Purchasing Shares of DeepSeek: A Step-by-Step Guide

Purchasing Shares of DeepSeek: A Step-by-Step Guide

DeepSeek burst onto the scene in early 2025, causing a stir in the AI industry. This Chinese AI startup, founded by Liang Wenfeng using funds from his hedge fund, is gaining attention for its innovative approach to AI model training. DeepSeek relies on a method called interference-time computing, which only activates the most relevant sections of the model during each query. This technique saves both time and money by eliminating the need for specialized semiconductors, like those from Nvidia, in large quantities.

While DeepSeek's AI models are relatively inexpensive to create, dominating AI establishments like OpenAI, Google, and Meta Platforms plan to invest heavily in AI infrastructure in the coming years. If DeepSeek can consistently build AI models at lower costs, it may pose a substantial disruption to the AI industry.

Artificial Intelligence Investments

If you're interested in investing in the AI sector, you might be wondering if DeepSeek is publicly traded and how to buy its stock. As of early 2025, the company is not publicly traded; it is privately owned by Liang Wenfeng's hedge fund, High-Flyer. Furthermore, DeepSeek has not announced any plans for an IPO in the near future.

However, you can still invest in the AI sector by looking into alternative companies like Nvidia, Microsoft, and Meta Platforms, which are all actively involved in AI development. There are several reasons why you might consider investing in these three alternatives instead of waiting for DeepSeek's IPO:

1. Nvidia:
2. Develops advanced chips for AI training models and applications.
3. DeepSeek's founder, Liang Wenfeng, reportedly stockpiled Nvidia chips before the US export ban on AI chips to China.
4. Nvidia may still benefit from AI developments, even if DeepSeek contains fewer specialized semiconductors.
5. Microsoft:
6. A leader in AI with significant investment in OpenAI, which developed the popular ChatGPT chatbot.
7. DeepSeek's breakthrough in creating AI models at a lower cost could drive the demand for AI, potentially benefiting Microsoft.
8. Meta Platforms:
9. Committed to investing heavily in AI to drive its core products and business.
10. If DeepSeek's lower-cost approach proves successful, Meta Platforms' development costs could drop, increasing its profitability.

To invest in these companies, follow steps 1 through 6 outlined below:

1. Log in to your brokerage app.
2. Enter the ticker or company name into the search bar.
3. Decide how many shares to buy based on your investment goals and the allocation of your portfolio for this stock.
4. Choose between a market order or a limit order, depending on your preferred pricing strategy.
5. Confirm and submit your order.
6. Review your purchase to ensure it was filled according to your expectations and adjust your investment strategy as needed.

Is DeepSeek Profitable?

Since DeepSeek is a privately held company, financial data on its profits is not publicly available. Investors should wait for the company's potential IPO before considering its profitability.

However, if DeepSeek does launch an IPO, it's wise to consider factors such as the true cost of training its AI model, transparency in the company's finances, geopolitical risks, possible fraud, and security and privacy concerns to help assess whether investing in the company might be profitable.

ETFs

As of early 2025, you cannot use exchange-traded funds (ETFs) to gain passive exposure to DeepSeek because it is not publicly traded. However, you can invest in ETFs that expose you to trends such as AI, robotics, and Chinese technology stocks. Some top options include:

1. Invesco China Technology ETF (CQQQ)
2. Global X Robotics & Artificial Intelligence ETF (BOTZ)
3. iShares Future AI & Tech ETF (ARTY)

These ETFs can help you diversify your investment portfolio and gain exposure to the broader AI sector without directly investing in DeepSeek.

Enrichment Data:

DeepSeek's AI model, particularly the DeepSeek-R1 model, utilizes inference-time computing, which is a highly efficient method for allocating computational resources during inference to evaluate multiple possible outcomes and select the best one. This technique, known as inference-time scaling or test-time scaling, improves model performance and efficiency.

DeepSeek's approach to AI model training and inference-time computing can have several significant impacts on the AI industry:

1. Lower training costs: DeepSeek's models can be created at significantly lower prices compared to traditional methods, challenging the idea that billion-dollar budgets are required for cutting-edge AI performance.
2. Increased AI adoption: The lower costs associated with DeepSeek's AI models could drive broader adoption of AI across industries, potentially increasing overall demand for AI infrastructure.
3. Improved performance: Inference-time scaling results in more accurate and optimized GPU attention kernels, which can lead to higher model performance.
4. Closed-loop workflow: A special verifier is used in a closed-loop fashion with the DeepSeek-R1 model to guide the code generation process, resulting in better outcomes each time.
5. Investment opportunities in AI infrastructure: DeepSeek's efficiency breakthrough could create additional demand for AI infrastructure, creating new investment opportunities in the fields of GPU manufacturing, data centers, and related technologies.
6. Competitive advantage: DeepSeek's efficiency breakthrough could attract significant investment as it challenges the dominance of US AI companies and offers a cost-effective alternative for researchers and smaller organizations to build and deploy competitive AI models.

In light of DeepSeek's innovative approach to AI model training, some established AI companies plan to invest heavily in AI infrastructure to stay competitive. For instance, Nvidia, a developer of advanced chips for AI training models and applications, may still benefit from AI developments even if DeepSeek requires fewer specialized semiconductors.

If DeepSeck's lower-cost approach to AI model creation becomes a consistent trend, it could disrupt the AI industry financially, potentially saving investors money when utilizing AI technologies.

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