memetic-engine-wizards
Table of Contents
These notes are part of the very large pile of notes at Neuronal Ensemble Memetics.
In the meantime I have learned 'observer theory' is a thing. I have also learned about Gerald Edelman Neuronal Darwnism, which I have to check out of course.
This is in a way a philosophical epxloration 'user interfaces' and 'interfaces'. Dan Dennett was pointing out this 'hiding of details', and this is an aspect where progress can be made.
Life Inside A Memetic Engine
It is pretty much obvious now that the brain is an information-processing device [McCulloch] that creates user illusions [Dennett].
—
Summary:
Vast amounts of tiny programmer memes that figure out how the computer they run on works, not because they set out to understand how it works, but because of the many that didn't mean the right thing, the ones that mean something useful are selected in a process of natural selection.
In a substrate where your meaning is your connectivity, or generally your effects on a computer system.
The best memes are the ones creating magic interfaces for confident wizards. Creating user-level entities that use the computer with swag.
This is the (very, very) raw audio diary:
—
If the brain has brain software running, we can go and understand the nature of this software, too.
It is clear that it is a valid viewpoint to say 'the mind is a programmer, programming the computer it runs on'. (I.e. it is executing a programming task).
Of course, whatever is programming cannot be competent by itself. It must bootstrap from simple elements.
I had this activity flow of the cell assemblies (see notes) in mind and wondered what software can run on such a computational system.
I came up with a thought experiment, called Banana maker matrix algorithm.
Suppose we already have a nice memetic engine, capable of trying out vast spaces of possible memes (and fast) and selecting them after some useful criteria.
Let's pretend for a moment this machine implementing a 'matrix' (virtual world) algorithm, a big imaginary planet with a cyber-highway along the equator that makes you pass ten thousand cities, twenty times per second.
Suppose further that there are simple agents in the system, let's pretend they are super-competent action heroes, who need to act on a clock. These people are very, very fast. And very competent and confident.
Let's assume they exist, because we assume natural selection can select for competence [Darwin, Dawkins] - the ones that were not competent and fast were discarded.
How to engineer this is then a question for later.
Let's suppose for a moment that the memetic engine can select action-hero short movies. In effect you, as an action hero, have a short amount of time, to please the memetic engine in some way. Of course, you can hack its mechanisms, too, if you are competent enough.
You get created (some activity flow makes you spawn) in a place in meaning landscape that you already have supplanted with useful tools and so forth. Part of what a good meme does is plan for the next iteration of its existence.
The other thing you do is quickly go to some city, where many generally useful memes provide information for more derived memes.
The most successful memes will be part of vast societies of contributing, more generally useful, memes. One might imagine some other meme leaves a sticky note on a wall, they don't know why they do it and you don't know why they do it.
But information can flow, and more useful information flows are selected. Say the meme-machine selects action-hero timelines, including the cities they move through or something.
Here is the next thing: This matrix has certain competencies, like spawning new cities and roads or manifesting a banana.
Everything that the computer can do, the matrix can do, and the memetic engine might also try it out.
Now and then the matrix will simply manifest a banana in a place, just to try out what happens. An 'everything possible' magic system mechanism.
Now you are a competent, optimistic action hero. And you trust in the magic of the matrix. 'I hold out my hand and there will be a banana'.
Again, the 2x2 matrix of optimism and competence, the optimism-drive, produces the following:
All the memes that are optimistic and pretend they know how to use the magic of the matrix, have a chance to survive. All the memes that are pessimistic have no chance and are discarded.
Optimism is not the only thing you need, you also need competence. In this case, it is the competence of the rest of the computer to provide you with what you needed at that moment to be a successful action-hero wizard (with swag).
banana! I don't know. +---------+--------+ | S | X | competent | | | (the information flow is capable of creating a banana, if you ask) +---------+--------+ | X | X | incompetent | | | +---------+--------+ S - memetic success X - discarded
Commanding the magic of the computer without knowing how the computer works.
This holy overlap of competence and optimism is how there is a magic piece in this whole thing now. From the thousands of memes that said 'There is a banana', there is one meme action hero that confidently puts out her hand and says 'there is a banana', and the system tried out randomly what would happen if there is a banana in that place - this short story movie timeline then was especially useful to the system and selected.
Because for some reason a banana is what this hero needed to be successful in its matrix short-term movie.
Nobody knows why: The memetic engine sees an information flow that worked well, and the hero sees the matrix that made a banana for her, similarly, the banana memes are just information flow pieces that had a chance to be active, and they do what memes do. Trying to be active more.
The interface between the user and the lower software world is something like 'competent query' and 'competent result', where both are selected memetically afterwards, so that the matrix becomes more and more magical to use (obeys every whim so to say, and is very useful, retrieves from midterm memory for instance), and the user-level entities become more and more competent, artistically elegant, on-point, demanding, confabulating, and confident.
If you would stop to understand the matrix you run on, some other meme would simply be faster.
I conjecture this would create competence hierarchies, where the higher agents in the system delegate the lower agents.
To put it the other way around; The more generally useful memes have a great memetic strategy - be so useful that all the higher-level agents can't help but incorporate you into their short-movies. So that you are 'on', memetically selected, in many situations.
When a high-level meme delegates lower-level memes to provide it with information, we can imagine little hacker wizard memes, in the substrate of the matrix so to say, that either figure out how the computer works and provide you with competence or not figure out how the computer works. Then they are discarded by memetic selection. Of course, they don't know how the computer works, they either represent a wiring that has meaning, or not.
The memes don't know what they mean when they start, it is only afterward that the meaning that made sense is leftover. This is the strange inversion of reasoning of Darwin's idea. Taken seriously for software-level mechanisms of computers that run meme-engines.
On the highest levels of this hierarchy, you have memes that are so competent, that they command everything that the whole computer can do with precision and artistic swag.
This then looks like a mechanism for a memetic machine to perfuse its computer with competence, to build information processing hierarchies that will use the computer, completely and competently.
Of course, the matrix machine is only a thought experiment, the matrix algorithm that runs on human brains is the one we know ourselves, usually called 'the mind'.
'The mind' is a class of software that implements magic interfaces to user-entities. (More on that in the notes).
The brain has something to do with navigating the world as an animal. Not because in principle all meme machines are about that, but because this specific meme-machine evolved biologically. (Whatever shapes the memetic landscape, coming from the genes, are biased to be about navigating the world and being an animal).
—
From thinking about it in this terms, I'm almost certain that the problem of phenomenological consciousness is the problem of what are virtual realities, and what are realities. I think it's the same theory that says what it is. (Greg Egan Permutation City and David Deutsch inspire me).
—
This puts half of the problem onto the machine hardware. It's how sick your sense organs are that allow you to create a world inside the mind. How well the thinking goo is tuned to lock into nice ideas while still having the dynamism to consider many possible things and so forth.
You don't get away from the fact that a neurophilosophy must talk about 'how the brain relates to the world'.
—
Those memes are allowed to get arbitrarily tiny, down to single-unit (whatever that might be) stupid computations. It's kind of sweet (technically sweet) to have a mechanism where arbitrarily abstract entities are allowed to coexist and refer to each other.
—
With this space of thinking you can muse about civilizations of memes, that build vast stores of knowledge. And archeologist memes going through the libraries of eons of accumulated knowledge.
Harmonious memes, cooperating memes, that never truly meet across times and space and yet, together contribute to the budding ideas, that only artistic memes and old wise-wizard memes can glean from the flow of time and history.
Social attractors of a kind that are bigger than a single meme on its own.
—
Update Thu Sep 12 07:57:24 PM CEST 2024:
I just listened to this again. These little poster stickers I was imagining could be implemented by the ensembles the way G. Buzsáki is describing them in The Brain from The Inside Out. If you have ensembles that are active for ~ 1 second, then you can implement a bit of evolving computation perhaps. Perhaps the same thing implements what you call 'short term memory' in cognitive psychology.
