The Chinese startup DeepSeek has sent shockwaves throughout the AI world with the release of its less-resource-intensive AI chatbot, calling into question the amount of power and financial investment needed to develop the technology.
The company started making waves this week when its app surpassed ChatGPT as the most popular free app on the Apple App Store.
The news comes just a week after it released its R1 reasoning model, which it said cost just $5.6 million of computing power to develop.
For comparison, OpenAI’s GPT-4 cost around $100 million to develop.
A Northeastern expert on artificial intelligence says this news is a positive development for the industry and will likely have a cascading effect.
Notably, the company’s models are open source, meaning they are free to be downloaded and modified by other parties.
“We’ve been tracking DeepSeek since they started to release their work, and we agree that their recent R1 drop is a big deal,” says David Bau, a Northeastern University professor in the Khoury College of Computer Sciences and the principal investigator of the National Deep Inference Fabric, which is working to investigate the “black box” components of AI chatbots.
Wall Street reacted sharply to DeepSeek’s rise. Microsoft and Google saw their stock prices sink. Nvidia was hit particularly hard, losing about 17% of its market value, which is close to $593 billion.
But Bau says this news shouldn’t be seen as a failure on Nvidia’s part, noting that DeepSeek’s architecture is based on Nvidia’s chips, just fewer of them.
“Many are asking whether DeepSeek will make American Nvidia chips less relevant, but we observe that historically, as you make technology cheaper, then you increase the aggregate demand for it,” Bau says.
For Nvidia’s part, Jensen Huang, the company’s co-founder and chief executive officer, welcomed DeepSeek’s new model, calling it “an excellent AI advancement.”
OpenAI CEO Sam Altman also had high praise for DeepSeek’s technology and said he was invigorated to have a new competitor in the space.
Bau says DeepSeek’s work may also encourage others to join the fray.
“The lower costs—and the demonstration that an upstart team can enter cheaply—will also attract other entrants,” he says.
But he emphasized that there is still much to explore.
“Every time we grow AI capabilities, we grow the scientific mystery,” he says. “More investment in the science of AI internals and AI interpretability is needed.”
Written by Cesareo Contreras, Northeastern University.
