One goal of this web site is to create the foundation for, “a million mini-Musks” – people who may not be billionaires, but who shake up the world to the degree that they are enabled in constructive and innovative ways. We’ll look at other examples besides Elon Musk, but we’ll start here because it’s an excellent contemporary example of Lesson One.
A Google search on “Elon Musk, First Principles” comes up with 135,000 hits, including this nice summary from LifeHacker – Elon Musk Brainstorming.
“Reasoning from first principles” basically means to break down a problem to it’s most basic components, typically math and matter in the case of an engineering problem. In math, it’s reasoning from axioms and postulates. In logic, it’s reason from a priori assumptions (items that are considered true without further proof) and logical postulates. Both were pioneered in ancient Greece, but the rules have been expanded and brought into other fields. An accident investigation goes through root cause analysis. In physics, reasoning from first principles is a common term, and is also called “reasoning ab initio” or “from the beginning”. It starts with various accepted formulas and builds up to models and experimentation.
An alternative is “reason by analogy”. That states that if X shares attributes with Y, we can interpolate other attributes of Y based on our understanding of X. This is useful if done correctly, and can lead to failure if overextended. It may lead to some innovations, but it will rarely lead to revolutionary inventions unless it jumps from one field to another.
When Elon Musk refers to reasoning from first principles, he breaks down the components of something to the chemical level. A rocket may be X tonnes of aluminum and other materials, and those cost Y amount on the open commodity market. A lithium battery may contain X kilograms of lithium which costs Y amount from a supplier. He then looks at the cost of the finished product – the rocket or the battery, and looks at the value added costs for those two items. If the cost difference is extreme, there is a market opportunity.
In Reasoning by Analogy, we start with the cost of other products on the market in that field, and if they all tend to be the same price, we assume that is the proper price because there are no examples of it not costing that amount. Reason by analogy does not allow for innovation in cost savings unless there is already a product that costs less than the others. Reason by analogy starts with end products already on the market and works backwards to try to find more efficiency in existing methods of production.
Musk argues, and proves with his successes at Tesla and Space-X, that reason from first principles can completely revolutionize a field by re-thinking the most affordable way we can do something at our current level of technology. If your entrenched competitors are simply refining last year’s model, they will never start over and create something revolutionary.
If you want to create an invention that is also an economic opportunity, you must understand both reason from first principles and reason from analogy. You want to be the one doing the reason from first principles when everyone else in the market is doing reason by analogy. Here are two examples to show you what to look for in a market opportunity.
Example of when not to build: The retail material cost of a new workbench is $100 using wood purchased at a hardware store. The store also sells workbenches for $90. Because the manufacturer is buying direct from lumber mills, buying in bulk, and purchasing finished goods from manufacturers using economies of scale and automation. If you are limited in your sources to the hardware store for wood and materials, you cannot profitably go into this business unless you are doing custom work. Alternatively, if you own a lumber mill, you can compare the price you get for lumber versus finished goods and decide if expansion to finished goods is a logical move. While this is rarely the case, we do see lumber distributors investing in precision tools that can cut very thin layers of very expensive wood for use in veneers.
Example of when to build: If your competitors make rockets that cost $300 million to launch 20 tonnes, and you are able to make a rocket that costs $100 million to launch the same payload, you have $200 million in competitive advantage for the existing market. You also have the ability to expand the market to those who cannot afford a $300 million launch vehicle, such as poorer nations or smaller corporations. In hearings before a senate panel, United Launch Alliance (ULA) was questioned as to why their services are so much more expensive for Defense Department satellites than those of Space-X. ULA pointed out that they have special facilities for handling delicate satellites that add to the cost, such as systems that flood the payload fairing with nitrogen to keep the satellite dry and clean while preparing for launch. Musk pointed out that Space-X could have the same facilities built for his systems, but doing so would double the price. That’s still a third cheaper than the two rockets from ULA. The second argument was that ULA has a very reliable pair of launch vehicles with long track records. Space-X has a much newer vehicle with a much shorter record, but it also has a much higher manufacturing rate.
ULA has a limited lifespan under those conditions, so they had to innovate. They have announced a partially-reusable launch vehicle called Vulcan. Ironically, by the time Vulcan is flying, the positions will be reversed and Space-X will have a much longer flight record. The only way for Vulcan, or similar projects from Europe, to be viable is to further increase the flight rate. That means finding roughly four times as many payloads as are currently flown. We will need a revolution in satellite manufacturing, because the current methods for building satellites are matched to the current rate of building launch vehicles.
So Space-X is also going into satellite manufacturing.
Musk chose to go after industries that are able to be revolutionized because they have been working from analogy for 40-90 years. He came from the Internet software services industry, which did not exist twenty years ago. It was also born of the computer age, which is still experiencing exponential growth after fifty years, and has built its methodologies to work efficiently when everything is moving very quickly. Aerospace was exponential for seventy years, but abruptly plateaued around 1972. Automotive engineering is even older. It only became technologically interesting again recently with the addition of computer technology. But the internal combustion engine, like the chemical rocket engine, was refined by analogy for decades with few new inventions. As the information age begins to level the curve of Moore’s Law, investment looks for new opportunities. The collision was natural, and has been mimicked in some ways by Google’s investments in satellites and launchers, Amazon/Blue Origin, and so on. I chide Apple that they are the only large Silicon Valley computer company without a space program. Even they are looking at cars, though.
