𝗛𝗼𝘄 𝗕𝗶𝗼𝗹𝗼𝗴𝘆 𝗕𝗲𝗰𝗮𝗺𝗲 𝘁𝗵𝗲 𝗙𝗼𝘂𝗻𝗱𝗮𝘁𝗶𝗼𝗻 𝗼𝗳 𝗔𝗜

𝗛𝗼𝘄 𝗕𝗶𝗼𝗹𝗼𝗴𝘆 𝗕𝗲𝗰𝗮𝗺𝗲 𝘁𝗵𝗲 𝗙𝗼𝘂𝗻𝗱𝗮𝘁𝗶𝗼𝗻 𝗼𝗳 𝗔𝗜

AI looks complex. You hear words like transformers and large language models every day.

The core idea is simple. It starts with the artificial neuron.

Biology inspired this. A biological neuron works in three steps:

• Dendrites receive signals.
• The cell body processes them.
• The axon sends an impulse forward.

Artificial neurons use math to do the same thing. They do not use biological signals. They use numbers.

Here is how an artificial neuron works:

• It takes numerical inputs.
• It multiplies each input by a weight.
• It adds the weighted inputs together.
• It adds a bias.
• It passes the result through an activation function.

The formula looks like this: z = w1x1 + w2x2 + ... + wn*xn + b

The activation function is critical. Without it, the network only solves linear problems. Activation functions allow the network to learn complex patterns.

One example is the sigmoid function. It produces a value between 0 and 1. This value shows how much confidence the neuron has in its output.

The perceptron was one of the first models to use this logic. Today, AI systems use billions of these connections.

Modern AI works because small mathematical units process information and pass signals forward.

The foundation of AI is math. The inspiration for that math is biology.

Source: https://dev.to/khasky/how-biology-became-the-foundation-of-artificial-intelligence-2427

Optional learning community: https://t.me/GyaanSetuAi