Saturday, July 21, 2018

Mimic Neuronal Behaviour Using Generative Adversarial Networks

The core problem with building sophisticated artificial intelligence, is understanding, and modeling, all the intricate dynamics behind how neurons work. Neurons, and all their various activities, are extremely complex, and we are still learning new things today. Artificial neural networks have been very instrumental in the recent advancements in AI. The problem, is that they are still very crude representations of the actual dynamics that go on inside the brain. If we could effectively model how a neuron works, we could simulate a neuron on a computer, and let its natural ability to learn, unfold in the simulations.

So, what if we trained a GAN to mimic the dynamics of a neuron?

What if you fed it as much data as you could about the neuron, its activity, how it interacts and affects other neurons. And how other neurons interact and affect it. And tried to get the GAN to model that behaviour?

And then once it captures what a neuron is, and all its dynamics. Have it generate multiple neurons, and have those neurons interact with each other in a simulation.

If you can figure out the general rules behind how the neurons interact with each other. Once you know those rules, you don't have to understand the brain. You can just simulate the neurons, and let the intelligence naturally emerge from their interactions.

This is footage of a neuron taken using atomic force microscopy, allowing for imaging of nanoscale dynamics of neurons.

The key to making this work is the training data, and figuring out how to best capture and collate it..

Footage like this could serve as a source of training data for the GAN. This data, combined with the electrical activity that correlates with the data. Could potentially serve as a great dataset from which to allow a GAN to model neuronal behaviour.

Tuesday, January 23, 2018


Music is likely much more special than we realize. Though deep down, maybe we always knew that there was something special about it.

Music, may actually have some deep connection to the nature of the universe.

What initially led me down this train of thought, was when I first heard a bird song, slowed down to human hearing range, as shown in the TED talk 'The unexpected beauty of everyday sounds' by Meklit Hadero. A beautiful talk, by a beautiful woman.

What I find so fascinating about their songs, is that they actually sound like melodies humans would make.

It hints at the possibility that our aesthetic for music isn't unique to humans. That possibly, something much deeper and more fundamental is at play that causes us to like music. The fact that we even make music at all is an anomaly. As we don't get food from it, nor does it seem to help in the survival of our species. Yet we dedicate so much time, energy, and resources to the endeavor. Music is such a fundamental part of our culture, it's so powerful, we all know how powerful it can be. At times it can feel transcendent.

The great philosopher Friedrich Nietzsche once said - “Without music, life would be a mistake" I'm inclined to agree. When I listen to Vivaldi, it truly feels like I'm connecting to something beyond me, something beyond this world. Birds sing, so do dolphins, chimpanzees even show a sense of musical preference. Clearly music is something special. But why?

All of these species are known for their intelligence. So maybe music is somehow fundamentally connected to intelligence? Interestingly, one of the problems of building artificial general intelligence, is how would one develop an AI that would actively go out of its way to make music? It's a difficult problem, and it may be that we will only have true AGI until we can make AI that can and will make music, not because it has to, but because it wants to.

The current popular understanding of the brain and of AI, takes the perspective of looking at the systems, as systems primarily built for learning, but that doesn't really explain how and why we make music. But the ideas Nell and I are developing about the brain, could potentially explain this. As our ideas don't look at the brain as primarily a system that learns, but as a resonance engine that continuously molds itself and it's neural activity to resonate with it's environment.
Our theory
proposes that the intelligence of the brain, and of life, is an emergent property of entropy maximization, otherwise known as the 2nd law of thermodynamics. In order for a system to maximize entropy within its environment, it must resonate with its environment. And by resonating with its environment, it forms what effectively is, a model of its environment.

It also turns out, that Andrés Gómez Emilsson and the Qualia Research Institute, are actually developing a theory to explain consciousness, as something that emerges from brain harmonics. They call this theory, The Symmetry Theory Of Valence.

Andrés gives a talk that goes into detail about the theory, and even makes clear, empirically testable predictions, that could falsify or prove the theory true. I highly recommend watching it.

In his talk he references research done by Selen Atasoy on the study of brain harmonics, and how certain brain harmonics determine certain states of consciousness. This research is not only very interesting, but also backs up the idea of looking at the brain as a resonance engine, rather than as simply a system that learns.

With this in mind, I think it becomes a bit easier to see why music seems to have such a powerful affect on humans, birds, dolphins, or really anything with a neocortex. Perhaps it's just embedded in the way the brain works. If the brain is a resonance engine, then perhaps the brain likes music, simply because music is very easy to resonate to. As nice sounds, have a clear, and beautiful mathematical structure. And dissonant sounds, sounds that we tend not to like, don't really have a structure. They literally cause dissonance in whatever medium they travel through.

All I know, is that I love music so very much. I lose myself in it. And perhaps there is a deeply profound reason why it affects me, why it affects all of us, in such a way.


(Note, birds actually predate mammals and have even evolved down a completely different path, and yet have still developed their own version of a neocortex, that looks a bit different, but essentially works the same way. Which is also amazing in it of itself. It suggests that the development of the neocortex, which allows mammals to learn new behaviors, isn't due to some chance occurrence. But rather, that evolution, regardless of circumstance, will naturally lend itself to the development of neocortex like structures.)

Monday, October 9, 2017

A New Theory Behind How And Why Neurons Work

(These ideas are presented in our paper 'Neuronal Entropy Maximisation - A New Model For Neural Networks') Recently, Nell Watson and I through our research have made many novel insights. Forming powerful connections between entropy maximisation and a variety of other fields such as neuroscience, cognitive science, machine learning, and so much more.








life may actually act as a catalyst for entropy production.



Here are links if you wish to look more into this.

Dissipative adaptation in driven self-assembly:







Here are links if you wish to look more into this:












Then we took another look at Hebbian theory.



The thought then came to mind.

What if neurons, are actually trying to control other neurons?



We felt, that this was it, right here.














It turns out, that bacteria can actually communicate electrically.


This, is a perfect example of collective agency.









They also said this.
"Understanding and being able to compute entropies for cellular automata
subjects on a deeper level."
















As shown in this article:




You can view a version of this experiment here:










Efficient Quantum Walk On A Quantum Processor:





Here's a quote that I love from the director of the C4 group at Sante Fe.
