How AI Just Broke the Speed Limit (1,000 Tokens/Sec) скачать в хорошем качестве

How AI Just Broke the Speed Limit (1,000 Tokens/Sec)

For years, AI speed was limited by the 'Memory Wall'—the physical distance between a processor and its data. But on February 12, 2026, that wall came crashing down. OpenAI’s GPT-5.3 Codex-Spark has achieved a staggering 1,000 tokens per second, and the secret isn't a faster GPU—it's a massive piece of silicon the size of a dinner plate. In this video, we deep dive into the engineering of the Cerebras Wafer-Scale Engine and how it allows an entire LLM to sit on a single chip. No more data bottlenecks, no more waiting for code to compile. We’ll explore the new era of 'Vibe Coding' where software is built at the speed of thought, and why the industry is finally moving away from the NVIDIA hardware that defined the last decade. What you will learn: The physics of the 'Memory Wall' and why it slows down standard AI. How Wafer-Scale Engines differ from traditional GPU clusters. The mechanics of GPT-5.3 Codex-Spark and its 1,000 tokens/sec inference. What 'Vibe Coding' actually looks like in a professional workflow. Why OpenAI is pivoting its hardware strategy in 2026. Chapters: 00:00 The 1,000 Token Barrier 01:45 The Problem with Traditional GPUs 03:30 Inside the Cerebras Wafer-Scale Engine 05:15 How Codex-Spark Achieves Real-Time Speed 07:00 Vibe Coding: Building Apps with Voice 08:45 The Future of Specialized AI Silicon 10:00 Conclusion: A New Era of Computing If you want to stay ahead of the curve in the AI engineering space, make sure to like and subscribe for weekly deep dives into how the latest tech actually works. #OpenAI #Cerebras #AIHardware #GPT5 #VibeCoding