A Thousand Brains: A New Theory of Intelligence

by Jeff Hawkins

Under one square millimeter of neocortex (about 2.5 cubic millimeters), there are roughly one hundred thousand neurons, five hundred million connections between neurons (called synapses), and several kilometers of axons and dendrites.

Darwin proposed that the diversity of life is due to one basic algorithm. Mountcastle proposed that the diversity of intelligence is also due to one basic algorithm.

The brain creates a predictive model. This just means that the brain continuously predicts what its inputs will be. Prediction isn’t something that the brain does every now and then; it is an intrinsic property that never stops, and it serves an essential role in learning. When the brain’s predictions are verified, that means the brain’s model of the world is accurate. A mis-prediction causes you to attend to the error and update the model.

In 2005, scientists in the lab of May-Britt Moser and Edvard Moser used a similar experimental setup, again with rats. In their experiments, they recorded signals from neurons in the entorhinal cortex, adjacent to the hippocampus. They discovered what are now called grid cells, which fire at multiple locations in an environment. The locations where a grid cell becomes active form a grid pattern. If the rat moves in a straight line, the same grid cell becomes active again and again, at equally spaced intervals.

Neurons, however, use what is called associative memory. The details are not important here, but it allows neurons to search though all the map squares at once. Neurons take the same amount of time to search through a thousand maps as to search through one.

As I have pointed out multiple times, intelligence is the ability to learn a model of the world. Like a map, the model can tell you how to achieve something, but on its own it has no goals or drives. We, the designers of intelligent machines, have to go out of our way to design in motivations. Why would we design a machine that accepts our first request but ignores all others after that? This is as likely as designing a self-driving car that, once you tell it where you want to go, ignores any further requests to stop or go someplace else.

We have similar concerns with humans. This is why no single person or entity can control the entire internet and why we require multiple people to launch a nuclear missile. Intelligent machines will not develop misaligned goals unless we go to great lengths to endow them with that ability.

The history book is an instance of a meme. First introduced by biologist Richard Dawkins, a meme is something that replicates and evolves, much like a gene, but through culture.

We, as individuals, exist to serve the needs of genes. Genes that lead us to have as many children as possible will be more successful, even if that sometimes leads to death and misery.

My best guess is again based on the idea proposed by Richard Dawkins in his book The Selfish Gene. Dawkins argues that evolution is not about the survival of species, but about the survival of individual genes.