CPU, GPU, HBM: What’s Actually Inside an AI Server?
An AI server is three parts doing three jobs — CPU, GPU and HBM memory. Here is what each one does and why the split explains the whole AI build-out.
Skopa Insights is a library of interactive long-form explainers covering AI hardware (CPU/GPU/HBM, the memory wall, chip manufacturing), the semiconductor supply chain and its choke points, hyperscaler capex, the Fed and monetary policy, earnings-season analysis and factor investing. Each piece is built around live charts and simulators rather than static text.
An AI server is three parts doing three jobs — CPU, GPU and HBM memory. Here is what each one does and why the split explains the whole AI build-out.
A GPU can do math faster than anything can feed it numbers. The memory wall — not raw compute — is what AI hardware engineers actually fight about.
One AI chip starts as a bucket of quartz sand and, three months later, is the most complex object humans manufacture. Every step, and every choke point.
One job teaches the model, the other uses it. Almost every argument about AI costs and profits comes down to which one you actually mean.
A handful of choke points decide who builds the world’s chips and who profits when they break. The full semiconductor supply chain, layer by layer.
The real money in clean energy isn’t in the headline solar and EV names. It’s in the mid-cap infrastructure firms capturing the actual capital flows.
EPS beats are a trap. Guidance revisions, margin trajectory and the words management avoids are what actually move a stock after earnings.
Four companies will spend $380B on AI infrastructure in 2026. Whether that is the greatest build-out in history or the costliest capex cycle ever.
Drag the Fed funds rate and watch mortgages, jobs, stocks and the dollar respond. The lags are real and the trade-offs are unforgiving.
After a decade of growth dominance, the P/E spread, sector leadership and the rate regime all point the same way. The case for value, with the numbers.