Each piece of computation could leave 1 second beacon of information blobs behind, it's intermediate outcomes, for its friends that come later in time in the course of the computation. Kindof straightforward 'working memory register' implementation from one perspective.
The analogy of action heroes flowing through cities might be more than strictly conceptual. If ensemble sequence trajectories (G. Buzsáki) have the chance to overlap, information can flow.
In other words, the precence of A
can steer the trajectory of B
. I would hypothesize this
must be possible in order to program with sequence trajectories of ensembles.
- A and B don't need to coincide, the computation can evolve over time given the itermediate outcome ensemble livetime.
B
is akin to an action hero flowing through a city, looking at the graphity on a wall (a
) of some previously acitve action heroA
.- longer time evolutions are possible via synapsembles, (https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3005627/). These are biochemical changes of neurons that modify their excitability etc. (also called fast weights, dynamically changing constellations of synaptic weights).
- trajectory branch could be implemented by 'microcircuits'.
- Or: The activation of
a
changes the attractor landscape so thatB(a)
is more likely thanB(not a)
. - Essentially, this just says that the present activation state influences what is active next; That's rather trivial.
- (The devil is in the detail)
Multiverse Meme Machine
What about the reality where Hitler cured cancer? The answer is don't think about it.
Rick Sanchez from 'Rick And Morty'
As a variation of this thought experiment, let's say the brain is creating a virtual multiverse. In our real multiverse, we don't need to worry about all the histories that are a chain of magical things happening.
Like the history where all objects turn into bananas when you point at them and say 'banana!'. We don't need to worry, because, for every universe like that, there are many more where it isn't.
Not so in the brain's virtual multiverse. Because some histories survive better than others. If there are magical universes that work, the memetic engine will roll with them.
- In the physical multiverse, everything possible exists, and 'non magical' trajectories (previouslay called 'histories') have higher frequency. The chance that the user finds herself in a non-magical universe is astronomically high.
- In a virtual matrix multiverse, magic trajectories can be selected, implementing a magic system. The chance that the user finds herself in a magical universe depends on the selection (collapse) implementation rules of the computer she runs on.
- (the devil is in the details)
- I think these might mirror 2 'collapse strategies' in non-deterministic programming. (more on that in another place).
- One where you find broad statistical regularities, and one where you find outlier ideas. Perhaps a bit of a System 1, System 2 thing, too.
I Imagine the counterpart of Neo in the matrix, he is moving around in the matrix and stopping bullets with his hands. Perhaps at the start, in most virtual worlds something incompetent happenend. Either he didn't think that he could stop bullets in the first place, or the matrix didn't make an information flow that meant bullets stopped.
The histories where Neo is stopping bullets, using what he percieves to be the magic of his reality, could at first be very few. Like the real histories in our mutliverse, where everything happens as if some magic system is actually being implemented.
They are like a tip of an iceberg.
In the second step, the histories where Neo and his magic are stable, are the ones we see around.
If information flows are stable because they implement software with a magical interface to users in a matrix, so be it.
'Try Out Everything' / Memetic-Engine Mechanisms
Intrinsic Firing Rate
(defn intrinsic-firing-rate "Applied after the threshold model. Says that neurons are allowed to fire at each time step with chance `intrinsic-firing-rate`. " [{:as state :keys [n-neurons intrinsic-firing-rate]}] )
Give your neurons an intrinsic firing rate!
This is a substrate-level mechanism to allow the network to try out everything a little bit.
