Deep Learning History: How Artificial Intelligence Took Over скачать в хорошем качестве

Deep Learning History: How Artificial Intelligence Took Over

Deep learning didn’t arrive as a clean victory—it arrived as an argument that refused to end, kept alive by researchers who kept building "the same strange machine" long after the field declared it unfashionable, unscientific, or dead. This documentary follows the deep learning boom of the 2010s as a cultural and economic shift: how the internet became a training ground, how GPUs built for games became the engine, and how a research debate turned into an arms race over data, silicon, and power. ​ What this documentary covers Why early AI felt sleek in movies but brittle in real labs, dominated by feature engineering and handcrafted rules ​ How ImageNet-scale data (built through massive distributed human labeling) changed what machines could learn from the world ​ Why GPUs—parallel hardware pushed by video games—were perfectly suited for training neural networks (matrix-heavy learning at scale) ​ The 2012 “scoreboard moment” where deep convolutional nets created a performance gap too large to ignore, shifting the entire field overnight ​ The next shockwaves: deep reinforcement learning (agents learning strategies from pixels), AlphaGo-era cultural impact, and self-play systems that surpassed human tradition ​ Generative models and GANs: synthetic faces, deepfakes, and the collapse of “seeing is believing” ​ Transformers (“Attention is all you need”): how attention unlocked scalable language models and changed the interface to computation ​ The real substrate of the revolution: compute as oil, data centers as refineries, and intelligence becoming an industrial product shaped by capital and infrastructure ​ The costs: bias, brittleness, adversarial failures, invisible human labor, and the environmental footprint of training at scale ​ The core question By the end of the decade, the question stopped being “Does it work?” and became: who controls the compute, who owns the data, who pays the environmental cost, and what kind of world gets built while everyone is distracted by the next breakthrough headline. ​ Chapters: 00:00 — The winter that didn’t end 05:30 — Feature engineering and the “control” era 12:00 — ImageNet: fuel at world scale 18:30 — GPUs: gaming hardware becomes the engine 25:00 — 2012: the scoreboard changes everything 33:00 — Agents that learn: reinforcement learning shocks 40:00 — GANs and synthetic reality 46:00 — Transformers and the language pivot 52:00 — Compute, power, and the new arms race #DeepLearning #MachineLearning #AIHistory #NeuralNetworks #Transformers #GANs #ReinforcementLearning #ImageNet #TechDocumentary 🤖 AI-generated content notice This video uses AI-generated narration and AI-assisted visuals to tell a long-form documentary story about deep learning’s modern rise, including datasets, GPUs, reinforcement learning, GANs, and transformers. The narration is based on a researched script and presented in an original documentary style (not copied from any single source).