Posts

In the first section of this blog post, I preview a very interesting paper that proposes an intriguing approach to hardware-based encryption that relies on biomemristors. In the second part, I showcase my own project, which I worked on with a teammate, where we built our own hardware-based encryption and decryption circuit based on the XOR Cipher method.

The main goal of this blog is to exonerate biological neurons and show that a single biological neuron is much more computationally powerful and sophisticated than you might think.

Simulating a single neuron is an easy task, thanks to the Hodgkin Huxley model, but simulating a network of neurons is less trivial and less documented over the internet. In this blog, We’re going to simulate a simple network of neurons. We’re going to create a model and a simulation of two neurons that interact at a synapse.

Neural networks are well-known for their ability to learn patterns from data, helping us make predictions and decisions in a variety of fields. But what if we could make these networks even smarter by teaching them to follow the rules that govern the world around us?

Imagine a world where each cell in our bodies could be uniquely colored, allowing us to track their movements and interactions with unprecedented detail. While this might sound like science fiction, a revolutionary technique known as Brainbow has brought us closer to this reality.