As we dive deeper into invention and innovation, and the history of it, we will find that Musk is not alone. First Principles are mirrored in nearly every dramatic innovation. Nor is it Musk’s only strategy.
Interestingly, the old “reason by analogy” companies are starting to reason by the new analogies provided by Space-X and Tesla. The Chevy Volt was created because an executive at GM questioned his engineers that, “If a tiny company in California can do this, why can’t we?”
What if you go past the “raw material cost” line and move it as well? Platinum and other precious metals are exceedingly rare on Earth, but can be found in abundance in some asteroids. By mining asteroids, we can actually expand the raw material supply and therefore lower the cost via the law of supply and demand. If platinum were half or a tenth the price, we will eventually find new practical uses for it. Planetary Resources goes to the heart of the matter concerning rare materials. Such systems may eventually become cost effective due to cheaper launch vehicles from Space-X and their competitors.
Or as they used to say in the L5 Society (before it became part of the National Space Society) – “Ninety percent of the materials available to humanity are not on Earth.”
What does ancient Greek philosophy have to do with entrepreneurship and invention? Quite a bit, actually.
Plato made a distinction between the concepts of form and substance. There are a number of related concepts from others of that time, but we’ll focus on these two terms first.
In the category of form, we put anything that is not physically bound to matter. These are things like math, information, data, and so on. It can also include more personal concepts such as love, responsibility, and virtue. Additional synonyms in today’s culture would be data, information, and software.
In the category of substance, we put anything that is matter – the human body, 20 tonnes of steel in a warehouse, and the device on which you are reading this. The information itself is form – the device is substance. Additional synonyms in today’s economy would be commodities, hardware, and real estate.
You could have form without substance (math, etc.), or form with substance (organized matter), or substance without form (a chaotic mess). Nearly every idea and interpretation in the ancient Greek world could be placed as a range on this continuum between pure concept and pure chaos. Stars were unmovable perfection, planets (and the Greek gods associated with them) less so (hence all the many loves of Zeus and various other less-than-perfect behaviors). As for humanity, “…man was given a towering head and commanded to stand upright, with his face uplifted to gaze on the stars of heaven.” (Metamorphoses 80-89) In other words, you may in part be a chaotic animal, but you can perceive unchanging ideals (Logos), and be guided by them like a sailor following stars through a chaotic sea.
In Plato’s thought, the idea was that there were perfect mathematical forms off in the heavens, and every attempt at a perfect form, or crude attempt at one, was simply a “shadow” of this conceptual mathematical geometry off in the ether. Aristotle was more focused on physical substance than perfect forms, on the concrete rather than the abstract.
In the painting above, Plato (left, pointing up at the heavens) and Aristotle (right, hand flat and representing the earth) represent the split between heavenly abstraction and terrestrial specifics.
In another sense, they represent the opposite directions of taxonomy. Plato’s perfect forms represent a way to see many entities by common attributes, and therefore groups information into categories. Aristotle was seeking to classify things by their differences into specific, individual entities. We usually hear the word taxonomy in two fields. The first is science, where genus, species, and so on are used to divide and group classifications of life forms. We also see it used for other areas such as geology, chemistry, and astronomy. The other area we see the word taxonomy is in database design. Business analysts use the term to divide information and group it in ways that allow databases to be built logically and at a maintainable scale. The process of breaking things apart and putting them back into cleanly-organized attributes is called database normalization.
In the 1300’s, when Dante Allegri wrote The Divine Comedy, Western culture had a clearer view of the nature of matter and information. In his story of ascending to Heaven, he sees people sharing love and knowledge and becoming more “rich” by giving more away. This did not make sense to his character, because we tend to think of scarcity in our material economy. Note that one oddity with sciences at the time was the theory that light went FROM the eye toward things that were bright, not the other way around. (Ironically, a ray-traced computer image tries to simplify the problem of showing a three dimensional scene by only modeling the light that goes towards the viewer, not every light path from every light source in the virtual space. The computer therefore starts at the screen and works backwards to the light sources. So while not true in the real World of Substance (Heisenberg notwithstanding), it can be true in the world of video games and other modern Worlds of Form.) So anyway, Dante:
What did the spirit… mean by… Division and Partnership?…
How can it be that a shared good makes a greater number of possessors richer by it than if it is owned by a few?’
And he to me: ‘Because you fix your eyes, again, only on earthly things, you produce darkness from true light. That infinite and ineffable good, that is up there, rushes towards love as a ray of light rushes towards a bright body. The more ardour it finds, the more it gives of itself, so that, however far love extends, eternal good causes its increase: and the more people there are up there who understand each other, the more there are to love truly, and the more love there is, and, like a mirror, the one increase reflects the other.Dante, Purgatorio Canto 15, 37-81
Division (substance) has the following attributes: when one divides a collection of matter, one reduces the value of the source of the collection by subtracting matter from it. Property can be divided. One benefits by taking that which is material and consuming it, such as food or fuel. Information is more valuable if it is proprietary, because goods made with that information can be scarce and therefore valuable. Units of value are represented as money or units of commodities or finished goods. Since humans inhabit the physical world, we need these things – food, fuel, clothing, and so on – to survive. If there are no external sources of value feeding the system, it is a closed system. Players in this closed system, if that system is static and lifeless, are justified in seeing it as a zero sum game, where no one can add value without someone else loosing it. During the Mercantile Age from 400 to 250 years ago, this was the prevailing aspect of western thought. Nations had very strong state control of economies to maximize the value of export and minimize imports. They banned the export of gold and silver, limited wages, and tried to maximize domestic resources while restricting consumption.
