@svetlyak40wt Ok, I sent you an invitation on github on the backend project, that contains under neuron/ what little I have implemented. @spacebat: could do the same if you let me know a github id.
Following: a short, yet long, discussion of the concept.
@svetlyak40wt@spacebat THREAD
The concept: living beings have a nervous system, and "real" intelligence. I think nature is complex, of a chaotic, fractal kind of complexity; still I think it's, well, natural: by this I mean that no natural phenomenon, including intelligence, ...
@svetlyak40wt@spacebat ...needs to be explained by sovrannatural causes. Of some phenomena we have a complete mathematical understanding (or so we think: eg the laws of motion); some other we can't "integrate", but we can approximate them to an extent with numerical models (think of weather forecasts).
@svetlyak40wt@spacebat But things can be mathematically defined and NEVER extrapolable: think of the Mandelbrot set.
Intelligence and learning are incredibly complex phenomena. But so is life, yet the Miller-Urey experiment demonstrated that natural forces can spontaneously...
@svetlyak40wt@spacebat ...produce the biochemical elements of life.
A human nervous system consists of a number of neurons in the order of 10^11. Each neuron can have up to several thousands of connections: the number of possible combinations is astronomical. The information isn't stored...
@svetlyak40wt@spacebat ...in neurons themselves, but in the structure of the network: a neuron isn't a "drawer" that contains memories, but a node of a network. That's why a stroke destroys our learned abilities, and simply growing up new neurons won't solve the problem: those abilities were learned...
@svetlyak40wt@spacebat ...with an evolutionary process.
The little I know about this process is (deeply semplifying) that synapses are selected by a somewhat darwinian process or random creation and decay, or survival, according to a feedback. So what if we could recreate in a simulation...
@svetlyak40wt@spacebat ...the very basic properties of a network of neurons, including input, output and a feedback system? Would such a system, in due time, show a trace of "real" learning?
So far the elements of the theory.
The implementation (what little there is of it) is in Common Lisp. ...
@svetlyak40wt@spacebat Neurons are excitable objects, with a baseline potential and a threshold - when they receive one - or more - exciting signal, such signals sum, adding to the neuron's potential for a short time span, after which the excited state subsides and the neuron sontaneously returns to...
@svetlyak40wt@spacebat ...its base state. Since the process must be asynchronous, a thread is used for each neuron. This probably is a severe limitation if the simulation runs on ordinary hardware, and I don't know enough about GPGPU to tell if this could be a good use case.
@svetlyak40wt@spacebat If a neuron's potential exceeds its threshold, the neuron "discharges", ie generates an exciting potential that travels through its outbound synapses to reach connected neurons. A neuron can have inbound synapses from many other neurons, ...
@svetlyak40wt@spacebat ...so the interactions are incredibly complex.
This part is implemented, tested, and works.
What I haven't implemented (and I don't know whether and when I will):
...
@svetlyak40wt@spacebat * a specialization of neurons into a "receptor" class, that receives its input potentials by sampling and translating external events (could be hooked to static data, like a file; could be connected to a peripheral like a microphone or a camera)
...
@svetlyak40wt@spacebat * another specialization into an "effector" class, that translates action potentials into data or, in a future, behavior of a peripheral (think of a simple robot)
* a feedback system on generated output
...
@svetlyak40wt@spacebat * a system of random decay and generation of synapses, reinforced and directed by the feedback system.
Given these elements, my little first Miller-Urey experiment on learning would be to give the simulation a simple static input (say a barcode?), ...
@svetlyak40wt@spacebat ...a "desired" output for the feedback system, then let it run and see what happens.
Should it prove to work, endless possibilities for experimentation and practic application would open.
@svetlyak40wt@spacebat As you can see from the code, I am very far away from realizing the experiment. Bear with me - in the meantime I had a daughter and I lost her, I went through a very unfair and traumatic dismissal, I discovered I am autistic... Plenty to deal with. Thanks for your kind interest.
I am a highly empathic autistic person. As such, I always felt that lack of empathy is the most dangerous and spiteful quality (or lack thereof) in a human being.
There should be more awareness of the presence of sociopaths, psychopaths and narcissists - disguided as humans - ...
... amidst normal people who try to live a normal life. Their lust for power is unsullied by moral obstacles: they only respect rules and laws to dodge consequences, but will hurt others in order to further their agenda if they don't expect a payback. When we look at...
... the senseless situation of mankind, we often embrace models close to Marxian thought, without realizing that such models are descriptive: they can explain fairly well the mechanics of injustice, but they don't really care about the causes. …
@svetlyak40wt@spacebat Sorry for the late answer - my private life is absorbing most of my bandwidth in this period (divorce):
as far as I can see, my concept shares something with the regulatory feedback ANN model, but the layout of the network itself is modified by the feedback.
@svetlyak40wt@spacebat Think of it as a directed cyclic graph, with an input layer, an output layer and an arbitrary number of intermediate nodes; plus, it can transmit information and modify its layout (the connections, not the nodes) according to a feedback mechanism, ...
@svetlyak40wt@spacebat ... working its way unsupervised to a stable configuration that produces an optimal feedback.