The product of thinking about computer science problems with every spare moment over a week has left me with a a terrible sense of humor and an undeniable need to make ludicrous analogies, this post is the latter.

The Travelling Salesman Problem or TSP for abbreviation junkies is a well known problem in computer science (or sales). Given a list of cities and locations, one must find the shortest path that visits all cities exactly once. What’s up with that exactly once clause? I don’t know about you, but I find that to be an awkward restriction for a travelling salesman. You’re going to want to loop back and revisit towns you unloaded your wares in earlier unless you’re selling miracle elixirs or IPO shares. Shall we rename the travelling salesman, the travelling charlatan?

The complexity of the problem comes into play because the number of potential paths grows as a factorial of the number of cities and paths. Simple heuristics like locally finding the nearest neighbor are easily proven to fail to find the global minimum and may diverge far from the ideal solution.

A different travelling salesman problem

What if the salesman doesn’t know where each of the cities are? What if some cities have no interest in buying or become ghost towns before the salesman arrives? What if the salesman needs to make enough sales to cover living expenses at each city? Would you agree that the problem has become even more challenging? Now the salesman has limited reach, and may end up at destinations without eager customers. I thought about this type of problem from a more realistic salesman perspective, as I’ve had my fill of theory this week. The final piece of the puzzle madness pie came when I thought to replace the salesman with another species, in particular a shark. My inspiration, life finds solution to intractable problems every day.

Jump the shark

A shark may find its meals far and few between. If the shark fails to find it’s next meal before it’s energy runs out, it faces a grim fate. Now we have dynamic locations with available food (4D x,y,z,T), dynamic reach as the shark can swim only so far, and an ongoing motivation to continue searching out meals in order to survive (hunger). I’m curious what genetically coded strategies in the shark’s mind enable it to efficiently seek out nourishment, and how may we mimic fragments of those algorithms.

Let’s begin the investigation by seeking patterns in how a shark may find its prey. It’s known that sharks have an uncanny sense of smell for blood in the water, and this can guide them to find prey over long distances. But what tactics do sharks take when lacking observations?

The above image and the following excerpt are from a science news article, “Sharks use math to hunt”.

A new study suggests that some sharks and other marine predators can follow strict mathematical strategies when foraging for dinner. The work, reported online June 9 in Nature, is the latest aiming to show whether animals sometimes move in a pattern called a Lévy walk.

Unlike random motion — in which animals take similar-sized steps in any direction, like a drunk stumbling around — Lévy walks are punctuated by rare, long forays in any direction. Draw a Lévy walk on a graph, and its squiggly pattern echoes a fractal, the mathematical phenomenon whose shape remains similar no matter the viewing scale.

“Living organisms, when allowed to make freely willed decisions, seem to end up obeying some kind of mathematical law,” says Gandhimohan Viswanathan, a theoretical physicist at the Federal University of Alagoas in Maceió, Brazil, who was not involved in the study.

Biologists had long thought that animal foraging was dominated by random walks. But in 1996 a team led by Viswanathan reported that wandering albatrosses, fitted with radio-tracking devices, made the occasional long flight that is the hallmark of a Lévy pattern.

Soon, biologists were reporting Lévy behavior in everything from deer to bumblebees and speculating how it might drive human migrations or the spread of genetically engineered crops. But many of those studies were flawed, says David Sims, a researcher at the Marine Biological Association of the United Kingdom in Plymouth. “Patchy data could mean you think you have a Lévy flight when you haven’t,” he says. And in 2007, researchers debunked the original 1996 albatross paper by noting that many of the reported “Lévy walks” — in which the birds’ transmitters remained dry, supposedly during extended flight — actually were birds resting on their nests.

Now, however, Sims and his colleagues say they have firm evidence for Lévy behavior in 14 species of open-ocean marine predators, including tuna, swordfish, marlin and sharks (although not great whites). The key is the sheer amount of data, on depth and location, gathered by electronic tags, says Sims. His group collected more than 12 million data points describing how the animals swam in the ocean over 5,700 days.

I’ve mangled the Travelling Salesman Problem, and gone off on a tangent about how sharks statistically roam for food. But there may be a shred of hope in counting on living organisms to solve computationally intractable problems like the TSP. While doing a little leg work early this morning, I came across an intriguing section of the TSP Wikipedia page. Marco Dorigo, outlined a heuristic method of solving the problem by simulating ant colonies (Ant Colony System or ACS). This field of study is called ant colony optimization and it has produced near-optimal solutions to the TSP.

