# Пов'язані статті щодо KV cache

DeepSeek's $10 Trillion Path: Leveraging Open Source to Pivot a Trillion-Dollar Hardware Ecosystem

This article proposes a strategic analysis of DeepSeek, arguing its goal is not short-term application-layer monetization but a long-term, foundational play to reshape the AI hardware ecosystem. It posits that DeepSeek's series of architectural innovations—MoE, MLA, DSA, CSA, Engram, TileLang—are fundamentally designed to drastically reduce the computational and memory (especially HBM) requirements for training and serving state-of-the-art AI models. By making AI feasible on hardware with lower performance (e.g., using NAND/SSD for KV Cache, LPDDR for weights and Engram storage), DeepSeek aims to foster and benefit from a viable alternative AI hardware supply chain, particularly in China. This strategy could unlock a trillion-dollar valuation for DeepSeek by enabling and owning a stake in a new, massive hardware ecosystem, rather than competing directly on subscriptions or multi-modal features.

marsbit05/25 13:13