Unformatted by Greg Docter

Overprecision is the tendency to believe that our predictions or estimates are more accurate than they actually are (Overconfident about overconfidence)

Quanta Magazine — The New Laws of Explosive Networks

Jennifer Oullette

Percolation transition

The emergence of large-scale connectivity on an underlying network or lattice (Anomalous critical and supercritical phenomena in explosive percolation)

Explosive percolation

“Instead of [of a phase transition] arising from a slow, steady continuous march toward greater and greater connectivity, connections emerge globally all at once throughout the system in a kind of explosion”

another take: Explosive percolation describes the abrupt onset of large-scale connectivity that results from a simple random process designed to delay the onset of the transition on an underlying random network or lattice (Explosive Percolation: Novel critical and supercritical phenomena)

Phase transition

During a phase transition of a given medium, certain properties of the medium change, often discontinuously, as a result of the change of some external condition, such as temperature, pressure, or others (Wikipedia)

Cascading failure

A process in which the failure of any component of a system increases pressure on other components, leading to their failure. Cascading failure is a common failure mode for many types of systems in which components are highly interconnected (Santa Fe Institute Glossary)

Criticality

Criticality is a concept taken from nuclear engineering in which fissionable material is brought together in enough quantity to start a chain reaction (Santa Fe Institute Glossary)

another take: In thermodynamics, a critical point (or critical state) is the end point of a phase equilibrium curve. The most prominent example is the liquid-vapor critical point, the end point of the pressure-temperature curve that designates conditions under which a liquid and its vapor can coexist. (Wikipedia — Critical Point)

a16z — Feedback Loops — Company Culture, Change, and DevOps (Podcast)

Sonal Chokshi featuring Nicole Forsgren, and Jez Humble

Mean time to recovery

The average time that a device will take to recover from any failure (Wikipedia)

Mean time between failures

MTBF can be calculated as the average time between failures of a system. The term is used for repairable systems, while mean time to failure (MTTF) denotes the expected time to failure for a non-repairable system (Wikipedia)

Change-fail rate

The ratio of new features to failures in production (DevOps KPI in Practice)

Leadtime

The amount of time that occurs between starting on a work item until it is deployed (Stackify)

Ribbon Farm — The Holy Grail of Self-Improvement

Tiago Forte

Emergence

A process by which a system of interacting subunits acquires qualitatively new properties that cannot be understood as the simple addition of their individual contributions (Sante Fe Institute Glossary)

“The whole is other than the sum of its parts” (Nicky Case)

Disturbance propagation

The way in which a small disturbance acting on one node within a system can travel throughout the system, effecting other nodes (Adapted from: Disturbance propagation in vehicle strings)

another take: The key point is that extending solutions based on a single node can lead to unintended problems on a macro level. Thus, control structures with only local information fail to be scalable.

The problem can be solved if we include reference information in the control structure (Adapted from: Disturbance propagation in large interconnected systems)

Dissipative structures

Dissipative structures are nonequilibrium thermodynamic systems that generate order spontaneously by exchanging energy with their external environments. Dissipative structures include physical processes (e.g., whirlpools), chemical reactions (e.g., Bénard cell convection), and biological systems (e.g., cells) (Encyclopedia.com)

A dissipative structure is characterized by the spontaneous appearance of symmetry breaking and the formation of complex, sometimes chaotic, structures where interacting particles exhibit long range correlations

(Wikipedia — Dissipative System)

Wednesday, October 24, 2018

Only the Big Ideas #6 — Entropy + biology/software, blockchain + moats, self-improvement + permaculture

Surfacing mental models, weekly

Read 3 articles to learn 10 mental models this week, including:

Entropy
Caching
Ecological niche
Opportunity cost
Stacking functions
Diminishing returns
Economic moats
Incentives
Network effects
Governance

Melting Asphalt — Entropy and Rebootable Processes

Kevin Simler

Entropy

Entropy is just a fancy word for ‘number of possible arrangements’. Entropy is a count of how many ways you can rearrange the ‘insides’ of a thing (its microscopic internals), while keeping its ‘outwardly’ (macroscopic) state unchanged.

The odds of seeing entropy decrease are effectively zero, not because any physical law compels it to be so, but because of sheer statistics — there are overwhelmingly more ways for the energy to be spread out than there are ways for the energy to be contained (Entropy Explained, With Sheep)

Caching

A cache is a high-speed data storage layer which stores a subset of data, typically transient in nature, so that future requests for that data are served up faster than is possible by accessing the data’s primary storage location.

Trading off capacity for speed, a cache typically stores a subset of data transiently, in contrast to databases whose data is usually complete and durable. (AWS)

Ecological Niche

A species’ niche is its ecological role or “way of life,” which is defined by the full set of conditions, resources, and interactions it needs or can make use of. Each species fits into an ecological community in its own special way and has its own tolerable ranges for many environmental factors (Khan Academy)

According to the competitive exclusion principle, two species cannot occupy the same ecological niche in a habitat if they are competing for the same resources (Biology Dictionary)

Stacking Functions

The Happy Philosopher

Opportunity cost

An economics term that refers to the value of what you have to give up in order to choose something else. In a nutshell, it’s a value of the road not taken (Shopify)

Opportunity cost = return of most lucrative option not chosen — return of chosen option (Investopedia)

Stacking functions

“a single input or element that serves multiple functions”

Stacking functions is a primary principle of permaculture and basically refers to elements in your life having multiple functions, instead of a single function (The Art of Stacking Functions)

In permaculture we speak about getting many yields (outputs) from one element (thing) in your system (Heathcote.org)

