What is DeepSeek & How Crypto Traders Can Use It?

What is DeepSeek and why is it causing a stir? People were caught off guard when Chinese AI (Artificial Intelligence) model, DeepSeek-R1, shot to the top of the U.S. iOS App Store, even beating ChatGPT as the most downloaded free app. It was a big moment that challenged the idea that top AI breakthroughs would always come from Western companies.

A big reason for its success? It offers high-level AI capabilities without needing massive computing power, making it much more accessible than many other AI models.

For crypto traders, this kind of AI can be a game-changer. DeepSeek’s models can scan huge amounts of market data, pick up on trends, and provide insights that help traders make smarter decisions, which could potentially lead to better profits.

In this guide, we’ll dive deep into this AI model, exploring how to use DeepSeek and comparing it to ChatGPT and other AI models. We’ll cover what makes DeepSeek different from already established LLMs, why it’s growing so fast, and how crypto traders can use it to get ahead of the market.

What is DeepSeek AI?

DeepSeek is a Chinese AI company that’s making headlines for its open-source approach to AI models. Unlike many AI companies that keep their models closed and restrict customization, the Chinese wonder is fully open to developers, researchers, and businesses.

This openness has made it popular among those looking for AI solutions that don’t require expensive API subscriptions or come with usage limits.

One of the biggest advantages of this AI model is its lightweight design. Instead of relying on brute force like many Western AI models, DeepSeek only activates the necessary parameters. This means it can do complex tasks with fewer resources—perfect for businesses that want to run AI locally instead of in the cloud. Since it’s open-source, developers around the world can modify and improve it, so it’s constantly being refined and new applications are being added.

How Good is DeepSeek?

What is DeepSeek used for? DeepSeek AI has performed well across many areas, especially in logical reasoning, coding, and problem-solving. Many users find it faster and more accurate than some of the well-known commercial models.

Coding Tasks

In real-world coding tasks, DeepSeek is known to generate cleaner and more optimized code than other AI models that often overcomplicate solutions. Developers who use it for debugging also say it provides better error explanations, so you understand the problem rather than just getting a quick fix.

Math Problem Solving

Math problem solving is another area where DeepSeek does well. Unlike some AI models that rely on pattern recognition, DeepSeek uses logical reasoning to solve structured problems in algebra, calculus, and probability. This makes it a great tool for students, researchers, and finance professionals who need precise and accurate answers.

Long Interactions

Compared to ChatGPT and Gemini, DeepSeek also performs well in long conversations. Many AI models lose track of earlier context in long interactions, but DeepSeek keeps a better memory of previous conversations, so it’s good for summarization, research analysis and other multi-step tasks.

The Chinese AI model can be self-hosted, so businesses and developers don’t have to send their data to external servers. Perfect for companies with sensitive data or who want full control over their AI.

When Was DeepSeek Founded?

DeepSeek was founded in 2023, making it a relatively new player in the AI industry. Despite this, the company has grown quickly and launched multiple AI models that put it in the same league as the bigger players.

Instead of building the biggest or most complex models, DeepSeek has focused on efficiency, adaptability, and community-driven development, and that’s allowed it to move fast.

Initially, this DeepSeek AI didn’t get much global attention because Western companies dominated the AI space. But as more companies and developers are looking for affordable and customizable AI solutions, DeepSeek is becoming an attractive option. Businesses and developers who previously relied on proprietary models are now taking a closer look at what an open-source AI can offer, especially when it matches or beats existing solutions.

Who Owns DeepSeek?

With its recent explosion in popularity, you must be thinking who made DeepSeek, the Chinese AI app, or who is behind DeepSeek? We’ll get into that in this section.

DeepSeek was founded by Liang Wenfeng, a Chinese entrepreneur with a background in finance and artificial intelligence. Born in 1985 in Zhanjiang, Guangdong, he studied at Zhejiang University, where he developed a strong interest in machine learning and AI-driven technology.

Before moving into AI, he co-founded High-Flyer Quantitative Investment Management in 2015, a hedge fund that used AI to analyze stock market trends. The fund became highly successful, managing over $8 billion in assets. His experience in AI-powered financial models eventually led him to explore the potential of artificial intelligence beyond trading.

