
It’s not known to many that the first person to recognize the universality of NAND and NOR gates to logic was first articulated by C.S.Peirce. However, C.S. Peirce has always contended that logic was a subset of what he called semiotics (see: https://en.wikipedia.org/wiki/Semiotic_theory_of_Charles_Sanders_Peirce )
In recent days, DeepMind has unveiled a new neural network article coined Perceiver-IO (see: https://deepmind.com/research/open-source/perceiver-IO ) that is a general architecture for any kind of input and output. In other words, it is an artificial manifestation of a sign processing or semiotic engine.
What I would like to explore here is to provide a semiotic interpretation…

In Frank Herbert’s Dune, the affairs of the entire universe revolve around a psychedelic drug known as the Spice Melangethat enables beings the ability to fold spacetime and see into the future.
The spice is essential because without it travel between planets in the universe would be practically impossible. The universe is interconnected in commerce through psychedelics.
The spice however also allows its consumers to see into the future. Hence to make predictions of what might come. Does not one find it odd that success in our modern financial industry relates to our ability to see into the future?
An…

It’s incorrect to treat either emotions or consciousness like an axiom in the formulation of general intelligence.
I agree that emotions are a parameter in cognition. But this parameter is also regulated by cognition. How we perceive the world is regulated by our cognition and emotions are an emergent response to our perception. An axiom is a boundary condition.
Emotions are affected by our perception and thus it’s not a boundary condition but rather is a constraint that morphs with our subsequent interactions with our world and our minds.
Others treat consciousness as an axiom in the framing of the…

All cognition involves the interpretation of language. But what is the difference between the brain’s interpretation of its senses and the interpretation of language?
For starters, the interpretation of language should appear to be simpler because another agent who vocalized or wrote the expressions did so with an intention of conveying meaning. Language is conditioned so the interpreter can understand it.
However, our environment doesn’t condition its expression for an agent to understand it. Here is the interesting observation, it is the agent itself that conditions how it interprets its senses.
A living thing interprets its environment by virtue of…

The consequence of humans trading in nouns is that they spend an inordinate amount of effort attempting to understand the design of natural things without understanding why that thing emerged.
We focus too much on the forest but always overlook the trees. Our reductionist habits are biased towards simplicity. We achieve simplicity by removing context from the equation.
This is despite our natural human ability to involve context to unearth meaning.
Physics is extremely successful at employing reductionist methods to understand our world. Physics has invented compact universal laws that describe the inexorable rules of reality.
But we must understand…

When we first learned how to drive on the highway, it was a conscious process. Now it’s unconscious and we can daydream for miles without even being conscious of the road. Habit becomes unconscious that’s how the brain works.
That means that everybody’s conscious habits are going to be different. So the nature of one’s consciousness differs from person to person because we have developed different thinking habits.
Some people always have vocalizations in their head, others do not. Some people can vividly visualize scenes, other’s can’t. We build up all kinds of unconscious habits that shape our thinking.
Conscious…

Three years ago I proposed a deep learning capability maturity model (see: A New Capability Maturity Model for Deep Learning ). Today I will revisit this maturity model (i.e. a roadmap in more pedestrian terms) to see it in light of my more developed understanding of general intelligence.
Let’s begin with the premise that “reasoning and learning are two sides of the same coin and should be treated equivalently.” This notion can be illustrated in this diagram:

200,000 years or 10,000 human generations is what it took to get where we are today. It took 9,700 generations of humans to realize the value of the scientific method. Stupidity is doing the same thing over and over again without making progress. So what were 9,700 generations of humans doing when they were not doing science?
These generations spent all their time constructing models of reality that were influenced more by authority than by a systematic method of model construction that challenged authority. …

It is patently absurd that so many researchers in cognitive science believe in a magical local rule (i.e. Hebbian learning, gradient descent, free energy, neural circuitry, etc) that leads to complex intelligence. I guess humans just never get tired of their reductionist methods.
But yet we have made tremendous strides using just local rules like gradient descent and massive computation to emulate intuition found in human minds.
Deep learning methods appear like a bottom-up process, but it’s actually a top-down process where an observational error is propagated down the layers perturbing weights along the way. …

Let’s begin today with the realization that Ptolemy’s model of the movement of the planets was extremely accurate. Ptolemy’s model was accurate enough to be very useful for navigators of their time. But it worked well because it was finely tuned to fit with observed experimental data.
But was wrong with Ptolemy’s model is that it did not correctly capture cause and effect. The earth and the planets revolve around the sun due to gravity and not everything revolves around the earth. This was the Copernicus model which he paid gravely for proposing.
200 years later Newton invented calculus and…

Author of Artificial Intuition and the Deep Learning Playbook — http://linkedin.com/in/ceperez https://twitter.com/IntuitMachine