On Intelligence by Jeff Hawkins

Created: 2021-01-04T19:31:41-06:00

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• Previous attempts at modeling intelligence are not well rooted in biology.
• Artificial neural networks have only the loosest relation to neural networks.
• Alan Turing -- demonstrating all computers are functionally similar regardless of how they are built.
• Universal Turing Machine: given the right operators, time, and enough memory any machine can compute anything.
• Neurons could be used to create AND, OR, NOT gates.
• Behaviorism: altering behavior by changing inputs and outputs.
• Multi-step deductive reasoning is seen as a pinnacle of human intelligence.
• Deep Blue winning chess by calculating more potential branches of play; having no intuition.
• Chinese Room Experiment
• Founding of "Grid Systems" who invented one of the first laptop computers.
• Traditional AI was about symbol manipulation and had nothing to do with how the brain works.
• Artificial neural networks tangenially relate to how brains work but they are incomplete.
• Physical brains deal with time spiking (patterns changing through time)
• Physical brains also have feedback connections; the organs controlled by the brain return information back, in greater number than data leaves.
• Auto-associative memory: cells that learn patterns impressed upon them and are able to take partial matches and suggest the original symbol.
• Theories that are intuitive and simple but ultimately wrong.
• Input-output fallacy: a particular misunderstanding of the brain relating from observing its inputs and outputs but not its function.
• Cognitive wheel: when an engineered solution works nothing like nature but yet still works.
• The brain contains heirarchies; areas which adapt sensory data or translate concepts in to physical motion.
• Synapses can boost or inhibit the firing of other synapses.
• Neocortex is made up of layers.
• Topmost layer consists mostly of axons.
• Layers other than the top, eight out of ten cells are pyramid cells.
• Pyramid cells connect to their immediate neighbors but also have axons to neighboring clusters.
• Pyramid cells have thousands of connections to other cells.
• Vernon Mountcastle -- "An Organizing Principle for Cerebral Function", makes the case that every region in the neocortex is the same. Clusters that decode one sense look the same as other senses.
• Clusters in the neocortex are partly specialized to their role by means of different connection counts/thickness, minor suitability tweaks.
• The best ideas in science are always simple, elegant, and unexpected.
• Much of extant neuroscience is about imaging which areas are activated corresponding to certain stimuli.
• Neuroplasticity: the brain's ability to repurpose itself.
• Spatial patterns: a pattern which appears across a spatial field; when seeing a plane, parts of the plane are mapped to pixels in a grid, the pixels on the grid are the spatial pattern.
• Temporal pattern: a series of spatial patterns that happen or change across time.
• Paul Bach-y-rita -- developing a means to project visual data to the nerves of the tongue.
• 100 step rule: an idea that brains take only one hundred computation steps to solve a given problem.
• Brains "compute" using very slow mechanisms because they do not compute at all; they are recalling previously solved patterns.
• Memory recall follows associative paths.
• Neurons are slow; they take ~5ms to complete a full computation cycle.
• Invariant representation: storing knowledge in a way that is flexible; it can generalize to similar problems.
• Many behaviors become automatic and require active effort and focus to change them.
• Autoassociative memory is good at recognizing and completing patterns it has previously seen but does not recognize them if they are transformed in some significant way.
• Continuously predicting some world state and being surprised when the prediction is violated; attention drawn to parts of a problem which do not fit in to the current predicted state.
• Prediction may be the primary role of the neocortex.
• Filling in: when errors, incomplete or nonsense input is replaced with something that statistically seems like it should be there.
• Intelligence defined as remembering and predicting patterns.
• Human neocortical "units" have six layers.
• Memory prediction framework of intelligence: intelligence as an emergent property of a system designed to predict future outcomes.
• V1<->V2<->V3 layers and such
• Receptive field: where a visual neuron will only respond to a subset of the vision space; it is constrained to a particular bounding box.
• Visual cells may also be conditioned to only respond to particular patterns; ex. lines at 30 degree rotations.
• Higher level visual cells learn features of composites from lower cells; some trigger whenever a face-like object are being seen.
• High level cells are activate whenever an object of a given type are visible; ex the cell for "traffic cone" is active if a traffic cone exists anywhere in view.
• Stacking receptive fields: lower level sees a small region (say 3x3,) while a higher level sees a 3x3 of its subordinate 3x3s and so forth.
• If an unexpected event happens the signal is thrown upward until somebody does know what to do about it.
• Column: a vertical unit of cells that work together for a single neural computation.
• Inhibitory cells exist so that columns can be disabled if they do not seem necessary. Certain regions only activate a grouping of columns for given stimuli.
• >90% of synapses are from cells outside a given column.
• Constant name pattern: a pattern which is relatively constant to represent a particular concept.
• Formation of name patterns: layer 2 cells fire when they predict an output based on a given input, layer 3b cells fire when a lower pattern is not found, layer 3a cells fire to inhibit layer 3b when the pattern is present.
• Identifying objects as patterns being sent up from sensors which try to match different memories, sending signals down until a new context is found where the sensors no longer mispredict what they are seeing.
• Some channels from higher levels may exist which go all the way down to lower or base layers.
• Distant dendrites as "coincidence detectors;" when multiple of them fire at once they cause a different layer cell to spike.
• Hebbian learning: neurons which fire at the same become correlated; "neurons which fire together wire together."
• Memories not moving; they appear to move but are actually re-learned elsewhere.
• Basal ganglia: motor control
• Cerebellum: precise timing
• Hippocampus: short term memory
• Hippocampus is sometimes theorized as the "top" of the neocortex; where memories are developed at the topmost layers and pushed downwards.
• Hippocampus has several specialized regions unlike the neocortex.
• Memories which cannot be recognized by anything at a lower level end up pooled in the Hippocampus; they stay there until they are either purged or occur enough times the memory is strong enough to work its way downward.
• Attention as a process which changes whether an autonomous process or a neocortical process handles and responds to an event.
• Neocortex has two hard rules: it is not fast, and its rules are simple (but repeated at scale.)
• Experts recognize patterns which sit on top of patterns.