Both evolution and the brain are massively parallel discovery processes. But what is the difference between the two?
As a model to understand evolution, let's take the super organism known as bacteria and its adversarial viruses. This process involves horizontal gene transfer and endosymbiosis. Often overlooked by many models of evolution that confine themselves only to mutation.
In an abstract sense, the 3 mechanisms of evolution to drive innovation involves: chance (i.e. mutation), local information propagation (i.e. HGT), information reuse (i.e. Endosymbiosis). What are the equivalences for this in brains?
Brains also employ these same 3 mechanisms. Chance in that neurons, like immune cells, are generated with randomness, local information propagation in that neurons have connectivity with other neurons and information reuse in the sense of Hebbian learning.
Creativity processes are only useful if they are subject to a selective process. Evolution has natural selection that drives the fitness of species. Brains select for the fitness of behavior that realizes goals.
Another process that we should explore is the effect of cultural evolution. We can analyze this from the perspective of language use and evolution.
Language evolution also involves 3 mechanisms to drive innovation: chance (language ambiguity), local information propagation (word of mouth), information reuse (memes).
The human brain is unique in the animal kingdom in that it is able to leverage two kinds of discovery processes. Brains and language.
Humans are linguistic bodies and as a consequence is influenced tremendously by language. The study of human minds makes sense only by acknowledging innate cognition and cultural evolution.
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John Krakauer in a recent Learning Salon conversation focused on the huge gap between participatory learning and propositional learning. It occurred to me that propositional learning is a kind of hypnosis!
Coincidentally, today's currents events are a consequence of hypnosis. @ScottAdamsSays was the first to notice Trump's apparent use of hypnosis methods. fortune.com/2020/09/27/don…
In this episode, @JohnCLangford proposes Reinforcement Learning to be essential to intelligence. An ambiguous statement however since RL isn't precisely defined by him in the talk.
This is opposition to @ylecun icing on the cake analogy. @KordingLab chimed in with an excellent argument against the cake analogy. He insightfully proposes however the immense capability of evolution to absorb information about causality.
What is the difference between these verb pairs? Hearing-listening, touching-feeling, thinking-understanding, talking-explaining?
There's a difference between the verb we use that can only be understood by grounding in this world.
It tried to see what GPT3 understood about exploiting and exploring. Here is the association made by GPT3. Exploring->investigating,analyzing. Exploiting->caring,using,respecting,testing.
Here is @demishassabis who explains the importance of embodiment to AI. Deep Learning learns by interacting with its world as explained by many researchers in the sensorimotor field.
I'm constantly surprised that this sensorimotor or enactivist approach to understanding human cognition is a minority view in cognitive psychology and neuroscience communities.
In science, there is a constant struggle against the orthodoxy. Just as in chess and in go, higher exists higher-level abstractions that trump long-established practices in the past.
Why are the processes of biological cognition inseparable?
If we are to argue for anti-representation (see: Cisek's pragmatic representation or Brette's no-coding) then we should have an explanation of why cognition is non-separable.
Non-separable is a characteristic of a holistic system. This means that a process cannot be decomposed into subcomponent parts. Quantum mechanics @coecke can be framed as non-separability as a first principle.
It has been proposed that the brain deals with 4 kinds of semantics. Referential semantics, combinatorial semantics, emotional-affective semantics, and abstraction mechanisms. cell.com/trends/cogniti…
Bohm's Rheomode levate, vidate, dividate, reordinate which are abstract cognitive processes overlap but don't align with these semantics. Combinatorial and emotional-affective fits under levate. Referential and abstraction fits under reordinate.
There's a rough correspondence between Bohm's Rheomode and Peirce's triadic thinking: