Ray Kurzweil - How to Create a Mind - The Secret of Human Thought Revealed

With 3 × 10 8(300 million) pattern recognizers at 72 bytes each, we get an overall memory requirement of about 2 × 10 10(20 billion) bytes. That is actually a quite modest number that routine computers today can exceed.

These estimates are intended only to provide rough estimates of the order of magnitude required. Given that digital circuits are inherently about 10 million times faster than the biological neocortical circuits, we do not need to match the human brain for parallelism—modest parallel processing (compared with the trillions-fold parallelism of the human brain) will be sufficient. We can see that the necessary computational requirements are coming within reach. The brain’s rewiring of itself—dendrites are continually creating new synapses—can also be emulated in software using links, a far more flexible system than the brain’s method of plasticity, which as we have seen is impressive but limited.

The redundancy used by the brain to achieve robust invariant results can certainly be replicated in software emulations. The mathematics of optimizing these types of self-organizing hierarchical learning systems is well understood. The organization of the brain is far from optimal. Of course it didn’t need to be—it only needed to be good enough to achieve the threshold of being able to create tools that would compensate for its own limitations.

Another restriction of the human neocortex is that there is no process that eliminates or even reviews contradictory ideas, which accounts for why human thinking is often massively inconsistent. We have a weak mechanism to address this called critical thinking, but this skill is not practiced nearly as often as it should be. In a software-based neocortex, we can build in a process that reveals inconsistencies for further review.

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 of semiconductors 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 program based 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 of semiconductor physics or even of computer architecture.

A similar observation holds true for the brain. A particular neocortical pattern recognizer that detects a particular invariant visual feature (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 chemical relations 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.

We have been examining the brain as an entity that is capable of certain levels of accomplishment. But that perspective essentially leaves our selves out of the picture. We appear to live in our brains. We have subjective lives. How does the objective view of the brain that we have discussed up until now relate to our own feelings, to our sense of being the person having the experiences?

British philosopher Colin McGinn (born in 1950) writes that discussing “consciousness can reduce even the most fastidious thinker to blabbering incoherence.” The reason for this is that people often have unexamined and inconsistent views on exactly what the term means.

Many observers consider consciousness to be a form of performance—for example, the capacity for self-reflection, that is, the ability to understand one’s own thoughts and to explain them. I would describe that as the ability to think about one’s own thinking. Presumably, we could come up with a way of evaluating this ability and then use this test to separate conscious things from unconscious things.

However, we quickly get into trouble in trying to implement this approach. Is a baby conscious? A dog? They’re not very good at describing their own thinking process. There are people who believe that babies and dogs are not conscious beings precisely because they cannot explain themselves. How about the computer known as Watson? It can be put into a mode where it actually does explain how it came up with a given answer. Because it contains a model of its own thinking, is Watson therefore conscious whereas the baby and the dog are not?

Before we proceed to parse this question further, it is important to reflect on the most significant distinction relating to it: What is it that we can ascertain from science, versus what remains truly a matter of philosophy? One view is that philosophy is a kind of halfway house for questions that have not yet yielded to the scientific method. According to this perspective, once science advances sufficiently to resolve a particular set of questions, philosophers can then move on to other concerns, until such time that science resolves them also. This view is endemic where the issue of consciousness is concerned, and specifically the question “What and who is conscious?”

Consider these statements by philosopher John Searle: “We know that brains cause consciousness with specific biological mechanisms…. The essential thing is to recognize that consciousness is a biological process like digestion, lactation, photosynthesis, or mitosis…. The brain is a machine, a biological machine to be sure, but a machine all the same. So the first step is to figure out how the brain does it and then build an artificial machine that has an equally effective mechanism for causing consciousness.” 1 People are often surprised to see these quotations because they assume that Searle is devoted to protecting the mystery of consciousness against reductionists like Ray Kurzweil.