In Partnership (form), value is represented by knowledge, data, or virtues. Knowledge can be copied indefinitely rather than split, and it gains in value to the culture the more it’s copied. Anyone who takes knowledge can benefit. On the virtues, integrity can be modeled for others, and both the others and the modeler will grow in integrity. Information is more valuable if it is openly distributed. Since humans are social creatures and knowledge workers, we need Partnership to survive. This is an open system. It allows for value to be created within itself from art and science. It also allows learning to come from outside sources without depriving those sources of those information assets. Information can be readily copied to spread value across more recipients.
In this 700-year-old poem, we also see the core concepts of the Open Source movement. Culture becomes richer as work is shared within the information (form) aspect of the world. Open source servers such as Apache and operating systems such as Linux have revolutionized web design, education, software development, and communications. In the beginning, the open source version of the Unix operating system, called Linux, was considered inferior because it was considered impossible to get the same quality standards with thousands of volunteer contributors as it would be with a team of hundreds of dedicated, skilled employees. But a funny thing happened. They eventually realized it was superior to the commercial product for that very reason. It was being “tested” by millions, and in a community like this, well… To paraphrase Dante, there are more who do quality control, and the more quality there is, and like a mirror, the one increase reflects the other.
Open Source Linux blunted the growth of the Windows Server operating system, which was ascending steadily until it suddenly went flat in the mid-1990’s. As the web became a market, Linux servers exploded in popularity and along with them, became the basis for most web systems. Open source dramatically dropped the barrier of entry to becoming an inventor, a creator, a writer, programmer – really any task that involves creating in forms or learning the forms behind a physical task, such as the knowledge (form) on how to fix a sink (substance). If you want to do 3D CAD design work or model chemical reactions, you have a choice between $5000 professional tools or free ones that will take a little more effort to learn, but produce the same results. Classic writings that were out of copyright became available for free thanks to Project Gutenberg, so anyone could learn the knowledge of the past as well as build the future.
The line between form and substance intersects when we talk of 3D printers. There is an odd “Digitophany” (digital made manifest, or visible) that makes even crude 3D printers seem very slightly mystical in their form and function. I can take a file, download it, and then send it to my printer to make a physical object out of plastic. The cost of this object is the cost of the plastic by weight. I can modify these forms or create entirely new ones on my computer, then convert them to substance with a combination of plastic, energy, and time. In the modern information economy, the line between the value of knowledge and the value of goods is far less clear than in past history. That said, a 3D printer is useless without a few kilograms of substance with which to print.
There is another place where the line between form and function blurs, and the ancients knew this as well. Humans are also a mix of form and substance that knows itself and the universe. The human is a form that can make form – that is, abstract ideas, and a substance that can shape substance. Where humans are unique is that we can take forms that never existed before and shape the material world into substance that has never existed before. We’ll get more into that in the next section. Humans are a messy mix of pure abstract logic and pure chaotic mud, but we are unique in that we embody the whole range between form and substance.
Our robotic efforts are a subset of this mix of abstraction and material – a child effort made in the image of their creators. If a human is soul and flesh, then the robot is math and metal.
Building on the concepts of Form and Substance, we’ll get deeper into how the mind invents in the next section.
How Observation becomes Symbolic Language. Note how the substance dissolves into form as the observed object is transcribed into the imagination.
How Observation becomes Symbolic Language. Note how the substance dissolves into form as the observed object is transcribed into the imagination.
There are a number of theories on how to invent things, and how to stimulate creativity. Creativity is not the same as invention. Creativity simply means to bring something about that is original with no regard to it also being wise or useful. Invention tends to work a problem and apply a solution. Creativity is a step in invention, just as mining metal is a step in building a car. But there is much more to invention than creativity.
We are going to reduce things to core terms that have accepted meanings going back hundreds if not thousands of years. This is why we started the discussion with Form and Substance. The source for much of this work is the Trivium – a book that summarizes teaching of Grammar, Logic, and Rhetoric. I will also refer to other sources and methodologies both ancient and modern. Some ideas I will discuss later are entirely my own. If I use the term “traditional”, however, I’m probably referring to the Trivium as an ancient and established source of learning and teaching. Much of the methods and structures of this teaching method were lost in the twentieth century. I’ll leave it to others to explain the details of why mass-produced Pavlovian students are creative, not because they are educated, but in spite of it. This may have worked in the industrial age of mass production and workers who had to do simple, repetitive tasks. If you’ve read this far, however, I assume that you aspire to something more interesting.
A visual artist works with four attributes to an artwork – Line, Shape, Color, and Texture. Many hours are spent trying to blend paints to get colors correctly represented, sculpt paint on a canvas to imply the appearance of metal or fabric or water or sky, and so on. The first tool in each case is vision – you must be able to perceive these attributes in the subject to represent that subject in the media of the artwork. By explaining Form and Substance, we’ve just made a distinction between the paint and the canvas. Now, we will expand this grammar of conceptual thought to explain the brushes and paints.
“There is nothing in the intellect that was not first in the senses, except the intellect itself. Human intellectual powers need material to work upon. This comes from nature through the senses. Nature provides the materials, and the human intellect conceives and constructs the works of civilization which harness nature and increase its value and its services to the human race.”The Trivium, Sister Miriam Joseph, C. S. C. Ph. D., Page 22.
