If you ask the man or woman on the street what they think is meant when we discuss automation, most will probably point to self-driving cars, heavy machinery or the old favourite – robots.
There is something iconic about robots that has made them become recognised as the cutting edge of technology. But, as is often the case, this cutting edge technology needs to be backed by a cutting edge network.
That is the view of one of the leading experts in robotics, Dr David Hanson, when I meet ahead of his keynote presentation at May’s International Telecoms Week. Hanson is known as the founder of Hanson Robotics and the creator of several robots, most famously Sophia – the first robot to ever be granted citizenship.
Sophia doesn’t need to be connected to the internet at all times, but the computational power she uses greatly increases when she is part of a network, Hanson says. When not connected, she uses just 1MB of processing power.
“When Sophia is not connected to the internet she can answer questions and interact just fine, but when she does have a connection, she can provide much deeper set of answers, running with our MindCloud AI service,” he says.
The data she is managing now includes camera data, 3D sensor data and microphone data, plus a lot controlling her motor functions “but it is something less than a megabyte right now”.
Human levels of performance and interaction in the real world will require “considerably more” data, says Hanson.
“You’d have a vast amount of surface sensor data and the tactile data becomes very important. Right now, her tactile data is very limited but we will be adding a lot more of those kinds of sensors in the future. Some of that can be processed locally. We’re seeing much better vision processing and deep learning that you can do on graphics cards in real time and dedicated machine vision and learning modules and processors,” he says.
“However, I can imagine for human-level intelligent performance, for the kind of learning you need, you’d be looking at a minimum of 20MB. We expect that if we have more powerful local processing, such as mobile computing, you might only need to send a few megabits a second to the cloud network.”
This is where he gets excited. It seems to be discussing newer, more cutting-edge technologies that thrills Hanson, who moves onto mesh computing.
“You can also load-balance some of that processing against mobile devices and other small connected IoT devices. If we consider that we may be able to utilise a mesh network of phones and other mobile computing devices and, through machine learning, be able to pick up data, you would decrease the loads on the cell towers and other networks,” he says.
“You could also take the resulting machine-to-machine models and share those with the cloud, so you don’t have to share the raw data but the resulting, interpreted models.”
That is going to reduce the load on the networks enormously – meaning networks could be directed to supporting other functions. Once machines get smart, he adds, they can do more with less data.
The impact of artificial intelligence on future communications networks will be huge, Hanson expects. AI will help telcos to create more robust networks through adaptive problem solving and this kind of product is already being tested on some networks. Data analytics mixed with AI can also help networks become more agile and more reliable.
So how does this impact telecoms and wholesale? “Scale becomes really important. Tools available in telecoms are essential to the future of these things because they are already scaled,” he says.
“Designing these tools so that they can scale through telecommunications becomes instrumental. The telecoms industry provides an optimised balance between power and price and that is where the real-world implications spring forth. The ideas are great but they are only relevant when they hit the real world.”
For Hanson, telecoms will play a key role in supporting an AI-powered future. But it will also benefit from this kind of next-gen technology. I ask him if telecoms is one of the quicker industries at adopting this.
He pauses before answering. “My impression is that telecommunications will adopt a technology once it is proven and scaled. Then the industry will adopt it like wildfire. Passing through that gate can be somewhat complicated. The computing you have in a mobile device has been in a very competitive space.”
