How artificial intelligence is changing the way world builds computers

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By Cade Metz, Karen Weise, Marco Hernandez, Mike Isaac & Anjali Singhvi

 

The race to build artificial intelligence is driven by little silicon chips called graphic processing units (GPUs), which were originally created for video games. Tech companies are now packing GPUs — which are ideal for running the calculations that power artificial intelligence (AI) — as tightly as possible into specialised computers. 

The result is a new kind of supercomputer — a collection of up to 100,000 chips wired together in buildings known as data centers to hammer away at making powerful AI systems. All this computing power comes at a cost. OpenAI, the maker of ChatGPT, hopes to build about five facilities that would collectively consume more electricity than the roughly three million households in Massachusetts. As technology companies chase the dream of AI, these data centres are popping up across the country  and around the globe, forcing tech giants to hunt for the electricity to power them and the water for cooling systems to keep the chips from frying in their own heat. 

Just as companies completely rebuilt their computer systems to accommodate the new commercial internet in the 1990s, they are now rebuilding from the bottom up — from tiny components to the way that computers are housed and powered — to accommodate AI. 

Big tech companies have constructed computer data centres all over the world for two decades. The centers have been packed with computers to handle the online traffic flooding into the companies’ internet services, including search engines, email applications and e-commerce sites. 

But those facilities were lightweights compared with what’s coming. Back in 2006, Google opened its first data center in The Dalles, Ore, spending an estimated $600 million to complete the facility. In January, OpenAI and several partners announced a plan to spend roughly $100 billion on new data centres, beginning with a campus in Texas. They plan to eventually pump an additional $400 billion into this and other facilities across the US. The change in computing is reshaping not just technology but also finance, energy and communities. Private equity firms are plowing money into data centre companies. Electricians are flocking to areas where the facilities are being erected. And in some places, locals are pushing back against the projects, worried that they will bring more harm than good. The bigger-is-better mantra was challenged in December when a tiny Chinese company, DeepSeek, said it had built one of the world’s most powerful AI systems using far fewer computer chips than many experts thought possible. That raised questions about Silicon Valley’s frantic spending. 

US tech giants were unfazed. The wildly ambitious goal of many of these companies is to create artificial general intelligence, or AGI — a machine that can do anything the human brain can do — and they still believe that having more computing power is essential to get there. 

Alphabet  recently indicated that their capital spending — which is primarily used to build data centers — could top a combined $320 billion this year. That’s more than twice what they spent two years ago. By analysing massive datasets, algorithms can learn to distinguish between images, in what’s called machine learning. The example below demonstrates the training process of an AI model to identify an image of a flower based on existing flower images. Training AI models involves analysing large amounts of reference data — a process that requires a lot of time and computing power.

 

So, tech companies started using increasingly large numbers of GPUs to build increasingly powerful AI technologies. “The old model lasted for about 50 years,” said Norm Jouppi, a Google engineer who oversees the company’s effort to build new silicon chips for AI. “Now, we have a completely different way of doing things.”  It is not just the chips that are different. To get the most out of GPUs, tech companies must speed the flow of digital data among the chips.

 

Tech at a cost 

Tech companies using large numbers of GPUs to build increasingly powerful AI technologies

They have developed new hardware and cabling to rapidly stream data from chip to chip

The change in computing is reshaping not just technology but also finance, energy, and communities

OpenAI hopes to raise hundreds of billions of dollars to construct computer chip factories in West Asia

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