This section borrows heavily from the chapter on the nature and function of language in the Trivium, above. There are other works called The Trivium, just as there are other textbooks called “Basic Chemistry”. But the work I cited here is considered the most definitive at the moment. I’ve seen another work on grammar that is part of a Trivium set, but it focuses entirely on words for word’s sake, not words for symbolic idea’s sake. Grammar is the art of inventing and combining symbols. If you focus only on words, you’ve missed diagrams, signs, musical notation, illustrations, flowcharts, and any other representation of ideas and works that can be shared across distance and time.
The steps in going from perception to abstraction are summarized as follows:
The mind may then learn of the world directly by comparing the essence, the attributes, of different objects and classifying each individual by species, genus, and aggregates. Language allows for both specific names for individual objects and general names for species based on attribute names that apply to essence. This language leads to Symbolism – the ability to represent not only objects, but the essence of objects, individuals, species, and aggregates as abstractions along with the concept of the objects themselves.
We have a natural mental scale to the naming of objects. We do not generally name specific blades of grass or rocks unless we are studying them in depth. Scientists working with Mars probes often come up with names for specific rocks in an image so they can discuss them as they decide where the rover is to drive next or what data they got back when drilling into a specific site. With symbolism, we can not only process the species, aggregates, concepts, and so on in our own mind, but we can communicate them to other human beings. We can encapsulate them in text which may be read hundreds or thousands of years later. We may even describe an object in sufficient detail that a robot can locate it within an aggregate, such as finding a part in a bin or a bar code on a wall of boxes.
Another power of symbolic classification and labeling, known as language, is that we can describe objects that do not exist at all, such as a unicorn, a planet orbiting between Earth and Venus, or a fictional character. We can Create concepts that do not currently exist by arranging the symbols into logical constructions that clearly articulate a new concept. We can also describe things using symbols that are entirely without substance, such as pure math.
The process of Invention, therefore, is essentially the mirror image of perception and analysis. We learn enough about the objects in the world that we have a vocabulary of symbols and a taxonomy of examples. We can then arrange, purely in forms within our minds, the symbols, attributes, and so on in the virtual workshop of the imagination. We can conceive of a car that has the attribute of exceeding the speed of sound. We can then use attributes from the species “things that exceed the speed of sound” (jet engines, rockets, etc.) and combine them symbolically with the concept of a “car” (four wheels, does not leave the ground, steering wheel, driver, and so on). We can then add things that are not part of either group, but are analogous and fulfill the same function. Cars like this require wheels made of aerospace-grade metals, which have no practical application otherwise. They must be crafted to the task at hand. However, they share the attributes, are part of the species, of the symbol we call a “wheel” in that they are round objects on an axle that support a ground vehicle. We have now expanded the genus of “wheel” to include these new species in the taxonomy tree. We may even find a practical application for them in a high speed train or centrifugal piece of industrial equipment.
We can then use this level of abstraction, the symbolic language in words, numbers, drawings – and use it to communicate to other humans and to computers needed in the design process. We can classify the parts and provide attributes of strength, weight, and so on. We can then use taxonomy to determine which parts exist (can be ordered) and which parts must be fabricated in a workshop. If we determine the attributes of a part are beyond the budget of the project, or cannot be fabricated with available components, budgets, or technology, we can scale the project back or cancel it altogether. But symbolic logic is of value to a social species such as humanity. We may not be able to fabricate a car that can go four times the speed of sound, but we can write a story about what it would be like to drive such a vehicle. We can also come up with a fictional design that allows the observer, the audience, to also imagine such a car in detail. We can come up with dozens of such designs in an afternoon on a pad of paper, expressed in the same symbolic language of sketches, captions, and other tools of the imagination. We can simulate driving such a vehicle in a short movie. That movie may inspire someone in a future generation to revisit the idea. If the technology exists in the taxonomy, it may happen in substance as well as form.
Buck Rogers/Apollo Era Poster (Ray Bradbury estate)
It already happened with crewed rockets and space stations, which were predicted in science fiction long before they existed. I have a poster on my wall from the estate of Ray Bradbury. It contains, without comment, a series of cells from the old Buck Rogers cartoon strip from 1929-1946, followed by photos of the technology discussed in that cell as it existed in the early 1970’s. The cell/photo combinations describe a pair of spacecraft in orbit together, a scuba dive, a space capsule returning from space under parachutes, a jet pack, a spacewalk, an instant camera, a space station, a nuclear power plant, a monorail train, a personal submarine, a Mars probe, a video phone, an undersea base, a moonwalk, a view of Earth and the moon together from space, a lie detector, a walking industrial-sized robot, a nuclear submarine, a moon rocket, and another moonwalk.“The human intellect conceives and constructs the works of civilization.” And if they can’t build them in metal, they will draw them in ink for future generations.
We will discuss the attribute of time and invention later in this series.
(Co-Written with Nadya Klunder)
Peter Thiel’s Founders Fund has invested $200 million in Stemcentrx to develop cancer drugs. Here are some key reasons why this is happening, and how to apply those lessons to your own efforts.
Like President Nixon in 1972, President Obama has just announced the new strategic goal – a “cancer moonshot,” to “cure cancer once and for all”. The goal is to find a single drug or new technology to cure cancer without radiotherapy or any other side effects. Successful accomplishment of this goal will save millions of lives around the world.
Every year around 14 million people worldwide learn they have cancer, and 8 million people die from the disease. In the US from 1950 to 2005, the percentage of people people being diagnosed with cancer has only dropped five percent per capita. That said, the mortality rate has dropped 26 percent per decade for the youngest groups and 6.8 percent per decade for the oldest between the years 1950 to 2008.