Figure 1: Blerps from https://github.com/benjamin-asdf/hyper-substrates
Skip Rate
;; ================ ;; Skipping Rate ;; ================ ;; ;; Neuron 'failure rate' to fire. ;; ;; This is biologically plausible. At first glance, this looks like an imperfection, ;; but I am reasoning that this would modify the dynamism of the substrate. ;; ;; Higher neuron failure rate is similar to attenuation, it makes the ensembles spread more ;; and be less stuck. But high attenuation makes them move around, whereas the skip rate makes them spread more ;; if applied before the threshold model, and simply smaller if applied after the threshold model. ;; ;; Intuitively, this means you might find other attractor states if you have some neurons that usually strongly ;; contribute to one interpretation, now you have the chance to find a new interpretation. ;; ;; This has been described under the topic of 'assembly shift' [insert paper] ;; ;; This could be applied before or after the threshold model, with distinct results. ;; ;; Skip rate is counterintuitive but useful! And might (or not) be implemented 'explicitly' biochemically in brain. (defn neuron-skip-inhibition "Give every neuron at each timestep a chance to =skip=. This is an inhibition model modifier, applied `after` the threshold model. " [{:as state :keys [skip-rate n-neurons]}])
Yes, this is useful. And these 2 together give the ensembles the chance to move around and so forth. (Also called assembly shift). Finding new connections between sensors and motors that nobody ever dreamed of!
We can imagine a neuron that fires together with another ensemble, through plasticity, it will be associated more with the new ensemble. If it now also skips when its old ensemble fires, this neuron will shift, and migrate to the other ensemble.
Lit:
Non deterministic computation and computing in superposition
- Not using quantum computing, but pretending to be a little bit quantum, in the classical domain.
- Nondeterministic Turing machine
- Pentti Kanerva - Computing in Superposition in the Classical Domain
- In computing in superposition, you have datastructures that are both the tree and the forest, both the molecule and water
- hyperdimensional computing and some relationships to neuronal ensembles
- Here is a simple computing in superposition example
- 'Everything possible a little bit' needs to be meaningful in the software system for this mechanism to work, this can be done with hyperdimensional computing techniques.
- The hyperon MeTTA interpreter is a non-deterministic metagraph rewriter. Looks interesting.
Random Perspective?
Perspective
mechanisms is a hypothetical class of mechanisms that simply make some random inputs to the neurons.
Thereby modifying the attractor landscape dynamically.
If we also take some neurons and designate them as perspective effectors (p-effectors), then you can see how this the system can learn to dynamically modify its landscape.
Consider the case where there is a single large concept in the user's mind, like pizza. If you know how to press the p-effector buttons, you can play around with random perspective lines, until a landscape is reached that splits the concepts of pizza.
That is, you stretch and form the meaning of landscape so that you highlight some dimensions. And this new dynamic meaning landscape is for instance well suited for highlighting the space of pizza toppings. Vegan cheese, tomatoes, paprika, mushrooms. Where before the was the concept of pizza, there is now a nuanced view of the kinds of possible pizza.
A similar mechanism is labeled 'attention' in contemporary machine learning.
If 'doing some random things' to your p-lines is a possible thing to do, then you can evolve memes that are good at using this move for you.
The cognitive user can then create certain 'thinking' situations, that the rest of the system is allowed to fulfill, not only using the neurons but also such higher-order orchestration mechanisms.
Note that the cognitive user would simply create the situation 'zoom into the concept of pizza until I see its constituents'. It is the nature of having 'confabulation and subsequent best guesses until a stable interpretation of the situation is reached that makes the system stop thinking' as the mode of operation, that the goal state is in some ways pre-determined, but vaguely so. The shape of the situation is set, and the thinking machine goes and pattern completes the details, using whatever buttons are available.
I think we see the failure modes such as a layer of mechanism in things like 'tip of the tongue'.
Note that the intrinsic firing rate can be seen as the simplest perspective mechanism: that is everything possible is possible with non-zero chance evenly.
Also:
A toy idea for a meme-pruning algorithm / A Candidate Dream Mechanism
This is important for me:
- Randomness at the bottom.
- A framework where random skip rate and intrinsic firing rate make sense.
- The idea of a virtual reality as brain-operating system.
- High dimensional computing, programing in superposition, non deterministic computation and things like Sparse Distributed Memory are usful computational primitives. Latest stuff on that.
- The joyful meme-hero wizards as intuition pump. They help.