6h • General Discussion 💬
The Five Layers of the AI Stack
The Five Layers of the AI Stack
AI isn’t just about smart models anymore.
It’s a full stack
1) Energy & Physical Infrastructure
Everything starts with power, data centers, cooling, and networks. No energy = no AI. This is the real foundation.
2) Processing Chips (GPUs & Accelerators)
GPUs do the heavy lifting. Faster chips mean faster training, cheaper inference, and quicker experiments.
3) System Software & Orchestration
This layer connects thousands of chips into one system. Scheduling, networking, and coordination decide speed or slowdown.
4) AI Models
Models get the spotlight, but they scale only as far as infra allows. Bigger ideas still need real compute.
5) Applications
What users see — chatbots, copilots, automation. This layer moves fastest when the layers below are strong.
The key insight:
AI is now an infrastructure race. Power, chips, and orchestration are the real accelerators — or bottlenecks. Countries and companies that build lower layers faster compound their advantage over time.
Question:
Which layer do you think is the biggest bottleneck today?
And which one is most underrated by founders right now?
4
2 comments
The Five Layers of the AI Stack
skool.com/ai-automation-society
A community built to master no-code AI automations. Join to learn, discuss, and build the systems that will shape the future of work.
Leaderboard (30-day)
1
🔥
+2754
2
+1249
3
🔥
+1124
4
+1011
5
🔥
+706
Powered by