Скачать или смотреть DeepSeek’s MHC: The AI Breakthrough Big Tech Didn’t Expect

#DeepSeek #ArtificialIntelligence #AITraining #MachineLearning #DeepLearning #LLMs #AIResearch

DeepSeek didn’t launch a flashy chatbot.
They launched something far more important — a new way to train large AI models without them suddenly collapsing.

In this video, we break down DeepSeek’s new mHC (Manifold-Constrained Hyper-Connections) architecture in simple English. You’ll learn why numerical instability is one of the most expensive hidden problems in AI training, how failed training runs waste massive amounts of compute, and why DeepSeek’s approach isn’t about making AI bigger — but making it cheaper and more reliable to scale.

We explain:
• Why large AI models suddenly fail during training
• How ResNet and Hyper-Connections evolved into mHC
• What “training stability” really means in practice
• Why fewer crashes = lower costs and faster innovation
• How this could lower the barrier for smaller AI labs
• The risks of efficiency-first AI development

This isn’t hype. It’s infrastructure.
Because the next AI breakthrough might not look like a new chatbot — it might look like a training run that simply doesn’t crash.

👉 Question for you:
Do you think the future of AI will be won by the biggest models or the most efficient training systems?

#DeepSeek #ArtificialIntelligence #AITraining #MachineLearning #DeepLearning #LLMs #AIResearch #AIArchitecture #TechExplained #FutureOfAI #AIEngineering #ModelTraining #AIStability #AICompute #FoundationModels #Transformers #AIInnovation #ScalableAI #TechYouTube

Disclaimer: This video is for informational and educational purposes only. All product names, logos, and brands are property of their respective owners.