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…
We are prone to 'believed-in imagination' as a consequence of the increasing ambiguity of this world. Society's complexity continues to accelerate many people's understanding of reality is compensated for with erroneous and easier to grasp alternative realities.
To address @blamlab observation, that he himself says that he can't be the only one going mad, is that propositional language (i.e. declarative) is a kind of hypnosis. The kind of belief that is constructed out of a grounding on this world but imagined without proper rigor.
In other words, @blamlab may have been the only one in the conversation that may have not been under collective hypnosis!
When we examine GPT-3, we realize that for many it appears near human in its capability. This is because it is us and our imaginations that derives meaning from its auto-generated text. GPT-3 does not have the imagination to find meaning in text by grounding to this world.
Humans do understand language and interestingly enough, it is related to hypnosis. That is a believed-in imagination of this world.
Indeed curious that the article above concludes that the opposite of hypnosis is ... empathy.
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(1) All technologies are combinations. Individual technologies are combined from components. (2) Each component of technology is itself in miniature technology. (3) All technologies harness and exploit some natural effect or phenomenon.
His framework is general enough so that we can recognize things that we don't conventionally consider as technology. These include culture, human organizations, processes, language and biology.
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?
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.