Every conversation with a chatbot hides a growing accounting problem. Each token the model generates must attend to every token
Continue readingThe KV Cache: The Memory Bill Behind Every Token Your Model Generates
Every LLM serving stack lives or dies by one data structure most developers never see: the KV cache. It is
Continue readingThe KV Cache: Why LLM Serving Is a Memory Problem
Ask someone to sketch a transformer on a whiteboard and they’ll draw the 2017 version: softmax attention over every pair
Continue readingMHA, MQA, GQA, MLA: The KV-Cache Trade-offs Behind Every Modern Transformer
DeepSeeded? No — DeepSeek. In September 2026 the Chinese AI lab released a paper titled “DeepSeek-V4.1-Flash: Pushing the Limits of
Serving a large language model to thousands of concurrent users is, underneath all the marketing, a memory management problem. Every
Continue readingDeepSeek-V4.1-Flash: Why the Most Interesting AI Paper This Month Is About Storage
AI agents have gotten remarkably good at reasoning, perceiving, and acting. But ask one to remember what you told it
Continue readingMetis: The First Memory Foundation Model That Learns to Remember
The attention mechanism is the backbone of every transformer model, but it carries a brutal cost: quadratic complexity with respect
Continue readingHow MiniMax Sparse Attention Achieves 28x Compute Reduction at 1M Context Length