It models behavior observed in real ants to find short paths between food sources and their nest, an emergent behaviour resulting from each ant’s preference to follow trail pheromones deposited by other ants.

ACS sends out a large number of virtual ant agents to explore many possible routes on the map. Each ant probabilistically chooses the next city to visit based on a heuristic combining the distance to the city and the amount of virtual pheromone deposited on the edge to the city. The ants explore, depositing pheromone on each edge that they cross, until they have all completed a tour. At this point the ant which completed the shortest tour deposits virtual pheromone along its complete tour route (global trail updating). The amount of pheromone deposited is inversely proportional to the tour length: the shorter the tour, the more it deposits.

This is Niles Eldredge. He was the co-developer with Stephen Jay Gould of the theory of punctuated equilibrium. But as a sideline, he happens to collect cornets. He has one of the world’s most largest collections — about 500 of them. And he has decided to treat them as if they were trilobites, or snails, and to do a morphological analysis, and try to derive their genealogical history over time. This is his chart, which is not quite published yet. But the most interesting aspect about this is that if you look at those red lines at the bottom, those indicate basically a parentage of a type of cornet that was no longer made. That does not happen in biology. When something is extinct, you can’t have it as your parent. But that does happen in technology. And it turns out hat that’s so distinctive that you can actually look at this tree, and you can actually use it to determine that this is a technological system versus a biological system. In fact, this idea of resurrecting the whole idea is so that I began to think about what happens with old technology. And it turns out that in fact, technologies don’t die.

Niles monitored the changes in the cornet over a 150 year period. What he discovered is that earlier evolutionary traits returned in later generations, skipping intermediate models. These man made adaptions are contrasted to biology which is bound to step wise evolutionary advantages. He observed that technology appears to have a much longer horizon for genetic memory.

Biological evolution is exhibited by species traits while guided by genetics. In technology the “thing” which evolves to optimize utility is not the object, but the idea or blue prints for the object. The sum of all archived information about a technology is the current state, while instantiations vary according to tastes and teaching. In contrast biological adaptions can be gained or lost over generations.

Internalize Radical Economic and Social Change

The American economy has shifted over time from agricultural, to industrial, to post-industrial. These changes resemble slow drifting tectonic plates (macro trends), but are scarred by periodic spikes that become massive mountains and deep ocean rifts of economic and social upheaval. The labor skills in greatest demand have changed drastically, leaving large segments of society without jobs that draw out their greatest gifts. It’s incredibly hard for folks who’ve spent their lives mastering specific challenges to relearn a new high demand trade, but survival is an unmatched motivator.

I’ve gone through a drastic change in applied skills over the past year. My background in science* has undergone a metamorphosis into new skills in web publishing, marketing, and web application development. I chose to do this because of my enthusiasm for open information exchange, and an unquenchable desire to find untapped value in open data. In contrast, collaboration is a four letter word in many shrinking markets. I haven’t finished crossing the chasm professionally, but at least I can see a ray of hope. I’m now able to rapidly understand and help build interactive web applications with my new skills. Growing an application of significant social value is one of my driving goals. My professional life mirrors some of the macro changes within the US economy, as many larger industrial era businesses are forced to shrink and embrace the network economy.

Pseudo Capitalism

Our nation is founded on economic principles which foster competitive change without heavy intervention from the government. The competition for market domination by businesses, mimics natural competition for limited resources. Like nature, markets evolve over time giving way to disruptive forces.

The most powerful counter force to full commoditization of labor is worker mobility^. Businesses compete for the most capable employees by offering inspiring corporate culture, partial ownership (equity), salaries that remove financial friction, and generous benefits. A direct connection between worker effort and observing the effect of their labor on the bottom line, is key to business success. Top down hierarchies suffer from a lack of push back on assumptions. The more empowered each employee is, the faster the business can adapt to opportunities in a shifting market.

There’s a powerful connection from government capital to social/infrastructure investment. American capitalism drifted over time to mix in strong government influence over finance:

• tariffs
• taxes
• Federal Banks
• heavy financial legislation

Federal, state, and local government spending supports:

• education
• government employees
• infrastructure & social programs
• defense industry

I’ll leave off this riff with a great historic image of the US economy from the 1920s to 2008.

This timeline come’s from GOOD (Oct, 2008)

Notes:
* = My education is in physics (BS) and engineering (MSEE) followed by fourteen years of simulations and algorithm development.

