The tech industry loves its garage startup stories. From Hewlett-Packard to Google, stories of bootstrapped companies becoming giants have inspired generations of entrepreneurs.
But the huge sums of money and computing power required for start-ups trying to harness it with today’s hottest technology, the artificial intelligence used in chatbots like ChatGPT and Google Bard, may be making those inspirational stories are a thing of the past.
In 2019, Aidan Gomez and Nick Frosst left Google to create an AI start-up in Toronto called Cohere that could compete with their former employer. A few months later, they went back to Google and asked if it would sell them the massive computing power they would need to build their own AI technology. After Google chief executive Sundar Pichai personally approved the arrangement, the tech giant gave them what they wanted.
“It’s ‘Game of Thrones.’ That is what it is,” said David Katz, a partner at Radical Ventures, Cohere’s first investor. Big companies like Google, Microsoft and Amazon, he added, control the chips. “They control the power of computing,” he said. “They choose who gets it.”
Building a groundbreaking AI start-up is difficult without gaining the support of “hyperscalers,” who control vast data centers capable of running AI systems. And that’s put industry giants in the driver’s seat — again — for what many expect to be the most important change for the tech industry in decades.
OpenAI, the start-up behind ChatGPT, recently raised $10 billion from Microsoft. It will return most of that money to Microsoft as it pays for time on massive clusters of computer servers operated by larger companies. Encompassing thousands of specialized computer chips, these machines are essential to improving and expanding the capabilities of ChatGPT and similar technologies.
Competitors won’t be able to keep up with OpenAI unless they can get their hands on the same amount of computing power. Cohere recently raised $270 million, bringing its total funding to more than $440 million. It will use much of that money to buy computing power from the likes of Google.
Other start-ups have made similar arrangements, notably a Silicon Valley company called Anthropic, founded in 2021 by a group of former OpenAI researchers; Character.AI, founded by two leading researchers from Google; and Inflection AI, founded by a former Google executive. Inflection raised a $1.3 billion funding round last week, bringing its total to $1.5 billion.
At Google, Mr. Gomez was part of a small research team that designed the Transformerthe core technology used to create chatbots like ChatGPT and Google Bard.
Transformer is a powerful example of what scientists call a neural network — a mathematical system that can learn skills by analyzing data. Neural networks have been around for years, helping to power everything from conversational digital assistants like Siri to instant translation services like Google Translate.
The Transformer took the idea into new territory. Running on hundreds or even thousands of computer chips, it can analyze more data, faster.
Using this technology, companies like Google and OpenAI have begun to build systems that learn from vast amounts of digital text, including Wikipedia articles, digital books and chat logs. As these systems analyzed more data, they learned to generate text on their own, including term papers, blog posts, poetry and computer code.
These systems — called large language models — now power chatbots like Google Bard and ChatGPT.
Before ChatGPT arrived, Mr. Gomez left Google to start his own company with Mr. Frosst and another Toronto businessman, Ivan Zhang. The goal is to build large language models that challenge Google.
At Google, he and his fellow researchers have access to an almost unlimited amount of computing power. After leaving the company, he needed something similar. So he and his co-founders bought it from Google, which sold access to the same chips through cloud computing services.
Over the next three years, Cohere created a large language model that rivals almost any other. Now, it is selling this technology to other businesses. The idea is to give any company the technology they need to build and run their own AI applications, from chatbots to search engines to personal trainers.
“The strategy is to build a platform on which others can build and experiment,” Mr. Gomez said.
OpenAI offers a service along the same lines called GPT-4, which many businesses already use to build chatbots and other applications. This new technology can analyze, generate and edit text. But soon it will handle images and sounds as well. OpenAI is preparing a version of GPT-4 that can analyze a photo, instantly describe it and even answer questions about it.
Microsoft’s chief executive, Satya Nadella, said the company’s arrangement with OpenAI is the kind of mutually beneficial relationship it has long nurtured with smaller competitors. “I grew up in a company that was always doing these kinds of deals with other companies,” he told The New York Times earlier this year.
As the industry races to match GPT-4, entrepreneurs, investors and pundits debate who the winners will be. Most agree that OpenAI is leading the field. But Cohere and a small group of other companies are building similar technology.
The tech giants are in a strong position because they have the vast resources needed to push these systems further than anyone else. Google too holds the Transformer patentthe foundational technology behind the AI systems that Cohere and many other companies are building.
But there is one wild card: Open source software.
Meta, another giant with the computing power needed to build the next wave of AI, recently opened up its latest big language model, meaning anyone can reuse it and build on top of it. Many in the field believe that this type of freely available software will allow anyone to compete.
“Having every researcher on Earth think together will defeat any company,” said Amr Awadallah, chief executive of AI start-up Vectara and a former Google executive. But they would still have to pay for access to a larger competitor’s data centers.