Peter Thiel is known as the first outside investor in Facebook, cofounder of PayPal and present head of the investment firm Founders Fund. His group has recently invested $200 million in Stemcentrx, a private company in San Francisco developing cancer drugs. This is the largest ever bet on a startup biotech company.
The Stemcentrx main approach to cure cancer is targeting naturally-occurring stem cells that may be pre-cancerous in the body. Discovered in 1960, stem cells offer new options for treating diseases such as heart disease, diabetes and cancer. Pluripotent stem cells can divide into more stem cells or can become any type of cell in the body. The stem cells self-renew within the damaged part, promoting growth of new tissues and subsequently replacing the diseased tissues. However, there are many unexpected side effects: when such cells are injected into patients, they can produce tumors from rapid growth of unrelated types of cells, spontaneous cells. Stem cell treatments are still in the research phase, and it is important to understand how stem cells become specific cell types and to find a way to control this process. While we hear about tumors as a side-effect of some forms of stem cell therapy, a similar issue may occur with stem cells that develop in the body naturally.
At Stemcentrx, they believe that these natural stem cells are the origin of different common cancers. However, their hypothesis that cancer is caused not by any spontaneously growing stem cell but only by rare specific stem cells is not commonly accepted. Thus, the company is focused on identifying the cancer-inducing stem cells via a unique molecular marker for such cells. Confirming evidence has been found so far for leukemia, breast cancer, and lung cancer stem cells.
In their experiments, they inject human cancer cells under the skin of lab mice. The growing cancer tissues are then further divided with different types of cells, which are then tested using other mice. The procedure is repeated until one type of cell (the cancer stem cells) is identified which is as capable of tumor creation as the original sample.
One very expensive issue with most pharmaceutical development is that genetic differences between mice and humans. A billion dollars may be spent finding a drug that shows promise in lab animals, which then fails completely in human trials. By using human cancer cells at the lab animal phase, Stemcentrx is avoiding this misinformation almost completely. This will both speed development and avoid wasted investment in therapies that do not translate to patients.
One of the main challenges of biological and biotechnology studies is “randomness”. There are too many factors affecting experimental results. Almost all drug development must work with very poor signal-to-noise ratios, and therefore must expend billions of dollars and many years to demonstrate reliable results. Stemcentrx is attempting to use rapid-development technologies to eliminate as much noise from the development process as possible, and therefore increase both human health options and return on investment by shifting probabilities.
According to investors, Stemcentrx was designed “to get these probabilities as close to one as possible at every step, to get rid of as much of this randomness or contingency as possible”. Key investors give Stemcentrx a high probability of success, because the Stemcentrx cofounders Brian Slingerland and Scott Dylla have unique and enormous potential and complementary skills.
Stemcentrx has already demonstrated very promising early clinical results for an antibody drug. This drug was shown impacting stem cells that appear to cause small-cell lung cancer in a study with 80 people. A larger study with this drug is planned. Presently, they are running clinical tests using three drugs they have developed. Stemcentrx working hypothesis, that destroying relatively rare cancer stem cells leads to completely combating the cancer, is showing promise with some cancers so far.
However, there are critics who debate the stem-cell theory based on some experimental results. One convincing case came from skin cancer studies. It demonstrated that about a quarter of melanoma cells from humans were able of induce cancer without a special, rare stem cell. To validate the scope of the cancer-stem-cell theory, more clinical trials are needed with different types of cancer.
Many books have been written on entrepreneurship, including one from Peter Thiel. One key aspect promoted in Guy Kawasaki’s Art of the Start is to have two founders with complementary skills. This is originally based on Guy’s experience with Apple (Steve Wozniak and Steve Jobs), but could be applied here to Brian Slingerland and Scott Dylla.
Peter Thiel, with his background from the software industry and interest in life extension technologies, is the ideal investor for a company that seeks to use accelerated development methodologies from rapid growth industries and pair it with the slow and noisy traditional processes of pharmaceutical development. He is also an early investor in Space-X, which did the same thing to the moribund technologies of satellite launch.
Also, like Space-X, Stemcentrx has an extensive in-house capacity for prototyping and production. Presently this company has very high level biotechnologists, a “vivarium” with 18,000 experimental mice, and a factory for producing their experimental drugs. Investigations of at least 10 types of cancer are in their plans for the next two years. Almost no development takes place outside using other facilities or subcontractors.
Space-X has a similar centralized production model. The key advantage of this is that you keep the engineers close to the production teams, and therefore avoid misunderstandings between theory and practice. You also are more capable of producing things in house quickly without having to depend on outside resources. It’s also vital in keeping trade secrets in-house. This same model was used by Lockheed “Skunk Works” for advanced aircraft development for the last fifty years. Earlier examples include R. G. LeTourneau, who used a similar method to develop advanced earthmoving equipment in the mid-twentieth century.
“I needed my own mill in which to prepare billets for forging, one very good reason being that even if I could get a steel company to prepare these special billets for me at enormous cost, I didn’t want to wait six weeks for a rush order to be filled. I am one of those who, if he gets an idea for a 100-ton capacity crane hook, wants to see it lift 100 tons first thing in the morning.”R. G. LeTourneau. Mover of Men and Mountains, Page 239.
