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4 articles found

Engrams Won’t Let You Run 1T Models Locally, But They’ll Do Something Better

The Engram approach using N-gram embedding tables is reshaping how small models reason by offloading memorization to O(1) lookups. Here’s why the hype misses the real breakthrough.

#efficient inference#Engrams#local LLMs...

document AI

OCR’s Memory Wall Just Crumbled: Why Page-by-Page Parsing Is Now a Legacy Pattern

Deep dive into the R-SWA attention mechanism behind Unlimited OCR, which makes KV cache growth a non-issue and enables one-shot parsing of entire books.

#document AI#Large Language Models#system design...

AI Inference

The Inference-First Rebellion: How Mamba 3 Is Rewriting the Rules of Efficient AI

Mamba 3’s state space architecture challenges Transformer dominance by optimizing for inference rather than training, delivering 7x speedups and superior hardware utilization.

#AI Inference#machine learning#Mamba-3...

artificial intelligence

Kimi Just Made Residual Connections Obsolete: The 10-Year Assumption That Crumbled Overnight

Moonshot AI’s Attention Residuals architecture replaces decade-old residual connections with selective depth-wise attention, delivering 1.25x compute efficiency and breaking the PreNorm dilution bottleneck that has plagued deep transformers.

#artificial intelligence#Deep Learning#machine learning...