How DeepSeek Cuts AI Costs: From Homegrown Tech to Desert Power
Last Updated on January 30, 2025 by Editorial Team
Author(s): Don Lim
Originally published on Towards AI.

This member-only story is on us. Upgrade to access all of Medium.
DeepSeek doesn’t rely on NVIDIA chips for inference. They also don’t solely use Western AI development frameworks like PyTorch and TensorFlow. This was a big shock to me as well, as I hadn’t paid too much attention to China’s software industry until recently. I’ve been developing software for several decades now, but the only software from China that I used was Filmora and face beautifying apps.
The Magnificent 7 (Mag7) companies can utilize similar optimization techniques as DeepSeek and save on electricity in remote locations. However, they won’t be able to escape NVIDIA’s influence, since they all use critical AI development frameworks called PyTorch and TensorFlow, which are currently dependent on NVIDIA chips.
Almost all Large Language Models (LLMs) use PyTorch (developed by Facebook) and TensorFlow (developed by Google) as development platforms or frameworks. These frameworks are specifically designed to handle the intensive vector and matrix calculations required for training and running large-scale neural networks. The developers of PyTorch and TensorFlow have been working with NVIDIA for… Read the full blog for free on Medium.
Join thousands of data leaders on the AI newsletter. Join over 80,000 subscribers and keep up to date with the latest developments in AI. From research to projects and ideas. If you are building an AI startup, an AI-related product, or a service, we invite you to consider becoming a sponsor.
Published via Towards AI
Towards AI Academy
We Build Enterprise-Grade AI. We'll Teach You to Master It Too.
15 engineers. 100,000+ students. Towards AI Academy teaches what actually survives production.
Start free — no commitment:
→ 6-Day Agentic AI Engineering Email Guide — one practical lesson per day
→ Agents Architecture Cheatsheet — 3 years of architecture decisions in 6 pages
Our courses:
→ AI Engineering Certification — 90+ lessons from project selection to deployed product. The most comprehensive practical LLM course out there.
→ Agent Engineering Course — Hands on with production agent architectures, memory, routing, and eval frameworks — built from real enterprise engagements.
→ AI for Work — Understand, evaluate, and apply AI for complex work tasks.
Note: Article content contains the views of the contributing authors and not Towards AI.