Will they cure cancer, or at least some varieties of what that broad term describes? It seems quite likely they will either solve some cancers, or find out much more quickly than their peers that they should find a new hypothesis. There are really three keys to their potential success– the stem cell theory, the rapid-development methodology producing accurate results, and the lab infrastructure to test the theory using the methodology. Theories, being “form”, are essentially “free”. Labs are material and expensive. Methodologies are somewhere in between, because your methods dictate your equipment and skill sets. They could be wrong in their theory, but they could rapidly adjust and preserve their investment in development methodology and testing hardware by applying a revised or entirely novel theory. They are leveraged correctly to advance quickly, right or wrong.
At any rate, bear these lessons in mind. They are worth knowing, regardless as to whether your moon shot efforts are literal or metaphorical.
The left side shows the parts of the brain that move our body parts (motor strip). The right side shows the parts that sense our environment.
The Cortical Homunculus diagram shows how much of the brain is devoted to various parts of the body. The motor strip (action) parts of the brain “wiring diagram” are on the left, while the perception parts are on the right. Note the large percentage of these areas devoted to the hands. The second most important part of the operation involves the face and tongue. Humans are built from the brain out to be builders and communicators. This section explains the importance of this mind/body/environment loop.
According to classic Liberal Arts (the Trivium), “Each of the liberal arts is both a science and an art in the sense that in the province of each, there is something to know (science) and something to do (art).” Art is also defined as something you get better at with practice, whereas science is simply known or unknown. One either knows the boiling point of water at sea level or one does not. Painting, writing, or music are arts in the sense that one (hopefully) improves with practice. Bear in mind we are reducing these terms to their core meaning, not referring to the fields of art and science as a whole.
Symbols are how we represent, record, calculate and exchange ideas. These symbols may be letters, numbers, mathematical and chemical formulas, musical notes, lines, shapes, colors, textures and so on. Humans have the ability to render meaning through symbolic media such as writing, speech, drawing, and other methods.
This symbolic conversion, and conversation, is a common thread of art and science. Symbolism allow us to store and transfer both the “noun” of static knowledge (science) and the “verb” of developing skills over time (art). Having this common thread between both art and science allows us to move from one level of skill and knowledge to new ones through invention and discovery. It also allows us to consolidate knowledge into “chunks” for easy recall and analysis.
Invention is both an art and a science – it is rooted in knowing, but improves in quality with repeated work at physically building the item being invented. We must represent the problems and existing solutions symbolically, through knowledge (science). We also develop new ideas to resolve these problems over iterations or insights – again first through symbols (the science of recording the problem and the “as-is” state of solutions), and then through physical or symbolic design (the design and analysis of the new or “to-be” solution being invented).
We associate science and engineering with each other the way we associate art and science, and for the same reason. Engineering and Science depend on each other and enhance each other, in much the same way a left and right leg enhance walking. Each step uses the previous step of the other leg as a foundation to move forward. We use new material science to engineer better instrumentation. In this way, science boosts engineering. That boosted engineering, in turn, leads to better instrumentation to advance material sciences. It’s said that one of the first things a blacksmith makes once they learn their craft is a better set of tongs. By doing so, they become more productive, and therefore can make other items more comfortably and efficiently. This cycle goes back and forth in all modern sciences and industries. A key example is using more advanced computers to enable the design of circuitry for still-more advanced computers.
The pattern of advancement is not self-propagating – there must still be creative humans and a steady stream of investment in the loop. But the loops in critical industries – this feedback loop of humans, machines, sciences, and investors – has kept most technology advancing at various speeds consistently since the beginning of the second industrial revolution. It has worked in fits and surges prior to that from the first industrial revolution back to the dawn of civilization.
People often speak of this area of study as STEM, which stands for Science, Technology, Engineering, and Math. Some add Art to the list and change the acronym to STEAM. This is rather messy nomenclature, rooted in educational subjects rather than the root terminology. Math is a science, and technology is a product of engineering. Art is not a separate category in the pure sense. We need artistic methods for things like user interfaces, digital renderings, visual communications, and so on. STEM, broken to categories, is a mix of the way of doing (engineering) with the way of knowing (science and it purest expression – math), along with the products of those three – technology. Art in this case is simply a specific expression of doing, but with different methods and media (usually) than those used by the engineer. Art (as a product) is also the purest form of symbolic expression, be it representational or abstract.
There is much to be said about the relationship between arts and sciences, but the key focus here is the relationship between symbolism and learning (science), as well as learning by doing (art).
There are different ways that humans learn. This is true whether one is learning from an instructor, reading a book, or inventing a field of discovery in a laboratory. When information is being communicated from a person who knows the science and practices the art (teacher) to a student, they may use verbal, written, visual, or kinesthetic (action) methods.
The first three methods transfer science, or knowledge. The last method, also called “learning by doing”, transfers both science and art. One cannot become a professional athlete, painter, or sculptor simply by reading about it. The mind/body interface needs to be “rewired” through practical motion to operate a paint brush, welding torch, or fiberglass resin brush correctly. There is a key interaction between these two categories of learning, just as there is a key interaction between arts and sciences themselves.
The sciences and symbols are communicated to the conscious, higher mental functions from outside the individual person. This communication allows learning via the medium of transferred symbols, such as speech and text. Once one understands intellectually WHY and HOW to do something, and with what, that knowledge guides the ability to wield hands and tools. One slowly, by doing, links the intellectual, conscious abilities with kinesthetic motor skills. This forms a feedback loop that enhances both knowledge and art. One learns at the material level how to correctly wield tools by defining the motions before the action, and evaluating the quality of the action after each step. One learns exactly how hard to hit a chisel to split plaster versus stone, or which angles to hold a fan brush comfortably while painting a sky.
