DeepSeek located in Hangzhou, Zhejiang, China, is CEO Liang Wenfeng’s company. It is making headlines with the release of an open-source AI model that reportedly surpasses well-known models from organizations like OpenAI. Notably, DeepSeek’s model operates with significantly lower computing requirements – utilizing fewer GPUs or specialized AI processors – while being developed by a comparatively less experienced team than those at leading AI labs.
This raises critical questions: Was everything developed as it should be, following the expected trajectory of AI innovation? Or is DeepSeek’s model a distilled version of U.S. technological advancements? Furthermore, with its rapid deployment and open-source approach, how does DeepSeek handle user data? What are the implications for data privacy, security, and potential surveillance? If it seems too good to be true, is it too good to be true?
Italy’s Privacy Guarantor & Data Protection
On January 28th, 2025, The Italian Data Protection Authority formally requested information from DeepSeek, raising concerns about potential risks to the personal data of millions of people in Italy. This development suggests that DeepSeek’s future in the EU may be uncertain.
Full statement in English:
“The Guarantor for the Protection of Personal Data has sent an inquiry to Hangzhou DeepSeek Artificial Intelligence and Beijing DeepSeek Artificial Intelligence—the companies operating the DeepSeek chatbot service via both web and mobile applications.
Given the potential high risks to user data, the Authority has asked the companies and their affiliates to clarify which personal data they collect, the sources of this data, the purposes of processing, the legal basis for such processing, and whether the data is stored on servers in China.
Additionally, the Guarantor has requested details on the types of information used to train DeepSeek’s AI system. If personal data is collected through web scraping, the companies must explain how both registered and unregistered users have been informed about the processing of their data.
The companies have 20 days to provide the requested information.”
In a fitting move for “Data Protection Day,” the Italian Authority has marked the occasion with decisive regulatory action. The CPDP – Data Protection Day is held yearly on January 28 to commemorate the 1981 signing of Convention 108, the first legally binding international agreement dedicated to safeguarding privacy in the digital era.
OpenAI as the “Teacher Model”?
OpenAI and Microsoft allege that DeepSeek violated its terms of service and intellectual property rights by using knowledge distillation on OpenAI’s models. Bloomberg reported that Microsoft Probing If DeepSeek-Linked Group Improperly Obtained OpenAI Data. According to Alex McMurray in efinancialcareers “Peking graduate hires at DeepSeek include Xiaokang Chen, a computer vision specialist, ex-Microsoft intern and 2024 PhD graduate.” (Jan. 27, 2025)
As IBM explains, knowledge distillation is a technique where a smaller “student” model is trained to replicate the behavior of a larger “teacher” model, effectively transferring knowledge between neural networks. OpenAI’s terms of service explicitly prohibit both reverse engineering their models and using their outputs to develop competing models. If OpenAI can prove that DeepSeek used knowledge distillation in this way, they may pursue legal action, though the case could be complicated by the fact that OpenAI is based in the United States while DeepSeek operates from China.
DeepSeek’s Approach: Pioneering or Just Iterative?
DeepSeek’s much hyped success stems from its pioneering approach to model architecture. The company introduced a novel MLA (multi-head latent attention) method that lowers memory usage to just 5–13% of what the more common MHA architecture consumes. They also devised the DeepSeekMoESparse structure, which effectively minimizes computational requirements and, in turn, further drives down overall costs. The DeepSeek V3 model, containing 671 billion parameters, was reportedly developed with remarkable cost efficiency at US$5.58 million over approximately two months. Andrej Karpathy@karpathy, a highly regarded computer scientist, former Director of AI at Tesla, and founder of Eureka Labs, a new AI+Education company, wrote in X;
“DeepSeek (Chinese AI co) making it look easy today with an open weights release of a frontier-grade LLM trained on a joke of a budget (2048 GPUs for 2 months, $6M).”
Andrej Karpathy
Large Language Models (LLMs), which power AI systems like ChatGPT, rely on parameters to process and understand complex patterns in data. The more parameters a model has, the better it can comprehend and generate sophisticated responses. By making their model open source, DeepSeek allows developers worldwide to access, modify, and enhance the underlying code, enabling community-driven improvements and adaptations of the technology.
What Is a Quant Fund?
A “quant fund,” short for “quantitative fund,” is a type of hedge fund that relies on mathematical models, statistical techniques, and algorithmic processes to guide its investments. Unlike more traditional hedge funds that depend on human-led analysis or discretionary decision-making, quant funds use data-driven strategies. Their teams often comprise mathematicians, data scientists, and computer scientists who develop and maintain models for automated trading and risk management. In this sense, AI plays a prominent role, as machine learning models can enhance prediction accuracy and allow real-time decision-making.
High-Flyer, the quant fund founded by Wenfeng, exemplifies this model-driven approach by integrating sophisticated algorithms into its trading strategies. Since 2015, High-Flyer has reportedly returned around 13% on average each year
Wenfeng’s DeepSeek Path
Yu Lili and Liu Jing interviewed Liang Wenfeng, to find out his novel path.
Here is an extensive quote from the interview:
“Undercurrent”: Before this, most Chinese companies would directly copy this generation of Llama structure for application. Why did you start from the model structure?
Liang Wenfeng: If the goal is to develop applications, then it is a reasonable choice to continue using the Llama structure and quickly launch products. But our destination is AGI, which means we need to study new model structures to achieve stronger model capabilities under limited resources. This is one of the basic research required to scale up to larger models. In addition to the model structure, we have also done a lot of other research, including how to construct data, how to make the model more human-like, etc., which are all reflected in the models we released. In addition, the structure of Llama is estimated to be two generations behind the advanced level abroad in terms of training efficiency and inference cost.
Project Stargate
American AI development remains robust with President Trump’s (click President Trump to watch the YouTube recording) important announcement at the White House on Project Stargate. According to the Stargate website:
“The Stargate Project is a new company which intends to invest $500 billion over the next four years building new AI infrastructure for OpenAI in the United States. We will begin deploying $100 billion immediately. This infrastructure will secure American leadership in AI, create hundreds of thousands of American jobs, and generate massive economic benefit for the entire world. This project will not only support the re-industrialization of the United States but also provide a strategic capability to protect the national security of America and its allies.”
Stargate’s large-scale initiative aims to bolster American leadership in AI, generate hundreds of thousands of domestic jobs, and yield substantial economic advantages worldwide. Beyond aiding the re-industrialization of the United States, the venture will also offer a strategic capability to safeguard the national security interests of America and its allies.
SoftBank, OpenAI, Oracle, and MGX provide the initial equity for Stargate. Among these, SoftBank and OpenAI serve as the primary partners, with SoftBank overseeing financial obligations and OpenAI managing operational responsibilities. Masayoshi Son will act as Stargate’s chairman. The principal technology collaborators for the project are Arm, Microsoft, NVIDIA, Oracle, and OpenAI. Construction is already underway in Texas, and additional sites are being evaluated nationwide as final agreements are put in place.
Project Stargate and Aristotle’s Nicomachean Ethics
In accordance with Aristotle’s Nicomachean Ethics, Project Stargate’s vast undertaking can be viewed as a pursuit of the collective good, promising both economic vitality and strengthened security for society. By mobilizing significant resources toward AI development, it embodies the Aristotelian principle of practical wisdom (phronesis), which demands reasoned action directed toward virtuous ends.
This article was written by Dr. Jasmin (Bey) Cowin, Associate Professor and U.S. Department of State English Language Specialist (2024). As a columnist for Stankevicius, she writes on Nicomachean Ethics: Insights at the Intersection of AI and Education. Connect with her on LinkedIn.
