Programming nature using AI

Using biology to solve coding errors

Mimicking natural systems to design better technologies

Turning biological organisms into machines

Reinforcing food paths

Growing toward food

Solving mazes

Sending error messages to the CPU

It’s too complicated

It wastes electricity

It executes only one instruction at a time, underusing CPU resource

It doesn’t support binary code

To make the CPU smaller

To reduce power consumption

To execute multiple instructions at different stages simultaneously

store instructions in memory

Slime mold errors

Slow RAM access

Power surges

Delays caused by decision-making in code

It avoids overheating

It predicts program output

It keeps frequently used data close for faster access

It stores backup instructions in case of failure

Multiple cores running multiple tasks simultaneously

One task done in sequential stages

One core running multiple programs at once

A process that only works on GPUs

Pipelining

Branch prediction

Cache optimization

Instruction decoding

It executes the instruction

It writes the result

It retrieves the instruction from memory

It decodes the instruction

They look nice in visualizations

They can talk to animals

They replace CPUs with living organisms

They offer adaptive, decentralized solutions to complex problems

Pipelining

Branch Prediction

Cache Optimization

Parallel Processing