^= “The most powerful counter force to full commoditization of labor is worker mobility”. This mirrors the most potent counter force to full centralized control of the social web, data and service mobility.

Highly profitable attention based business is powered by crack dev teams working at Google and Microsoft (Bing). From the point of view of an outsider looking in, there is a massive shift in resource gravity that has taken only a decade. It is a living example of attention jiu-jitsu, which leverages human interest towards desired outcomes. In this case the result is ever larger revenue growth and accompanying data-centers. The yield of compute center investments are reaped by maintaining information superiority in an emerging network economy. The massive information network density may be the perfect environment for a new pattern to emerge. Upon writing this, I can imagine a room full of artificial intelligence researchers laughing at the possibility of accidental intelligence. My counter is that with enough information (energy) density and connectivity, the highly unlikely becomes inevitable. A plausible method leading to identifiable A.I. is to create a rich environment for intelligence to emerge, as opposed to chasing after intelligence by emulation software. A single spontaneous event is enough to change everything.

Organized structure arising from chaos isn’t a novel concept in nature. Cosmologists have constructed intricate hypotheses based on circumstantial evidence and measurements of ancient energies (I trust their data much more than my arm chair A.I. ideas, which isn’t much). A popular theory tells a tale about the history of the entire universe. The story heralds the unfolding of super galactic structures, all emerging from a single event of supreme energy density.

I look to life for supporting patterns to my “far out” thought riffs. In the search for technological intelligence, what better place to look than the history of the human species, an incredible biological machine. Evolutionary development shows a marked gain in cognitive abilities (brain size) happening over a relatively short timespan.

By reviewing this tree of species is there evidence of a threshold for connectivity that may give rise to sentience? Since we don’t have enough social analysis of our ancestors (read as: I’m too lazy to research it at the moment) it’s tough to judge what was the required neural connectivity to define conscious self awareness. Intelligence is likely a gradual awareness that improves as neural connectivity increases. For example, my dogs are aware, but they’re not self aware (as far as I can guess). In my less lucid moments (strong emotional states), I too become less self aware.

There’s Dollar Signs $$ in Knowledge

Different aspects of decision making are emerging as valued hubs on the web. Hunch and Quora are joining accepted knowledge systems like Wikipedia, Stack Overflow, and many others. Legacy knowledge systems derive value from organized crowd sourced user contributions. As more systems lead to rich connected data frameworks, users benefit from improved information availability. I look forward to progressive models which reward the extracted value with their user communities, something the gentlemen behind Iter8r are working on.

Inspired by knowledge systems, frankensearch.appspot.com was my first effort at a real time search mashup. I’ve been fascinated with various forms of social search since becoming an admitted Net junky over the past 18 months. Since late last year Victus Media has served as an outlet for focusing my efforts on revealing greater user value in social search.

I’ll leave off with a great share I got from my friend David Semeria, the genius behind the LM Framework. Can you see emerging information patterns in collaborative software development?

Twitter Code Swarm from Ben Sandofsky on Vimeo.

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Each of our minds stands alone

The island of self is separated by an ocean of understanding from adjacent minds (more on this later). To connect with others, we must cross the communication chasm that is the product of diverse perceptions. One of the difficulties of deep and meaningful communication is conveying our genuine thoughts and feelings. Another barrier is syncronization, for each message we must be ready and willing to send or recieve it. Beyond willingness, we must also be capable. Skill and effort are required to effectively communicate. Consider the example of web blogs. It takes focused effort to distill abstract thoughts into meaningful written messages, and it takes time to read and interpret those messages.

Enter the Internet

For much of modern history written letters and books were a form of asyncronous communication. Advanced concepts were shared across continents and cultures. Technology has evolved over the centuries and a single massive network has arisen.

With the net, we can send out signals across the globe with the ease of pressing a single button. We have enabled adjacency of minds on a massive scale. Due to the asyncronous nature of many forms of net communication, the requirement for simultaneous openess of minds is relaxed. Individuals are free to tune in, and harmonize when and where they are ready.

What’s in the tubes

The messages consist of text, images, music, video, software, and other data. From single authors and small groups, great collaborative structures have emerged such as wikipedia, and YouTube. Heavy references and linked terminology make plain what otherwise were once obscure topics. Curiousity naturally leads us to less confusion by following linked information. We have more power to find and consume information and media than ever before in history, and this is only the beginning. Arguably more valuable than the rich data itself, are the relationships which emerge between distant minds.

