The IF statement is the root creator of software programming. It has the ability to compare two values against each other and branch out to blocks of instructions. So it is perceiving (reading), decision making and routing - all that which differentiate life from inanimate objects. The AI agents perform the exact same loop, by delegating the first two steps to a model.

Going further backwards, the transistor (or a PNP junction) is the hardware level enabler of the IF statement. The action (switching) driven by the current which in turn controls other switches, is the first manifestation of "observe and act" by inanimate things at the speed of electricity.

Mechanical equivalents existed ofcourse - speed of a governer which controls the flow of fuel which in turn controls the speed of the governer.

I learnt a lot today from the interactive demo. You have the best clarity and right skill to educate

> A perceptron *is* the smallest brain you can build.

> In 1958, a researcher named Frank Rosenblatt built a machine *he called* the perceptron.

> It was *inspired* by a single brain cell, a neuron.

Nice and minimalistic

I played with similar approach in JavaScript and built a NanoNeuron https://github.com/trekhleb/nano-neuron (it is more verbose than Python though)

If you want to learn the fundamentals of ML I recommend a book, such as Deep Learning: Foundations and Concepts by Chris Bishop. If you insist on staying online, one option is https://course.fast.ai/

If you don't know ML I don't think you're going to learn much through ad hoc demos.

I can build a smaller brain.

f(x) = 0.

Okay, it’s conscious. But can it run doom? I rest my case.