30 June 2018
Dr David Hanson, founder of Hanson Robotics and creator of Sophia the Robot, talks James Pearce about automation and the role of networks in robotics
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
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
"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
Human levels of performance and interaction in the real
world will require "considerably more" data, says
"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
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
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