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My First „AI Moment”: Building Neural Nets with Python & Genetic Algorithms, 25 Years Ago
Long before today’s AI boom and the proliferation of sophisticated tools, about 25 years ago, I had my first truly profound encounter with the core concepts of machine learning. Driven by a deep curiosity about how systems could „learn” to solve problems autonomously, I embarked on a journey to build one from scratch.
My toolkit back then? Python, which even in its earlier days showed its versatility, and a custom-built neural network. For the learning process, I didn’t have pre-trained models or advanced frameworks; I turned to genetic algorithms – a fascinating approach that mimics the principles of natural evolution to find solutions.
I created a „population” of simple neural networks. Each network had its weights and activation thresholds (their „genes”) initialized randomly. The training was an iterative evolutionary process:
* The „fittest” networks – those that performed best on a given set of input-output examples – were selected.
* Their „genes” (the network weights and parameters) were then „recombined” (crossover) and subjected to random „mutations” to create a new, potentially improved, generation.
This cycle of selection, recombination, and mutation repeated, allowing the population of networks to gradually „evolve” a solution.
The real „aha!” moment, the one that truly solidified my fascination with AI, came when I tested this system on logical operations – specifically the XOR problem. This is a classic non-linear challenge that simple, single-layer networks can’t solve. I fed the network input-output examples for XOR, launched the evolutionary loop, and watched.
To my amazement, after many generations, a network emerged that correctly performed the XOR operation for new, unseen inputs! It had learned the underlying logic without me ever explicitly programming the rules for XOR. It figured it out.
And all this was achieved using Python on hardware that would genuinely be an embarrassment to find in a smartwatch today! The feeling was incredible – not just because it solved XOR, but because it demonstrated a system devising its own solution path through learning and evolution.
That early, hands-on experience, building and training a neural network from fundamental principles, instilled in me a deep and lasting appreciation for how machines can learn and adapt. It’s a foundational perspective that continues to shape how I approach complex AI and automation challenges today – always seeking to understand the core mechanics, not just applying „black-box” tools.
This foundational journey fuels my ongoing passion for leveraging Python and AI to build truly intelligent, innovative, and practical solutions.
➡️ Follow my profile for more insights on AI’s practical applications, how the journey of innovation drives modern solutions!
#AI #MachineLearning #NeuralNetworks #GeneticAlgorithms #Python #Innovation #TechJourney #ProblemSolver
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Autor: Administrator | Opublikowano: 17 maja, 2025
