Nader

“Recall the metaphor I used in chapter 4 relating the random movements of molecules in a gas to the random movements of evolutionary change. Molecules in a gas move randomly with no apparent sense of direction. Despite this, virtually every molecule in a gas in a beaker, given sufficient time, will leave the beaker. I noted that this provides a perspective on an important question concerning the evolution of intelligence. Like molecules in a gas, evolutionary changes also move every which way with no apparent direction. Yet we nonetheless see a movement toward greater complexity and greater intelligence, indeed to evolution’s supreme achievement of evolving a neocortex capable of hierarchical thinking. So we are able to gain an insight
into how an apparently purposeless and directionless process can achieve an apparently purposeful result in one field (biological evolution) by looking at another field (thermodynamics).”
― Ray Kurzweil, How to Create a Mind: The Secret of Human Thought Revealed

“The evolution of animal behavior does constitute a learning process, but it is learning by the species, not by the individual, and the fruits of this learning process are encoded in DNA.”
― Ray Kurzweil, How to Create a Mind: The Secret of Human Thought Revealed

“Your ability to generate power is directly proportional to your ability to relax.”
― David Allen, Getting Things Done: The Art of Stress-Free Productivity

“It is important to note that the design of an entire brain region is simpler than the design of a single neuron. As discussed earlier, models often get simpler at a higher level—consider an analogy with a computer. We do need to understand the detailed
physics ofsemiconductors to model a transistor, and the equations underlying a single real transistor are complex. A digital circuit that multiples two numbers requires hundreds of them. Yet we can model this multiplication circuit very simply with one or
two formulas. An entire computer with billions of transistors can be modeled through its instruction set and register description, which can be described on a handful of written pages of text and formulas. The software programs for an operating system,
language compilers, and assemblers are reasonably complex, but modeling a particular program—for example, a speech recognition programbased on hierarchical hidden Markov modeling—may likewise be described in only a few pages of
equations. Nowhere in such a description would be found the details ofsemiconductor physics or even of computer architecture. A similar observation holds true for the brain. A particular neocortical pattern recognizer that detects a particular invariant
visualfeature (such as a face) or that performs a bandpass filtering (restricting input to a specific frequency range) on sound or that evaluates the temporal proximity of two events can be described with far fewer specific details than the actual physics and
chemicalrelations controlling the neurotransmitters, ion channels, and other synaptic and dendritic variables involved in the neural processes. Although all of this complexity needs to be carefully considered before advancing to the next higher conceptual level,
much of it can be simplified as the operating principles of the brain are revealed.”
― Ray Kurzweil, How to Create a Mind: The Secret of Human Thought Revealed