AWS Trainium

AWS Trainium is a computer chip that the online giant Amazon designed itself. Amazon rents out computing power through its AWS division, meaning through huge data centers that customers rent access to via the internet. Trainium sits in exactly these data centers. The chip is built for a single task: training AI systems. Training means that a program learns from millions of examples until it can write texts or recognize images. This requires an unimaginable number of computing steps, and normal processors from a laptop would be far too slow for this.

Amazon’s way out of dependence on Nvidia

Almost all major AI models of recent years have been trained on chips from the company Nvidia. Nvidia dominates this market so strongly that customers often wait months for deliveries. Prices are correspondingly high. For a company like Amazon, this is a double problem: it pays a lot and is dependent on a single supplier.

Trainium is the answer to this. Amazon does not build the chip to sell it in stores. The chip only runs in Amazon’s own data centers, and customers rent computing time there. This way, the margin stays in-house instead of flowing to Nvidia. Google pursues the same strategy with its TPU chips, as does Microsoft.

For the financial world, Trainium is therefore a signal. Every chip that a cloud provider builds itself is a chip it does not buy. Investors closely watch how quickly these in-house developments gain market share. So far, Nvidia remains clearly in the lead, but the gap is an important gauge.

What sets the chip apart from the processor in a laptop

A normal processor is an all-rounder. It can play music, calculate spreadsheets, and render games. Trainium can do almost none of that. It essentially masters one type of computation: the mass multiplication and addition of large number tables. That is exactly what AI training consists of, over ninety percent of the time.

This specialization is the whole trick. Because the chip doesn’t need to do anything else, Amazon can use almost the entire surface area for computing units. A comparison from everyday life: a Swiss Army knife can cut bread, but a bread knife cuts it faster and cleaner. Trainium is the bread knife.

A single chip is never enough, though. For a large language model, thousands of Trainium chips are connected together and work on the same model. For this to work, the chips must be able to communicate with each other extremely quickly. Amazon has developed its own interconnect network for this purpose. In addition, there is a sister chip called Inferentia, which does not train but instead runs the finished model in daily operation.

Trainium in headlines and in products

You never see the chip directly. It sits in a hall, often thousands of kilometers away. But anyone who uses a chatbot running on AWS may indirectly be using Trainium hardware. The best-known example is the company Anthropic, in which Amazon has invested billions and whose models are partly trained on Trainium.

In business news, the name usually appears in two contexts. First, in Amazon’s quarterly results, when it comes to the enormous investments in data centers. Second, in reports about chip competition, when the question is whether Nvidia will retain its dominant position.

A common misconception is that Trainium is a competing product for private individuals. No one can install this chip in a PC. It exists exclusively as a rental service in the cloud. This is exactly what makes it so attractive for Amazon: the customer pays for computing time, not hardware, and ideally notices nothing at all about the chip switch.