Скачать или смотреть DeepSeek’s New "Engram" Architecture: The Memory Upgrade AI Desperately Needed

DeepSeek just released a groundbreaking architectural shift that challenges the standard "bigger is better" approach to AI. For years, we’ve relied on massive compute to force models to "learn," but they still lack a fundamental human trait: true memory.
In this deep dive, we explore Engram, DeepSeek’s solution to the inefficiency of current LLMs. Instead of forcing the model to constantly re-compute simple patterns like "Alexander the Great" or "United States," Engram introduces a dedicated, hash-based memory module that allows the AI to instantly recognize familiar concepts.
We break down the math, the architecture, and the surprising results—including why adding memory actually makes the AI better at reasoning and coding, not just recalling facts.
In this video, we cover: 🚀 The Efficiency Wall: Why scaling parameters isn't enough anymore. 🧠 Memory vs. Compute: How Engram saves energy by using "constant time lookup" for billions of patterns. 🛡️ The Truth Detector: The gating mechanism that prevents the memory module from hallucinating. 📈 The 25% Rule: DeepSeek’s mathematical formula for the perfect balance between "Experts" and "Memory". 📊 Benchmark Breakdowns: Why Engram beats standard MoE models on MMLU, Math (GSM8K), and Coding (HumanEval). 🔎 Needle in a Haystack: How this architecture achieved a massive jump in long-context accuracy (84.2% → 97.0%).
DeepSeek has proven that by offloading "boring" reconstruction tasks to memory, we free up the model’s deeper layers for complex thought. If you are an AI engineer or enthusiast, you need to understand this architecture.
CHAPTERS: 0:00 - The Efficiency Wall: Why LLMs are Inefficient 1:15 - The "Relearning" Problem (Alexander the Great Example) 2:45 - Introducing ENGRAM: The Hash Table Solution 4:10 - The "Truth Detector" Gating Mechanism 5:30 - The Mathematical Sweet Spot (20-25% Memory) 6:50 - Benchmark Results: Reasoning & Coding Boosts 8:15 - The Depth Effect: Why Memory Improves Logic 9:40 - Long Context & Needle in a Haystack 10:55 - Real-World Efficiency (CPU Offloading) 12:10 - The Verdict
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