An algorithm for simulating the human brain already exists, but no computer can execute it

An international group of researchers from Japan, Germany, Norway and Sweden has fulfilled one of the cherished dreams of an enlightened humanity. They presented a white paper that details an algorithm for modeling how the connections between neurons and synapses in the human brain work. In a simplified form, this is the key to replicating how the brain works on a computer.

A neuron is the basic unit of the nervous system, a cell with a mechanism for transmitting an information signal. A synapse is a node of neurons, a place of their connection for the exchange of information. The combination of neurons and synapses forms the structure that gives rise to the functionality of this part of the brain: memory, data processing, decision making, and more. Modeling all such possible connections and analyzing the result is the ultimate goal of the new algorithm.

One problem is that this requires prohibitive computing power. It is believed that there are 1 billion compounds in the human brain. Even if you describe each neuron with just one bit, simulating an entire brain would require a memory capacity 100 times that of today's supercomputers. In practice, all this goodness must also be combined together for joint work, and this is additional power.

As a result, the implementation of the developed algorithm is not yet possible, but the merit of the research team is that their brain model is made "extremely scalable" and is open source. And as computing power grows, it will become easier to simulate the workings of the brain until one day we reach 100%. And then humanity will enter a new phase of its development.