All technology seems to be modelled off of aspects of nature. We see it over and over again. Through evolution by natural selection, Nature has been able to work out creative solutions to support all forms of life on earth. By observing and studying these life forms – their behavior, movement, form, adaptability, and so on, humans have developed new technologies or optimized existing ones. Popularly known as biomimicry, this approach to innovation where materials, structures, and systems are designed, based on nature’s time-tested sustenance strategies, is quickly gaining ground with scientists all over the world.
The robotic arm was one of the biggest breakthroughs in the 21st century. It truly kicked in the era of automation by revolutionizing the way factories work. However, being modelled after the human arm, it does pose a few challenges. It is made of rigid parts which restrict movement. The bulky arm is also a threat to people, which is why it has to be carefully protected to prevent collisions. So, the Bionic Handling Assistant has been modelled after an elephant’s trunk, which not only solves a myriad of human arm problems, but opens up a wide range of grander possibilities.
Perhaps one of the most famous examples of biomimicry is evident in the history of human flight. Leonardo da Vinci is largely recognized as a key instigator in its development, as he made the first real studies on birds and human flight in the 1480s. His original design, called the Ornithopter, was never created, but was a principal in showing how man could potentially fly.
Several designers and engineers worked on this bird-inspired concept in the following years, for instance Otto Lilienthal completed more than 2,500 flights in a glider, but it was not until 1903 that the Wright Brothers flew the first powered, heavier-than-air machine in a controlled and sustainable flight. This technology went on to define the aerial developments of 20th century and the technology seen in the air today.
Bees in a hive behave as a single unit. Each bee can sense what job needs to be done and gets on it, without being instructed to do so. They instinctively know what is expected of them based on where they live in the hive and what the adjacent bees are doing.
The hive mind inspired swarm technology. A group of tiny robots, controlled by a central computer, can act as a single unit to take on complex tasks by communicating with one another and dividing the tasks among themselves. Each robot can think for itself to the best extent possible and acts primarily on the local information it gathers, i.e., by observing adjacent robots. Since no robot is in charge, a robot can easily replace another, should a unit malfunction. This technology is set to change the face of search and rescue missions. They are also currently used to improve the efficiency of power grids.
So, both Elephants and Bees have inspired man’s continuous innovation in technological advancements. This leads me to ponder what models of Mother Nature is Starlink chasing? I see one clearly already, a Neural Network.
A Neural Network
As the new Starlink internet from space solution evolves and we mere mortals gain insights into the genius of the mind of Elon Musk, I must wonder what will it all mean? What will it all become? How will it all be used?
So, respecting my natural curious tendency, I started to observe Starlink to see if it reveals any clues to its future. To discover exactly what patterns I see forming as Starlink matures? Is it trending towards some identifiable outcomes?
It is commonly called a Constellation. Okay, that makes sense. In Nature, we have a constellation of stars and by its biomimicry, the Starlink constellation is looking very much like a constellation of stars, albeit far more spatially organized when compared to Mother Nature’s handiwork.
This constellation is being formed on multiple plains with chains of these small LEO satellites arranged in what we call shells. So, Starlink is constructed on three dimensions with height, width, and depth. A neural network has multiple dimensions too. In fact, we call Deep Learning ‘deep’ because of the number of layers that it has within these dimensions. There are just a few layers to Starlink, so it is not really that deep on its own in space. But, what if we combined the space-based layers with arrays on earth, the terrestrial-layers would augment and aggregate the depth of the Starlink neural network. That might enhance it more, right?
Now that Starlink has tested its laser linking technology with two satellites talking to each other without much meaningful latency due to the free-space propagation properties of space and at astonishing gigabit speeds, the constellation is forming and organizing into a swarm of satellite nodes. With each satellite acting as an equal node within the swarm.
Now, if Starlink spacecraft possessed local compute, storage, analytics, and artificial intelligence edge computing capabilities built into these satellite nodes, an intriguing shape is starting to be revealed.
Traditional satellites like the Geostationary birds (spacecraft) found in the Clark Belt are just big relaying amplifiers. They are pretty dumb actually. They simply turn around data and blast it back to earth like a fire hose spraying all within their footprints.
As I ponder this thinking, I must question, why? Why build an array of satellites in outer space? Surely you could do it all much similar and at a fraction of the cost in a huge hangar-like building here on earth. What makes space the perfect place to build a neural network like this one?
The answer is space itself.
To create a proper neural network we need at least three elements – Interconnections, Intelligence, and Instrumentation (I3). Of course, neural networks are modelled after the human brain and its neural network.
An artificial neural network learning algorithm, or neural network, or just neural net, is a computational learning system that uses a network of functions to understand and translate a data input of one form into a desired output, usually in another form. The concept of the artificial neural network was inspired by human biology and the way neurons of the human brain function together to understand inputs from human senses.
Neural networks are just one of many tools and approaches used in machine learning algorithms. The neural network itself may be used as a piece in many different machine learning algorithms to process complex data inputs into a space that computers can understand.
Neural networks are being applied to many real-life problems today, including speech and image recognition, spam email filtering, finance, and medical diagnosis, to name a few.
So, if Musk is constructing the world’s largest global neural network, and he has the interconnection capability coupled with the onboard intelligence capability, then he is just missing the instrumentation capability. But, maybe we, the Starlink users, will give him a vast assortment of technologies to ‘instrument’. We could feed our data freely into his array and then Musk could derive new data outputs from our inputs.
So, is Elon Musk about to build the world’s largest scale Internet of Things (IoT) network? A smaller scale compute power onboard the spacecraft could easily accommodate the traffic flows of IoT. The laser links would make it a mesh network too. So, maybe the neural network could be a ‘mini me’ variant compared to a true AI neural network design? The Baby Yoda version like in the Mandalorian. lol
But, the ground terminals are far too big for most IoT applications, unless we use them as gateways and extend the reach with a terrestrial mesh network to compliment the space-based mesh network? IoT in Space – that sounds like a very cool idea.
The applications for this model are endless. For example, could Starlink improve weather forecasting with a global granular grid of weather reporting stations? Would that lead to forecasting of agricultural crop yields? Does that allow Musk to predict the stock market? Okay, okay, maybe my imagination is starting to run wild here? But, the opportunity to do good with this neural network is inspirational. However, yes, I agree that it is truly a lot of informational power in the hands of a few, or the one.
Now, let me throw a proverbial bucket of ice water on all those extremest conspiracy theorist who will inevitably and immediately start screaming. “Skynet Lives”. First of all, Elon Musk is no Terminator. Second of all, it is conjecture on my part that Starlink has the edge networking compute power onboard their spacecraft. Yes, it is a safe prediction, but not a certainty by any means. Third, there is nothing to indicate in the SpaceX story any parallels to Skynet. And fourth, if SpaceX is to be believed, they are just building a global internet connection from satellites. No big deal, that is enough for them. But, is it ever enough for Elon Musk?
So how else can these Starlink spacecraft be utilized once fully operational? Can we stitch together a fabric in space that weaves in many new and creatively innovative applications? More time and daydreaming is necessary to understand how these tens of thousands of satellites can coalesce to form something far grander in scope and scale than just fat internet pipes from space.
But, one point is true, we can bolt-on a great many technological components to Starlink to transform it from a basic internet transportation network into something far more powerful and life changing (and ‘NO’, to those wannabe supervillains who are about to ask yet again – it is not Skynet, not yet anyways).
Goddard, G. (2020). Biomimetic design: 10 examples of nature inspiring technology. Science Focus. Retrieved on September 16, 2020 from, https://www.sciencefocus.com/future-technology/biomimetic-design-10-examples-of-nature-inspiring-technology/
Unknown. (2017). Technologies inspired by nature. Aranca. Retrieved on September 16, 2020 from, https://www.aranca.com/knowledge-library/articles/ip-research/technologies-inspired-by-nature
Unknown. (2020), Neural Network. DeepAI. Retrieved on September 16, 2020 from, https://deepai.org/machine-learning-glossary-and-terms/neural-network
About the Author:
Michael Martin has more than 35 years of experience in systems design for applications that use broadband networks, optical fibre, wireless, and digital communications technologies. He is a business and technology consultant. He offers his services on a contracting basis. Over the past 15 years with IBM, he has worked in the GBS Global Center of Competency for Energy and Utilities and the GTS Global Center of Excellence for Energy and Utilities. He is a founding partner and President of MICAN Communications and before that was President of Comlink Systems Limited and Ensat Broadcast Services, Inc., both divisions of Cygnal Technologies Corporation (CYN: TSX). Martin currently serves on the Board of Directors for TeraGo Inc (TGO: TSX) and previously served on the Board of Directors for Avante Logixx Inc. (XX: TSX.V). He has served as a Member, SCC ISO-IEC JTC 1/SC-41 – Internet of Things and related technologies, ISO – International Organization for Standardization, and as a member of the NIST SP 500-325 Fog Computing Conceptual Model, National Institute of Standards and Technology. He served on the Board of Governors of the University of Ontario Institute of Technology (UOIT) [now OntarioTech University] and on the Board of Advisers of five different Colleges in Ontario. For 16 years he served on the Board of the Society of Motion Picture and Television Engineers (SMPTE), Toronto Section. He holds three master’s degrees, in business (MBA), communication (MA), and education (MEd). As well, he has three undergraduate diplomas and five certifications in business, computer programming, internetworking, project management, media, photography, and communication technology. He has earned 20 badges in next generation MOOC continuous education in IoT, Cloud, AI and Cognitive systems, Blockchain, Agile, Big Data, Design Thinking, Security, and more.