Our Minds are the most valuable web data

I believe the discovery of other minds which resonate with our ideas is the most potent and valued asset of the net. Serendipity in the virtual contiuum of expanding thought and knowledge is a welcome ally. When we harmonize our thought patterns with even a single kindred spirit we find meaning and insight in our own life experiences. Over time this gravity of belonging leads to the emergence of new societies and dynamic global communities in a way that has never before existed in history.

Stretching back through the history of humans, we have had an inseparable relationship with tools. From simple beginnings like the sharpened stone, we have rivaled the complexity of our own biological systems with our technology. Our usage of ultra specialized and general purpose tools is so ingrained in our everyday life, subsisting without them would take great effort. Apparently technology and life have intertwined fates. Without the will to be imagined, created, repaired and utilized technology would cease to function. If one day a form of mechanized life were discovered (or emerged), it would cease to be simply technology. The two, organic and inorganic entities, are coupled in their extropic structuring of the universe. Together, man and technology, go hand in hand inevitably towards the future.

The greatest tools nudge us gently in the right direction. Subtle at times, in harmony wlth our vision, or like massive steel frying pans smashing us in the face, when we step out of line. Both types have their merit. They teach us, they help us explore unknown space. They enable us to do what we could not accomplish without them. Our diverse efforts help to refine and polish the efficacy of tools in areas of perceived need. Our lust for knowledge and freedom from physical pains drives us to discover and explore.

I thank Kevin Kelly for his inspiration of my continued curiosity of the Seventh Kingdom. The concept of extropy and how tools relate to mankind are both derived from his fascinating work. You can find some of it here in various book formats.

Don’t take it too personally the next time a friend, coworker, or customer says your software sucks. You see each time our code is released into the wild, it faces fierce competition in fulfilling the needs of many potential users. Although you (may have) optimized your library for a specific application(s) (homologous to a natural environment), it may not have sufficient fitness to survive in other virtual ecosystems. In addition expectations may be far different than what your software currently provides, either functionally (works like crap) or visually (looks like crap).

Open Source is the Perfect Stage for Competitive Software

We witness open source development communities get ruffled feathers when someone reinvents what their code does, and also releases it under an open license (recent Twisted versus Tornado server discussions). But the truth is, it’s sometimes better to recreate a solution optimized to one’s needs, then try and rework existing open code into what is required. This is certainly true if developers need to understand all the nuances of a complex code base. The flip side is that each open source community is competing for additional skilled developers and resources. If they can provide what is needed, it improves their future chances of code survival.

Much like in nature, when a complex species is unable to adapt fast enough to a radically changing ecosystem, new life forms better suited to the resulting environment may take hold. This law transcends physical boundaries and rules the world of open source. New constructs and languages are ever evolving to meet the challenging demands of a dynamic digital landscape. We see this in operating systems, programming languages, and layered web services.

I, for one, embrace the remorseless competition of source code’s challenged survival. Its implications on continually improving software shows great promise for the future.

Neural Interfaces May Teach Us More About Consciousness

The key to our consciousness may not be the brain itself, but the waves that continually travel throughout the structure.  Much like highways, our complex neural networks are simply infrastructure for our electromagnetic (and chemical) thought waves to traverse and interact.  By focusing our learning about brain waves, neural interface devices will help us understand what gives us a sense of consciousness.  In addition the potential for replicating artificial infrastructure exterior to our bodies, but accessible to our conscious minds could be possible.  Yeah I know, it’s a far out idea but consider our brain’s division.  It is composed of two main hemispheres and multiple clusters, and there is somewhat redundant data storage in various portions of our mind.  Yet with all these interacting clusters, we have one consciousness.

Mind Outside of Body

As our body functions via gene regulatory networks, our consciousness emerges from an incredible complex network of signals. If network signals are the source of our sense of consciousness, what does this imply about the restriction on where our minds can dwell?  While imagining this thought experiment, I considered potential requirements for a functioning external environment that the mind could spread to. Any extension to our mind would require similar brain-like infrastructure to our own physical brain:

• organic cloned nerve cells and clusters
  • radically different species, plants?
• technological replications
  • specially designed computer systems and interfaces
  • artificial brain-like matter
  • uploaded to a cloud-like system
• near instant information flow between various sections of the mind
• a method of formatting new infrastructure to be compatible with our memories
• novel brain structures for handling additional sensory information, from remote locations

The complexity of our brains is staggering.  We are just beginning to understand some of the building blocks, small clusters of neurons, and the enormous network of connections that host our conscious thought. In order to even consider extensions to our minds, we will first need to become experts on the states of mind, the intricacies of  information flow and storage within our brains, and how the sum total of all brain structures and mind signals results in a single consciousness, a single voice.  Both technology and neuroscience (amongst other scientific disciplines) will be tasked with tremendous technological obstacles if expanding our minds is to become reality.