Some motions will become more natural and “pre-programmed subroutines” over time, such as the angle to use a chisel, torch, or fan brush. While this is going on, one also gains a “feel” for the tools and media. One realizes just how much flux to add to a welding bead or how much cobalt blue to mix with white to make an evening sky. These methods also apply to me typing these words, as I think of sentences and simply let my fingers, after decades of practice, convert those words into symbols. What was once a learned behavior in High School typing class, and became natural in college programming classes, is now something I no longer think about at all.
There are several lessons to draw at this point.
Learning arts is not easy, though some arts, like some sciences, are easier for some people than others. I can build a bench, but don’t ask me to play baseball or piano. It’s possible I would be better at these things had I the right instructor in childhood, or even now if I put the time in. I know a number of people in their forties who have learned how to sing well after a lifetime of frustration for both themselves and anyone within earshot. Even a professional opera singer I know says her practice sessions are not easy on bystanders. So how does one go from learning something cognitively to knowing how to physically craft and create with skilled hands? How does one cross the gap between conscious and subconscious symbolism? By “subconscious symbolism”, I mean the process by which we write neural “subroutines” to say, “Decide if the pitch is a strike or ball” or “type the letter Q”. This is usually called muscle memory, but can also apply to snap perceptions as well as reflexive actions. This transition has three key pieces – the symbolic science, the motor-skill art, and the ability to communicate the relationship between them clearly.
When I was in my early twenties, my father was teaching me how to taxi on the ground in a twin engine aircraft (a 1953 Piper Apache, specifically). When we came to a turn on a taxiway or runway, he told me to “lead with the engine”. When I attempted to turn it like a single-engine aircraft, I would get a sharp rebuke to “lead with the engine”. My father was a production test pilot in the 1950’s with 1.3 YEARS of logged air time, an aircraft and power-plant (engine) mechanics license, and too many accomplishments and adventures to count. He knew both intellectually and physically how to fly an aircraft far better than I ever could. But unfortunately, this led to some abrupt symbolic shorthand when describing processes he’d long since subsumed into his subconscious mind in favor of knowing new abstractions, like knowing which switches to flip when a six-engine jet is on fire.
Over the course of a few tries, I worked out what he meant. Here is a breakdown of the process of making a turn in a twin-engine prop aircraft on the ground.
There is also the issue that nose wheels are expensive, as are brake pads. Pilots tend to do as much ground steering and stopping with fuel, flaps, and elevators as physics will allow before resorting to depreciating the wheels and brakes with wear and tear. While all this is going on, as with a single engine aircraft, you are being mindful of the winds and angling the control surfaces so that a gust will drive the plane downward into the landing gear safely rather than tip the aircraft like a leaf on the wind.
So… Got all that? Did you get all that from “lead with the engine”, or did it have to be expanded a bit? Those four short words do encapsulate the concept of using the engines to set moments of inertia and minimize the stress on the landing gear. My closeness to my father was helpful in unpacking his tendency to say things in short bursts. For the record, I have to rewrite these chapters at least twice to overcome my own tendency to say things in personal mental shortcuts.
It is key to really, completely understand the key concepts before moving on. You should know your basic sciences and arts like you know your own phone number and address. For that, you will need good communicators as your mentors. Which is the other reason I keep rewriting these chapters for clarity – so that my work will be of value to you, the reader, in forming these foundations.
One of the beauties of symbolic writing and representation is that your mentors don’t have to be physically present, or even alive. Leonardo di Vinci is still teaching artists and inventors five centuries after his death. You just learned how to turn a twin engine aircraft on the ground from my father, who passed away in 2004. For the creator and teacher – your best students may never meet you in space or time, but may only be learning from the symbolic artifacts you leave behind. By extension, one can also leave a legacy of transferred skills with students, and the artifacts they, in turn, leave behind.
We have an example with European martial arts. We tend to think of martial arts as Kung Fu, Judo, or other Asian fighting skills that have been passed down from master to student, uninterrupted, for centuries. In Europe, skill with longsword techniques peaked several centuries ago, then died out with the invention of personal firearms. All that remain are woodcuts diagrams with intentionally-cryptic descriptions. This was to allow the instructor to make a living teaching students personally. The terms in the inscriptions were meant to be reminders to students who he had taught, rather than knowledge transfer to people he had not met. As such, it has taken much effort by modern martial artists to reconstruct the techniques. Even then, there are some actions that are taught two different ways, because either method matches the woodcut drawing and description equally well.
While the phrase, “lead with the engine” was maddening to me in my twenties, it was a key bit of symbolic shorthand to my test pilot father in his twenties. With great skill and knowledge, the mind tends to group, condense, and distill complex building blocks of thought into small packages with short labels.
The key point here is summarized in a 1956 cognitive psychology study called “The Magic Number is Seven, Plus or Minus Two” by George A. Miller. This relates to the idea of working memory capacity. The ability to break complex thoughts down to seven components, or abstract simple ones up to seven components for more detailed analysis, is called “chunking”. It has all kinds of applications, from the length of phone numbers (seven digits) to advertising jingles and hooks in pop music choruses. The mind has a tendency to start dropping key elements when one has to deal with ideas with more than seven components. Astronaut and advanced pilot training involves putting the subject in a simulator and throwing more and more problems at the pilot until they start making mistakes. The art of passing the test is to handle as many problems as possible with skill. Once one is overwhelmed, one has to drop the problems in the correct order, from the least significant to the most dangerous.
One can only get so far with a few elemental chunks. To handle complex concepts, one must lump these elements into more complex “molecules” with their own properties. One can then work with the complex concepts as if they were simple. My father had a single mental box labeled “lead with the engine.” He had used as a single concept for so long (over four decades at that point) that he had, to some degree, lost the natural verbal ability to unpack it.
If one concatenates thoughts into symbolic shorthand, one effectively can put more “chunks” into a mental theory or concept than someone who has to have everything broken down to the smallest possible building block. Genius, to a large degree, can be thought of as how well one can manipulate complex concepts as if they were simple ones.
One must be careful to put one’s molecular concepts together accurately. A misunderstanding at the early stages of learning will result in skewed results for as long as that block remains intact and unexamined. Entire fields of academic thought are built around intentionally or unintentionally flawed core concepts.
We have similar shortcuts imposed in education all the time. One if my friends is a textbook editor. She disputed the point in one textbook that people thought the world was flat, then after Columbus, they realized it was round. The fact is, people knew the world was round for many generations prior to that point. The response from the educational establishment – “We know… but it’s easier to teach this way.”
A true master of a field can not only assemble complex thoughts from existing symbolism, but break down the terms of the original science to look for errors.
My brother was a chemist at a major earthmoving equipment manufacturer. They received one of one hundred advanced spectrometers with advanced computer controls. He immediately checked the calibration of the instrument against wet chemistry methods, which are considered a gold standard for chemical analysis. In so doing, he found numerous software bugs that made the instrumentation’s readings highly suspect. He wrote a long bug report of the issues he found and e-mailed it to the manufacturer.
A month later, a new software release was announced by the manufacturer. He installed it, then rechecked the results. Finding them accurate, he put the instrument into production.
A year later, he went to a conference of all the users of the instrument, across many industries and manufacturers on the same scale as his employer.
He went to the booth and said, “So, I guess you got a lot of complaints about that first software release.”
“No.” – came the rather passive response.
“Wait… how many people complained about it?”
Let that sink in a bit. For a month, many top industries on the scale of his were doing analysis and quality control with bad instrumentation. I’m not sure which ones, or if they rechecked things later and caught errors, or if there was a lasting impact. But there it is – all from one software release for one industrial instrument. And there are thousands of such instruments made. Each one forms a sort of “symbolic shortcut” in our industrial and scientific infrastructure as a global economy.
My brother told his sons, both of whom have MS degrees, “Never trust software results. Get out your scientific calculator and check the results before trusting the software.” One son did so with civil engineering software on water tower design and found similar bugs.
When my father returned from World War II, and before going on to be a pilot, he worked as an electrical engineer at a tractor factory in Canton, IL. His future father-in-law worked at the same plant. They were trying to figure out why an electrical panel would not operate as intended. My father took the panel apart, looked at the wiring on the back, found the error from the factory where it was built, fixed it, and reconstructed the panel to work as intended. He got a reputation at the factory as a genius from that moment. I’m not sure if this helped the process of my father and mother getting married and starting a family, but it certainly didn’t hurt the situation. Later on, when he was doing production test flying of the B-47 Stratojet, he was the only one who knew the entire electronic/electrical system of the aircraft. Even the men who originally designed it knew their own parts well, but not the whole. He had an excellent motivational poster at work. As the test pilots arrived, there was a sign over the door that said, “What you don’t know about the B-47 will kill you.”
It was not an exaggeration. My father quit after four years because, as he concisely stated, “Most of my friends were dead.”
ALWAYS check your complex concepts, your terms, your shortcuts, formulae, software, and equipment. Know the roots of your learning historically, and from multiple perspectives. If you are inventing something new, validate it against the hardest sciences possible, from as many perspectives as possible. Do the math – forwards and backwards. Consider sources.
The best inventors, or artists for that matter, know their media by having worked in it for years. An architect may go to a CAD system or drafting table and do designs, without ever having nailed a board or poured concrete. Such an architect is not going to have a kinesthetic sense of the materials with which buildings are made.
However, look at the greatest inventor/entrepreneurs. They got their hands dirty in the fields where they did invention. R. G. LeTourneau worked in a metal foundry at age 14 in the year 1900. Edison, Tesla, and so on physically built their inventions. Lockheed Skunk works, which built the most advanced aircraft of the Twentieth Century, was unique in that they put all the engineers and designers in with the assembly workshops. This closed the loop between thinking and doing as tightly as possible for such complex projects. Even artists of earlier centuries formulated their own paints. Burt Rutan refined his knowledge of aviation with model aircraft and work as a test pilot’s flight engineer prior to building his first experimental aircraft.
The best inventors know their working media. The ability to do work with your hands with the design materials, be they software or steel, leads to better and more realistic designs. This is how our brains are wired – so work with it. Once you can work with materials both mentally and physically, you can master the media and create new works that are both realistic and visionary. You learn the subject at both a conscious and subconscious level. Humans are built specifically to work with our hands and senses, and we have the brain maps to prove it.
The process of learning by doing can be complex. Make sure you get good mentors in the craft, or you will develop bad habits that are difficult to unlearn. Know your media, your tools, and your design – both symbolically and kinesthetically. Knowing your media and concepts backwards and forwards, without built-in mistakes, is the strongest foundation for invention and discovery.