case a neural network) was able to recognize the face of a cat from video streams. That was heralded as a breakthrough. But, cutting to the chase, AI may be able to identify a cat, as a cat, from its database or learning algorithms. However, it is still quite incapable of knowing whether the cat is real, or just a picture (because it has no awareness of what a cat is), without assistance (human, or other) – back to the real issue, self-awareness. The concepts are solid but the technology lags.
Now, before I get a flood of responses saying we have self-aware systems, I want to clarify something. I am not talking about the kind of self-awareness that one can find in a thermostat that regulates the very temperature that it measures. While that is technically correct, it is not the point of the self-awareness I am discussing. I am talking about real self-awareness – ultimately, the concept that machines realize that the human race is a threat and would not hesitate to eliminate all forms of life on the planet in order to protect its autonomy (as is depicted in so many sci-fi scenarios).
Of course, that scenario is far out (if ever possible) on the radar screen but it defines the ultimate in machine intelligence. However, initial implementations of this path are visible and will be the core of the AI of tomorrow. How the rest turns out is anybody’s guess.
Do not get me wrong. We have a really good start on AI and its capabilities. However, its current capabilities have been oversold and this has led to the current bubble. Yes, there is quite of bit of low-hanging fruit available and is what has VCs and other investors throwing money at the platforms. Nevertheless, eventually, we are going to have to separate the wheat from the chaff and that will be the reality check coming down the line.
Executive Editor/Applied Wireless Technology
His 20-plus years of editorial experience includes being the Editorial Director of Wireless Design and Development and Fiber Optic Technology, the Editor of RF Design, the Technical Editor of Communications Magazine, Cellular Business, Global Communications and a Contributing Technical Editor to Mobile Radio Technology, Satellite Communications, as well as computer-related periodicals such as Windows NT. His technical writing practice client list includes RF Industries, GLOBALFOUNDRIES, Agilent Technologies, Advanced Linear Devices, Ceitec, SA, Lucent Technologies, , Qwest, City and County of Denver, Sandia National Labs, Goldman Sachs, and others. Before becoming exclusive to publishing, he was a computer consultant and regularly taught courses and seminars in applications software, hardware technology, operating systems, and electronics. His credentials include a BS, Electronic Engineering Technology; A.A.S, Electronic Digital Technology. He has held a Colorado Post-Secondary/Adult teaching credential, member of IBM’s Software Developers Assistance Program and Independent Vendor League, a Microsoft Solutions Provider Partner. He is a senior/life member of the IEEE, the Press Liaison for the IEEE Vehicular Technology Society and a member of the IEEE Communications Society, IEEE MTT Society, IEEE Vehicular Technology Society and the IEEE 5G Community. He was also a first-class FCC technician in the early days of radio. Ernest Worthman may be contacted at: [email protected], or [email protected]