Even if a mind can be extended beyond the physical bounds it was created with, huge new avenues of research would be opened.  Artificial Intelligences could be given the spark of life using the same techniques that would allow for mind extension.  If full knowledge of mind is achieved, near identical duplicates could be replicated (or stored as backups in case of loss).  What difference would there be from artificial minds to naturally initiated minds?  We could design new aspects to our consciousness through specialized constructions (stronger curiosity).

How may expanded minds communicate and share?  Could they copy information directly and what interfaces may allow for huge amounts of information transmission. Can minds share the same infrastructure and coexist?  Imagine the concept of crowd sourcing or social design with many minds co-located and analyzing incredibly challenging problems from thousands of views simultaneously.   What would identify and associate each thought on a single infrastructure back to a single consciousness?

• orthogonal waves
• a universal ID, embedded in each thought
• identity marker signals/features

Imagine in the far future, extended perception throughout massive distances, minds may duplicated over light years by transmission of state.  Our minds could potentially exist throughout the cosmos, ubiquitous in many places at once yet all acting with a single will.  Our perspective would be forever altered, no longer small and selfish but collective and considerate of broader and deeper issues.  Limited resources will always force us to make decisions to allow for innovation.  New minds will need to be allotted enough structure to grow and flourish.  Older minds will need to expand outward or follow the natural life cycle of death and rebirth.

Thanks to Kevin Kelly for Infinite in Some Directions and Evidence of a Global SuperOrganism for opening my mind to new potential paths that technology may develop in.

Follow Mother Nature and Build Complex Systems Fractally
Start with just one or two other people that you can relate to, who’re as determined as you (or more so) to build the organization and get them on board.  Empower leaders to replicate what you have done with your first small group iteratively.  As the community grows and others are responsible for managing new and existing members, your group will need to spend some time refreshing their alignment to the collective’s current goals at all levels.  Do your best to remain open and available to anyone in your organization, and insure that they feel empowered to make decisions on the group’s behalf.  For any job or task, the person doing the task is responsible for representing the organization as a whole.

Or If You Have Unlimited Resources: Entice Your Dream Team to Organize
If I could harness the will, focus, and influence of my favorite bloggers/thought leaders into one organization/corporation, I imagine it would be a creative financial force to be reckoned with.

• At the marketing helm steering through any branding barriers would be dynamo Seth Godin.  He’d be my first pick to help entice the rest to consider the possibilities of a “Legion of Super Web Heroes”.  Plus Seth could relay the marvels of having his own action figure.
• Dreaming up visionary technology would be “fringe of now sci-fi” author Kevin Kelly.
• Knowing the companies that have the greatest Kung-Fu when it comes to tech and coming up with a plethora of far out and brilliant ideas himself, Robert Scoble.
• But wait, how do we profit best from combining this team and tech? With none other than venture capitalist, and way beyond web 2.0 personified, Fred Wilson.  He could wring out the potential as well as having incredible connections with startup geniuses.
• I almost forgot Paul Graham, the programming sensei.  His essays got me started down this road.  I came across one of his posts about YCombinator and that got me thinking, and thinking, and thinking…
• Where do I fit in with this Legion of Super Change Makers?  Every super group needs an eccentric data miner concerned primarily with the quality of life of those who inherit our imagination.  Curiosity fueled and blessed with the worlds greatest companion (Michelle), fantastic friends and loving family.  It’d be one helluva job just keeping up with the developments of the market disruptors above.