Diminishing returns

The law of diminishing returns states that in all productive processes, adding more of one factor of production, while holding all others constant, will at some point yield lower incremental per-unit returns (Wikipedia)

When increasing amounts of one factor of production are employed in production along with a fixed amount of some other production factor, after some point, the resulting increases in output of product become smaller and smaller (Auburn.edu)

Turing Capital — Blockchain Moats

Michael Karnjanaprakorn

Economic moats

Sustainable competitive advantages. Economic moats are almost never stable, either getting a little bit wider or a little bit narrower every day (Measuring the Moat — Michael Mauboussin)

A durable competitive advantage that protects returns on invested capital. The dynamics of capitalism guarantee that competitors will repeatedly assault any business “castle” that is earning high returns (adapted from: Hurricane Capital’s collection of quotes from the-above Maubossin piece)

Tren Giffin Charlie Munger on Moats (First of the Four Essential Filters)

Supply-Side economies of Scale
Demand-side Economies of Scale (network effects)
Brand
Regulation
Patents and Intellectual Property

Incentives

Something (financial, moral, coercive, natural/intrinsic) that motivates an individual to perform an action (Wikipedia)

“Never, ever, think about something else when you should be thinking about the power of incentives.”
— Charlie Munger

Network effects

A network effect (a.k.a. demand-side economies of scale) occurs when a product or a service becomes more valuable to its users as more people use it (a16z)

Potential network effects in blockchain: data, protocol, token, monetary, security

Governance

The mechanism for change in a system (Fred Ehrsam)

another take: Governance refers to all actions such as decision-making processes that are involved in creating, updating, and abandoning formal and informal rules of a system. These rules can be code (e.g. smart contracts), laws (e.g. fees for malign actors), processes (what must be done when X happens), or responsibilities (who must do what) (Leopold Bosankic)

another take: Governance of a blockchain amounts to having authority to update its code, which might be done either for technical reasons or to change critical constraints or assumptions (such as the rate at which new coins or shares are issued).

Blockchains must rely on a governance process in which the users agree upon a set of requirements for the underlying software code to be changed, including provisions for dispute resolution, sanctions for violating the agreed upon rules, and procedures for enforcement of penalties (Oxford — Corporate Governance and Blockchains)

Thursday, October 11, 2018

Only the Big Ideas #5 — Quantum computing, Bias, Plasticity, Genomics

Surfacing mental models, weekly

Read 4 articles to learn 10+ mental models this week, including:

Quantum Suprememcy
Qubit
Quantum Superposition
Regression to the Mean
Loss Aversion
Emergent Behavior
Self-Organization
Theory of Minimal Surfaces
Moore’s Law
Network Effects
Winner-Takes-All Market Dynamics

Wired — The Wired Guide to Quantum Computing

Tom Simonite

Quantum Supremacy

The potential ability of quantum computing devices to solve problems that classical computers practically cannot (Google AI Blog, Wikipedia)

Qubit

The basic unit of quantum information. Whereas the state of a bit can only be either 0 or 1, the general state of a qubit according to quantum mechanics can be a coherent superposition of both states (Wikipedia)

Another Take: Quantum computers aren’t limited to two states; they encode information as quantum bits, or qubits, which can exist in superposition…Because a quantum computer can contain these multiple states simultaneously, it has the potential to be millions of times more powerful than today’s most powerful supercomputers. (How Stuff Works)

Quantum Superposition

“The math of superposition describes the probability of discovering either a 0 or 1 when a qubit is read out…A superposition is in an intuition-defying mathematical combination of both 0 and 1. Quantum algorithms can use a group of qubits in a superposition to shortcut through calculations.”

Populism

Kevin Kwok

Regression to the Mean

Extreme outcomes tend to be followed by more moderate ones (Farnam Street)

Regression to the mean occurs when unusually large or small measurements tend to be followed by measurements that are closer to the mean. It happens because values are observed with random error. (Regression to the mean: what it is and how to deal with it)

Loss Aversion

The idea that losses generally have a much larger psychological impact than gains of the same size (Scientific American)

Another take: The key idea behind the bias is that people react differently to positive and negative changes of their status-quo. More specifically, losses are said to be twice as powerful compared to equivalent gains. (The Decisions Lab)

Quanta Magazine— The Physics of Glass Opens a Window Into Biology

Jordana Cepelewicz with physicist Lisa Manning

Emergent Behavior

“The whole is other than the sum of its parts” (Nicky Case)

Self-Organization

Self-organization can be defined as the spontaneous emergence of global structure out of local interactions.

“Spontaneous” means that no internal or external agent is in control of the process: for a large enough system, any individual agent can be eliminated or replaced without damaging the resulting structure.

The process is truly collective, i.e. parallel and distributed over all the agents. This makes the resulting organization intrinsically robust and resistant to damage and perturbations (Complexity and Self-organization,6)

Minimal Surfaces

A surface that locally minimizes its area subject to some constraint. Of all possible surfaces, it is the one with minimal energy (Wikipedia, Math.Berkely)

(this was a tough one to nail down…I’m not satisfied with this explanation, but do believe the mental model has enough utility to include)

Neo.Life — Who Will Be the Google of Genomics?

Andrew Hessel

Moore’s Law

Moore’s law is the observation that the number of transistors in a dense integrated circuit doubles about every two years. Moore’s law is an observation and projection of a historical trend and not a physical or natural law (Wikipedia)

Moore’s law suggests exponential growth. Thus, it is unlikely to continue indefinitely (Investopedia)

Network Effects