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26 May AI Domains and Approaches

Grouping, Classifying and Categorizing How do you solve big technical problems? Rather than selecting or inventing an approach and then attempting to apply it to a problem to see how well it works, let’s analyze the problem and see if we can find or invent a solution that matches the problem space, and see if […]

06 May Impulse Waves in Layers


Layered Model Just as the brain has areas with three to six distinct layers, a typical artificial neural systems (ANS) also has several layers. The example at right shows a network with three layers that illustrate a neural network‘s distributed architecture. The uniform circles connected by lines are symbolic of the state of an ANS at […]

05 May Learning from Errors


If at first you don’t succeed, try – try again. Humans are pretty good at learning from our mistakes. In fact, some suggest that whatever doesn’t kill you makes you stronger. Today I’d like to riff on that theme a bit, and talk about ways in which machines can implement learning from errors. Error Minimization […]

26 Apr Continuity of Learning

Language in Head

Production and Comprehension We know that comprehension and language production occur in different areas of the brain and occupy opposite ends of the continuum in the communicative model. The relative independence of the production and comprehension centers suggests one of three possibilities: Syntactic and lexical data are replicated in both the production and comprehension centers of […]

09 Apr Abstract Contexts and Fuzzy Reasoning

The Face of AI

We do not yet know how we remember things, nor do we know how we use remembered things in reasoning. The amazing feedback loops of afferent and efferent fibers between different layers of the cortex give us some amazing clues (Hawkins 2004). Today’s discussion of abstract contexts and fuzzy reasoning is intended as a bridge […]

08 Apr Symmetrical Logic and Lineage

Morpho Butterfly

Symmetry may not immediately appear as a principle of logic or reason, but it should. In mathematics we learn the commutative and associative properties of addition and multiplication. These represent a mirror-like symmetry. Symmetry, or invariance against change, is a fundamental principle of physics and an underlying assumption driving some logical decisions. Causality, for example, […]

05 Apr Knowing About Agents and Instruments

Let the Dominoes Fall

Cause and Effect Causal knowledge can be learned by experience, as described in our friend Yorrick’s early experiences with the source of good feelings (Section 4: Seeds of Knowledge). The process of learning from experience is empirical and very fuzzy, meaning it is difficult to describe or replicate the learning process artificially. Cause can also […]

03 Apr Causal Chains in Action

Pulling Together

Expectations are often influenced by our understanding of cause and effect. In physical interactions between our bodies and the external environment, and in social interactions between other complex people, we are capable of predicting an outcome long before it actually comes to pass. We are also capable of predicting an outcome immediately before it comes to pass, as […]

02 Apr Context and Expectations

Keyboard Music

Expectations are context based, top-down ideas of what comes next. These top-down ideas feed perceptual processing centers in the brain, helping us focus on what matters, ,and sometimes blinding us to other possibilities.  The two types of context we will consider today are sensory and non-sensory. Sensory context applies to anything in the physical world […]

01 Apr Generating and Qualifying Propositions

Brain Hemispheres

What are the limits of reasoning? Is it possible to reduce every cognitive activity (telling time, falling in love, inventing rockets…) to a set of premises and conclusions: propositions? LITTLE ANIMALS ARE FURRY is a very simple proposition. Can intelligence be defined by the complexity of the sequence of propositions we can balance in evaluating a situation? I […]