How Did DeepSeek Build Its A.I. With Less Money?
The Chinese start-up used several technological tricks, including a method called “mixture of experts,” to significantly reduce the cost of building the technology.
The Chinese start-up used several technological tricks, including a method called “mixture of experts,” to significantly reduce the cost of building the technology.
Last month, U.S. financial markets tumbled after a Chinese start-up called DeepSeek said it had built one of the world’s most powerful artificial intelligence systems using far fewer computer chips than many experts thought possible.
A.I. companies typically train their chatbots using supercomputers packed with 16,000 specialized chips or more. But DeepSeek said it needed only about 2,000.
As DeepSeek engineers detailed in a research paper published just after Christmas, the start-up used several technological tricks to significantly reduce the cost of building its system. Its engineers needed only about $6 million in raw computing power, roughly one-tenth of what Meta spent in building its latest A.I. technology.
What exactly did DeepSeek do? Here is a guide.
How are A.I. technologies built?
The leading A.I. technologies are based on what scientists call neural networks, mathematical systems that learn their skills by analyzing enormous amounts of data.
The most powerful systems spend months analyzing just about all the English text on the internet as well as many images, sounds and other multimedia. That requires enormous amounts of computing power.
About 15 years ago, A.I. researchers realized that specialized computer chips called graphics processing units, or GPUs, were an effective way of doing this kind of data analysis. Companies like the Silicon Valley chipmaker Nvidia originally designed these chips to render graphics for computer video games. But GPUs also had a knack for running the math that powered neural networks.
