Day 3: Neural Networks vs. The Human Brain (Prediction vs. Thinking) скачать в хорошем качестве

Day 3: Neural Networks vs. The Human Brain (Prediction vs. Thinking)

Title Day 3: Neural Networks vs. The Human Brain (Prediction vs. Thinking) We often hear that Artificial Intelligence is modeled after the human brain, but this comparison is based on 70 years of misleading terminology. In Day 3 of our series, we strip away the sci-fi hype to reveal the mathematical reality behind "Deep Learning". While biological neurons are living cells influenced by chemistry, hormones, and emotion , artificial neurons are simply mathematical functions that process numbers in a digital vacuum. We break down exactly how AI moves from random guessing to high-accuracy prediction—not through understanding, but through "weighted voting" and massive repetition. In this video, we cover: The "Brain" Myth: How the 1956 Dartmouth Conference sparked a metaphor that confuses the public to this day. The Learning Loop: A simple breakdown of how Neural Networks learn via inputs, weights, and Backpropagation (fixing errors). Humans vs. AI: Why humans win on Context and Adaptation (learning from 1 example) , while AI wins on Speed and Consistency (learning from 10,000 examples). The "Common Sense" Trap: Why AI makes confident mistakes that a human never would, simply because it lacks genuine understanding of cause and effect. Stop assuming the machine "thinks." Learn how it predicts. Next Up: Stay tuned for Day 4, where we expose how these systems control your job prospects, loans, and social feeds without knowing a single thing about you. #neuralnetworks #ArtificialIntelligence #DeepLearning #MachineLearning #AIvsHuman #Backpropagation #DataScience #TechEducation #AIHistory #HowAIWorks #PatternRecognition #MathNotMagic #FutureOfAI #SmartTech #EdTech