Idea Blazer Kevin Kelly Challenges Us To Imagine The Direction of Evolution
After having spent some time enjoying the blog of author Kevin Kelly, I couldn’t resist posting about his recent tour de force, Ordained-Becoming.  I shamelessly admit to not reading everything Kevin has written (I failed to find the time to even complete the first of two parts of Ordained-Becoming!).  When I
do find a moment to read his work, I find it’s best to take a single post of his and carefully dig in.  Although I have chosen to touch on only a few of the concepts from that work, should you have any interest in the subject of evolution at all, I highly recommend the read.  You can find it in my current favorite of his blogs, The Technium (although I’m still fascinated with his series on The Swarm). The story told discusses a potential direction for evolution.  Is life on earth is changing diversity, and species complexity.   We are introduced to some of the findings of Simon Conway Morris (specialist) who began a study of obscure fossils:

Paleobiology Graduate Student Simon Conway Morris’ Determines Diversity May Be Decreasing?
One of his Simon’s earlier conclusions suggests there was greater amount of diversity hundreds
of millions of years ago, compared to today.  This suggests that diversity has declined over time and taking this hypothesis further he posed that evolutionary forces would continue in that direction. This would foretell a future less
diverse in species. Optimal species would take hold in certain areas
but there would be a decline is the number of unique species in a specific environment.

Reviewing the Fossils, Morris Finds that Species Were Less Diverse 500 Million Years Ago
Later on Morris reconsidered his theories prompted by the work of Steven J. Gould, specifically Wonderful Life. In it Gould discusses “a fundamental contingency of evolution”, an introduced random element that suggests there is no inherent direction for evolution.  Morris reviewed his earlier work and found that he had confused a few of samples that appeared wildy different in structure but were actually quite similar to their modern counterparts.

My preferred model for growth, survival, and extinction concentrates on local regions of stability with competiting populations for limited resources in a fixed environment (chaos theory).  As to the natural mechanisms for evolution and beneficial mutations, one can think of life as a long time scale search for optimal species survival traits (hardiness).

Some theorize
that evolution is increasing in complexity.  For instance look at humans compared to single cell organisms.  We are fairly complicated with estimates of between 10-100 trillion cells working in unison. In the Technium, Kelly sees Technology as the latest form of
evolution and predicts that it will become a species in of itself.  Whether or not we identify and
recognize it as “life” now is up to debate (self-replicating machines, nanorobotics, Ralph C. Merkle’s work ). Today we manufacture technology.  There aren’t a
lot of computers building computers, but we use a series of complicated machines
when constructing modern technology.  There’s already a level of separation (or more) between us and our tools, and in the near future technology may not need it’s inventor to evolve.

Take for example my portable computer/phone.  I use my iPhone all the time for a great many applications, but I don’t know how the chips and
software are manufactured.  Even though I have a background in developing algorithms/software
for many years I am largely ignorant of the specific programs that make up the iPhone’s core systems.  Although familiar with many of the methodologies, I realize that I can only hold a large program or two fresh in my mind before becoming overwhelmed.  Apple has created an incredible software framework/publishing system for developers to write and sell their own iPhone applications.  This framework leads back to social design and the search power of collaborative views as dominant trends for future technology design. The most successful companies will build a backbone (or the operating system) and let everyone else add to it with an easy to use set of tools.

Back in Ordained-Becoming, Kevin goes on to talk
about how there may yet be an evolutionary direction and that nature prefers certain powerful features (local attractors) like discovering the optimal proteins for light collection in eyes (it has evolved in quite a few unrelated species).  He discusses the two opposing forces on evolution,

• physical limitations (gravity, food, space) and
• novel creations of “the complexity of interlinked genes”.

There might be one species that dominates in a given environmental role.  But you can
see now that even as many species become extinct or are shrinking in populations, many new species sprout up.  Consider an isolated evolutionary area, for instance Australia.  They are a number of different species that developed in Australia, yet they share similarities to mammals elsewhere. Beyond the fact that they’re warm blooded, young are
born living (classification traits of mammals), consider the flying squirrel and the sugar glider.  Both have developed thin membranes for coasting in the air a short periods between trees.  Also in respect to diversity consider special advantages to some of Australia’s native creatures.  The Marsupials have little pouches that they carry their
young in, so they don’t need a baby carriage (I couldn’t resist). Because they don’t require holding onto
their young all of the time, the pouch has been a survival
advantage for them.

Implications for Technology?

So what does that mean for tech? What’s going to happen as technology
evolves? Is it going to be more complicated? More diverse? Is it just
going to be one big interconnected type of system (living internet)? These are the type
of ideas or thought experiments inspired by Kevin’s
work. And I’m only about 2/3 of the way through his first of two
posts on the subject. Hopefully I will
have more to share on this topic soon.

The Raw Audio: