The Technology of Nature: Swarms, Simple Rules, Repetition, and Variance
Biological systems mesmerize us. They feature incredible complexity, but somehow simplicity and beauty at the same time. When we look more closely we discover layers of mathematical symmetry embedded within the natural world. We see breathtaking patterns, and delicate balance everywhere we turn. By the relentless grindstone of time and chance, biological systems are worked by the laws of the universe. When we look at how these systems have come to be, we find that simple, well crafted rules help nature to produce the awe-inspiring world we are surrounded by. We might just learn how to best organize ourselves, our data, and even our payment networks, in time, by studying the technology of biology.
Although this topic is somewhat intangible, I intend to illustrate how a few commonly observed characteristics of nature help to shape reality as we know it.
Highly connected individual bodies behave as one organism quite often in nature. From swarms of birds, to the bizarre collaboration of organisms that make up a Portuguese Man O' War, nature is filled with examples of this strategy. Swarms can react as one, providing protection to the individual participant. Information spreads across the group in an instant, allowing the swarm to avoid danger and fend off predators.
Efficiently Evolves: Organisms are seeded with some starting data (DNA). Through their lifecycle they are trained by outside stimulus. Eventually the organism reproduces, passing down their experience to their offspring encoded in new strands of DNA. This process repeats to create unimaginable specificity to their environment, allowing them to excel at whatever helps their likelihood of survival.
Simple, Perfected Rules: The process of endless evolution creates highly efficient, but often simple patterns. The culmination of life experience works to slowly discover these perfect methods over time.
Safety in Diversity: Nature Spawns Mutants. Tiny variance in the individual organisms yield unexpected solutions to most any problem the natural world can produce. A newly formed hydrothermal vent on an ocean floor might be devastating to the local ecosystem, but eventually, these other forces combine with subtle mutation to adapt, creating entire new species in the process.
Better Than Human Design?
Take for example the traveling salesman problem. Over the years we have come up with some great algorithms for solving it, but it's far from trivial.
As it turns out, after many years of evolution, nature does this really well. When rudimentary rules are carefully crafted, followed over many iterations, and slightly varied over time, novel solutions can magically emerge. It might take hundreds of years to get there, but the results are undeniable.
Efficiency Evolves: Slime Mold
What you're watching is a single celled organism, a slime mould, finding the most efficient route between pieces of food scattered across a surface by researchers. Pretty cool, but that's not the best part. The food was positioned and proportioned to mimic Japanese cities. The results were incredible, as the slime mould had successfully created paths that were just as, if not more efficient than the actual Tokyo rail system:
The slime mold characteristically pulses as it spreads out in search of food. It seems to follows this (over-simplified) pattern again and again to achieve what engineers consider a complex problem.
- Expand and find food
- Contract, leaving only the best paths behind
While the specifics of what decision making process is being used here is unknown, through this repeating pattern of behavior, it achieves what we have struggled to do well with modern algorithms.
It is also interesting that this organism is technically a single cell. It cheats by having many nuclei floating around in its handsome exterior. Without the boundaries between cells, you could imagine a low latency communications network going on in there, informing the rest of the body where exactly to expand, and where to contract. Also interesting it seems to cycle in a rhythmic pattern, over and over again. The kind of pulse we so commonly associate with life.
Honey bees are another example of nature solving this problem. Bees are tasked with collecting enough pollen to make honey for the colony to thrive. The traveling salesmen problem is kind of what they do. This time, instead of cities, the bees need to find the best path between all of the flowers in their area. Ages of repeating this basic process has led to measurably impressive efficiency.
Until recently, we could only dream of building these kinds of systems. Sure the wright brothers drew inspiration from birds, but the first airplane hardly had the intricacy we find in the wings of a Golden Eagle.
The discovery of fractal geometry may have given us a frosted window into the intricate natural world.
Simple, Prefect Rules: Fractals
Fractals are just plain cool. An over-simplified explanation of how they are generated goes something like this:
- Pick a starting (complex number) value
- Run it through a special, but simple, equation
- Plot the output's real and imaginary components, and use that value as the starting value for the next iteration
The Mandelbrot Set is perhaps the most well known of these equations. A basic representation of this is:
Z = Z² + C
Iterate and plot the output from this simple function over and over and you've got a fractal. Amazingly, this carefully chosen equation combined with well selected colors can generate some visually impressive results. If you continuously increment your starting value and calculate the colors over and over you get a fractal "zoom".
Now instead of incrementing the start value, we keep it the same but rotate the color thresholds. Even in greyscale changing the color mapping brings out life-like "movement".
Possibly the most fascinating thing about fractals are, they seem to be the basis for many of the patterns we find in nature. A striking resemblance to our slime mold in this case. When exploring the set, familiar forms leap from the "random" images. An intricate seahorse, a lightening bolt, or the beautiful fibonacci-spiraled shell of a Nautilus, can be generated using a simple mathematical formula.
Since the equations used to produce these fractals are relatively simple, they can be much less expensive to calculate than other popular imaging techniques. This is why the visualizer built into WinAmp back in the day really whipped the llama's ass, even on that Pentium III. Fractals pack such an efficiency punch that they helped revolutionize the way 3D graphics were generated for computer games, CG movies, and other digital arts. An entire field was launched forward on the back of Mandelbrot's discovery.
I went the whole fractals section without mentioning how they relate to price action, but thats an entire post for some other day.
Resiliency of Diversity: Fungi
Many species of mushroom have been found to adapt to the sources of food they can readily consume over many iterations of their, generally short, lifecycle. This eagerness to adapt is one reason for the incredible diversity in the Fungi kingdom. In fact, it is estimated that we've only discovered less than 3% of all fungi species that exist!
Due to their typically short lifecycle, some mushrooms update their programming quickly, producing new enzymes and other compounds that are hardly found in nature. This is why some of the most rare and important compounds available to man, like Penicillin, come from fungi. This property can be used for our benefit, especially for bioremediation. This dude hacked Oyster mushrooms by training them to eat cigarette butts.
What does Bitcoin have to do with all of this? Well, Bitcoin, of course, is not a biological system, but it does share some of the fundamental principles that make them so successful. The network of computers that communicate using the Bitcoin protocol have some similar an interesting properties to the miraculous examples we find in nature.
Reactive Swarm: High Connectivity
Nodes are like individual organisms in nature, while the network as a whole is like a tight-knit swarm, voluntarily acting in unison.
The adjustable block size of Bitcoin Cash encourages powerful, highly connected nodes to process transactions moving through the network. At the same time, it discourages home brew raspberry pi nodes that might slow down the broadcast or transfer of large, newly mined blocks, hindering propagation. A node without good connectivity risks mining orphaned blocks. A node with insufficient storage capacity or memory risks failing to process the block data. With high connectivity the swarm can react to a double spend attack instantly, unlocking untapped efficiency in the form of 0-confirmation transactions.
Efficiency: Bitcoin Remembers and Efficiency Evolves
Bitcoin nodes remember. With every reboot, they start with a list of nodes to connect to. Like the DNA passed down from one generation's life experience to the next, these simple instructions are used to bootstrap a nodes connectivity, allowing it to quickly communicate with its strongest peers.
Bitcoin has only existed a short time, and has not had much opportunity to build up intrinsic "intelligence" like nature does over time. Bitcoin does allow for rapid adaptation, and given enough time the efficiency required to achieve society's goals for it will only improve. We've seen what adjustable blocks can do, and we're already looking forward to huge efficiency improvements like Graphene, increased miner adoption, and Subchains (weak blocks) to name a couple well known proposals.
Simplicity: A Chain of Digital Signatures
The most essential definition of Bitcoin is simply "a chain of digital signatures". The whitepaper is only 9 pages long, including references and cover page. It uses a purposely simplified scripting language to perform all of it's duties. For all of its scantness, it is often described as "beautiful". An elegant and carefully crafted protocol that unleashes breathtaking results once evoked.
This is one reason many are critical of technologies like Segregated witness, and the Lightening Network which complicate the essential structure of the protocol. Those who believe in the value of a tried and true original recipe take issue with anything that might change their simple formula, creating completely different outcomes. In nature, these different paths emerge all the time in search of a new route to efficiency. One will likely emerge as the best solution in the end, continuing its legacy one block at a time.
Resiliency: Bitcoin Mutants
Bitcoin's system of governance is open ended and encourages iteration to solve difficult problems. When a significant challenge arrives, like the cigarette butt in a jar of mycelium, the network can mutate, creating a new variant better equipped to deal with the pitfalls of its ancestor. The lessons learned from that mutation are carried on through the next block, and the next, until a new mutation is necessary. Bitcoins First mutations might be considered Bitcoin Cash & Bitcoin Segwit. The were spawned from a common ancestor, but have unique characteristics all their own.
As biology reminds us, one path will be the most efficient given it's environment in the end, and as many iterations of governance are applied to the protocol, Bitcoin will be what emerges as the best of breed among its mutant siblings.
Thanks For Reading!
In the paid section I've assembled several hours of videos, short documentaries, and other related material that reinforce the ideas slapped into this post. None of the videos are directly Bitcoin related, but they help to illustrate how nature uses simple iterative processes to yield incredibly efficient and impressive results, and how we might use them as a model to solve some of our most difficult problems.
Cover art by Sharon Cummings
3 of 3 reviewers say it's worth paying for
0 of 3 reviewers say it's not worth paying for