Скачать или смотреть How ChatGPT ACTUALLY Works — A Visual Deep Dive (2025) ||

Ever wondered what happens inside ChatGPT? 🤖

In this deep dive, I break down the ENTIRE process of how large language models work — from input to output — using beautiful animations. Updated for December 2025 with GPT-5.2, Gemini 3, Claude Opus 4.5, and Llama 4!

🧩 TOPICS COVERED:
Introduction & 2025 AI Landscape
Tokenization (How text becomes numbers)
Embeddings (How numbers become meaning)
Transformers (The architecture that changed AI)
Attention (The secret sauce)
Training ($500M+ and RLHF)
Generation (How responses are created)
Benchmarks & Future Outlook

📚 KEY CONCEPTS:
• Tokens & BPE Algorithm
• Embedding Vectors & Semantic Similarity
• Transformer Architecture (200+ layers in GPT-5.2!)
• Self-Attention & Multi-Head Attention
• RLHF (Reinforcement Learning from Human Feedback)
• Multimodal AI (Text, Image, Audio, Video)
• Autoregressive Generation & Sampling

🔢 DECEMBER 2025 STATS:
• 1.8 Trillion Parameters (GPT-5.2 estimated)
• 100,000+ Token Vocabulary
• 200+ Transformer Layers
• 10M Token Context (Llama 4 Scout!)
• $500M+ Training Cost

🚀 2025 AI MODEL COMPARISON:
• GPT-5.2 — 400K context, 92.5% MMLU (Dec 11, 2025)
• Gemini 3 Pro — #1 LMArena, 1M context
• Claude Opus 4.5 — Best coding, 81% SWE-bench (Nov 2025)
• Llama 4 — Open source, 10M context
• Sora 2 — Text-to-video with audio sync


🎨 All animations made with Manim (Python animation library)

#ChatGPT #GPT5 #AI #MachineLearning #DeepLearning #Transformers #ArtificialIntelligence #LLM #OpenAI #Claude #Gemini #Llama4 #AI2025