Last week, Chinese artificial intelligence (AI) lab DeepSeek released an open-source AI model, DeepSeek-R1, that performs nearly as well as OpenAI’s most recent model, o1, by some performance benchmarks yet at a much lower cost.
DeepSeek-R1 has become rapidly popular with hundreds of derivative models developed over just a number of days. This has negatively impacted the market value of U.S.-based competitors with Nvidia registering a record loss Monday.
Rice University AI experts are available to discuss the new model and weigh in on what it means for the future of AI.
“While DeepSeek is not exactly a breakthrough scientific innovation, it is impressive from an engineering perspective,” said Xia Ben Hu, an associate professor of computer science at Rice who researches machine learning algorithms and systems relevant to applications in social informatics, health informatics and information security. “Despite higher efficiencies, the demand for compute won’t likely decrease.”
Hu has developed an open-source package called AutoKeras that is among the most used automated deep learning systems on GitHub. Work on deep collaborative filtering, anomaly detection and knowledge graphs from Hu’s research group at Rice has been included in the TensorFlow package, Apple production system and Bing production system.
Anshumali Shrivastava, an associate professor of computer science, electrical and computer engineering and statistics at Rice, and a member of the Ken Kennedy Institute, sees the arrival of DeepSeek as “entirely expected.”
“More efficient AI alternatives are possible, and DeepSeek has finally allowed that to sink in in a real sense,” said Shrivastava, whose work focuses on large-scale machine learning, scalable deep learning, algorithms for big data and graph mining and leveraging AI for cybersecurity. “AI optimization is poised to become the next big focus.”
Shrivastava is the founder of ThirdAI, which develops custom, private and cost-effective AI solutions, and he has been an Amazon Visiting Academic, machine learning consultant at Blackstone and scientist at FICO.
To schedule an interview with one of these experts, contact Silvia Cernea Clark at sc220@rice.edu or Marcy de Luna at marcy.deluna@rice.edu.