In 2023, Liang launched DeepSeek to develop powerful AI models that could compete with global leaders like OpenAI and Google DeepMind. But his approach was different—he wanted to make high-performance AI models open-source, allowing developers and businesses to use them freely. He also focused on making AI more efficient, reducing the high costs associated with training large models.

DeepSeek is headquartered in Hangzhou, China, and as of January 2025, it has a team of no more than 200 people, including researchers and engineers specializing in deep learning, reinforcement learning, and large-scale AI training.

Liang’s vision goes beyond just competing with Western AI models. He wants to position China as a major player in AI research and development, creating technology that is both cutting-edge and widely accessible.

Different Versions of DeepSeek

DeepSeek has been rolling out AI models since 2023, each one improving on the last and specializing in different areas.

Here’s a simple breakdown of their key releases:

What is DeepSeek V3?

DeepSeek-v3 marks a major milestone and helped the company gain some popularity in the global market. In essence, it is one of the most advanced AI models out there. It dropped in December 2024 and takes a big leap forward from its previous versions.

The model runs on a Mixture-of-Experts (MoE) system, which is a fancy way of saying it’s designed to be both powerful and efficient. It has a massive 671 billion parameters, but only 37 billion of them activate per token, so it doesn’t waste unnecessary computing power while still handling complex tasks.

One of the biggest things that makes DeepSeek-V3 stand out is how it was trained. The model processed a jaw-dropping 14.8 trillion high-quality tokens—basically, a ridiculous amount of data—using an FP8 mixed precision framework that helped speed things up while keeping costs lower.

It only took 2.788 million H800 GPU hours to finish training, which is pretty impressive considering how massive these AI models are. It also uses some clever techniques, like an auxiliary-loss-free strategy for smoother load balancing and Multi-Token Prediction (MTP) to make its responses more natural and context-aware.

One of the biggest upgrades? 128,000 tokens of context length. That means DeepSeek-V3 can handle super long conversations, analyze huge documents, and keep track of complex discussions better than most AI models out there.

What is DeepSeek R1?

DeepSeek R1 is a new AI reasoning model from the Chinese startup DeepSeek, launched in January 2025. It’s designed for complex problem-solving and logical reasoning, putting it in direct competition with models from companies like OpenAI.

What makes DeepSeek R1 stand out is its efficiency. Training AI models is typically expensive, with big tech companies spending hundreds of millions, but DeepSeek managed to train this one using 2,000 Nvidia GPUs at a total cost of about $5.6 million. That’s a lot less than what most companies invest in similar projects. The model uses the same Mixture of Experts (MoE) architecture as DeepSeek V3, which keeps it efficient, using only enough resources to complete a task.

DeepSeek R1 is also open-source under an MIT license, meaning anyone—whether researchers, developers, or businesses—can use, modify, and build on it freely. That sets it apart from many high-performance AI models, which often come with strict licensing and usage restrictions.

In terms of capabilities, DeepSeek R1 has performed well in evaluations. It scored 79.8% Pass@1 on the AIME 2024 benchmark, which measures AI reasoning and problem-solving skills, and 97.3% on the MATH-500 test, showing strong performance in complex math and coding tasks.

DeepSeek R1 highlights how AI development is evolving, with more companies prioritizing efficiency and open access. While it’s still early to say how widely it will be adopted, its combination of cost-effectiveness, strong reasoning ability, and open-source availability makes it a model worth watching.

In short, DeepSeek-R1 is built for a wide range of tasks, from solving technical problems to creating content and organizing complex workflows.

How to Use DeepSeek R1?

In this section, we’ll show you how to use DeepSeek R1.

Step 1: Go to DeepSeek.com or Download the App

It’s easy to get started with DeepSeek R1. For desktop users, search for DeepSeek using your preferred engine, or better still, use this direct link to jump straight in: https://chat.deepseek.com/

If you found the DeepSeek official site via search, you’ll be presented with two options. The first option is Start Now, and for desktop users, this will take you to the chat interface (if you used the link provided earlier, you’ll be on this page already).

The second option is Get DeepSeek App. This option reveals a QR code that you can scan that will take you to your respective app store based on your mobile operating system (iOS or Android).

Choose which one works best for you. We’ll choose Start Now and go into the chat interface.

Step 2: Toggle DeepSeek R1 in the Chatbox

Once you get to the chat page, you can type in your request. Note that you’ll be using the DeepSeek V3 model. To access DeepSeek R1, you need to click on the DeepThink (R1) button inside the chatbox.

If you want DeepSeek to search the internet when working on your response, click on the Search button inside the chatbox.

Step 3: Ask DeepSeek a Question

Once you’ve made your selections, you’re good to go. For this example, we’ll just enable DeepSeek R1. I started with something simple and asked the AI model to “Break down the tokenomics of Solana and evaluate its inflation/deflation model.”

As you can see the DeepSeek R1 model “thinks,” and you can see the thought process in the chat.

Now, let’s scroll down to the actual response. Right off the bat, the DeepSeek V3 model gives us a more complete breakdown of the token distribution, while the DeepSeek R1 model provides more concise information.

Now, this shouldn’t be a surprise since DeepSeek R1 was built to better reasoning for complex tasks, including software development, logical inference, mathematical problem-solving, and coding.

On the other hand, DeepSeek V3 is more of a general-purpose large language model (LLM) built for a wider range of tasks, from conversational AI to multilingual translation and information gathering.

In short, coders and developers should stick to DeepSeek R1, while DeepSeek V3 is more than enough for general, everyday users.

How Does DeepSeek Work?

The rise of Chinese tech startup DeepSeek is being called a Sputnik moment in AI, marking a shift in the global race for artificial intelligence dominance. Much like the Soviet Union’s unexpected leap in space technology during the Cold War, DeepSeek’s rapid progress has caught the attention of Wall Street, Silicon Valley, and policymakers in the White House.

As a serious ChatGPT competitor, DeepSeek challenges AI models like Google’s Gemini and those developed by OpenAI CEO Sam Altman.

DeepSeek’s strength lies in its efficient AI architecture, which reduces reliance on massive data centers and expensive computer chips. Unlike companies like Amazon Web Services and Microsoft CEO Satya Nadella’s AI initiatives, which depend on the latest high-powered hardware, DeepSeek has optimized its model to work with fewer resources while delivering similar capabilities. This efficiency has helped it gain recognition as an excellent AI advancement, even as the U.S. imposes export restrictions on advanced computer chips needed for AI training.

The White House has tightened export controls on AI technology, limiting China’s access to cutting-edge computer chips. Despite these challenges, DeepSeek has adapted by using alternative methods to train and optimize its model. Unlike Meta’s LLaMA, which is deeply integrated with Western cloud services, DeepSeek has designed its AI to operate more independently, avoiding reliance on U.S. data centers.

How Was DeepSeek Trained?

Unlike AI firms in Silicon Valley, which train their models using unlimited access to high-performance computer chips, DeepSeek had to work within the limits of export-controlled hardware.

DeepSeek was trained using a multi-stage process that included pretraining, context extension, supervised fine-tuning, and reinforcement learning.

First, the model was pre-trained on a massive multilingual corpus of 14.8 trillion tokens with a strong bias towards English and Chinese and mathematical and programming data.

This provided a foundation. Then, it extended its context length from 4,000 to 128,000 tokens using YaRN to be able to process and generate longer sequences. Supervised fine-tuning was done using 1.5 million samples covering reasoning tasks like math, programming, as well as logic and non-reasoning tasks like creative writing and simple question answering.

The reasoning data was generated by expert models, non-reasoning data was from a previous version of DeepSeek and was reviewed by humans. Reinforcement learning further refined the model’s reasoning abilities. Expert models trained on synthetic data generated by an internal version of DeepSeek, domain-specific and optimized through reflection and verification.

DeepSeek also used a technique called “distillation” where a new AI system learns from an existing one by looking at answers to questions. This allowed the model to be built quickly and cheaply, challenging the idea that top AI requires big budgets. Through this process, DeepSeek built a model that can compete with other top AI systems while being efficient and cost-effective.

DeepSeek’s ability to thrive under limitations proves that AI innovation isn’t just about having the most powerful computer chips—it’s about building smarter, more efficient models.

DeepSeek vs. ChatGPT & Other Rivals

The AI space is getting more competitive, with DeepSeek-R1 stepping up against big names like ChatGPT-4o, Claude 3.5 Sonnet, and Gemini 2.0.

While OpenAI, Anthropic, and Google dominate in the West, DeepSeek is China’s ambitious open-source alternative, offering affordability and accessibility. But is DeepSeek better than ChatGPT?

We compared the most popular models and added the information to the table below:

Open-Source vs. Proprietary Models

DeepSeek-R1 is the only open-source model in the group. This means developers and businesses can tweak and use it freely, unlike ChatGPT-4o, Claude 3.5, and Gemini 2.0, which are all closed-source and controlled by their respective companies. Open-source gives the model an edge for customization, but proprietary models often come with more refined performance and security.

Real-Time Web Search and File Handling

Access to live information is a big deal. DeepSeek-R1 has real-time web search with over 100 sources, making it the most robust in this area. ChatGPT-4o and Gemini 2.0 also support web search but in a more limited way, while Claude 3.5 doesn’t offer it at all.

For file uploads, DeepSeek-R1 and Gemini 2.0 allow 100MB files, which is significantly better than ChatGPT-4o’s 50MB and Claude 3.5’s 20MB limit.

Reasoning and Customization

All four models support advanced reasoning, making them great for complex problem-solving, but DeepSeek-R1 stands out with custom prompt templates, a feature the others don’t have. This makes DeepSeek more flexible for structured workflows, while ChatGPT-4o and Claude 3.5 are better for general AI reasoning and coding tasks. Gemini 2.0 is strong in multimodal understanding but lags behind in deeper reasoning.

Multimodal Capabilities (Text, Code, Images)

Each model handles text, code, and images, but with different strengths. ChatGPT-4o is the best for writing and coding, with Claude 3.5 excelling in long-form content and summaries. Gemini 2.0 leads in visual and multimodal tasks, making it ideal for Google-integrated use cases. DeepSeek-R1 covers all these areas but isn’t as polished in handling images and mixed media compared to GPT-4o and Gemini.

Cost and Market Accessibility

DeepSeek-R1 is the most budget-friendly option, developed on just $6 million, while OpenAI’s GPT-4 cost over $100 million to build. ChatGPT-4o, Claude 3.5, and Gemini 2.0 all require premium subscriptions to unlock their full potential. If affordability is your priority, DeepSeek-R1 is the best bet.

Training Hardware and Performance

The hardware behind these models affects their speed and efficiency. DeepSeek-R1 runs on Nvidia H800 GPUs, which are not as powerful as OpenAI’s H100 GPUs, but still deliver solid performance. Claude 3.5 is optimized for efficiency with AWS, while Gemini 2.0 uses Google’s TPU v5p for high-speed multimodal processing. ChatGPT-4o remains the most powerful overall, benefiting from top-tier computing resources.

Market Impact and Ethical Considerations

DeepSeek-R1’s launch has shaken the AI industry, especially in China, positioning itself as an alternative to U.S.-based AI models. Its open-source nature and affordability have drawn comparisons to a “Sputnik moment” in AI. However, a key drawback is its censorship policies, which align with Chinese government regulations and filter sensitive topics.

On the other hand, ChatGPT-4o, Claude 3.5, and Gemini 2.0 follow Western moderation rules, meaning they block misinformation, harmful content, and sensitive ethical discussions but don’t enforce government-driven censorship.

Which AI Model is the Best?

It all depends on what you need. If you want an open-source, cost-effective AI, DeepSeek-R1 is your best choice. For overall performance, ChatGPT-4o is still the strongest model. Claude 3.5 is great for writing, summaries, and reasoning, while Gemini 2.0 is perfect for Google users and multimodal tasks.

DeepSeek is a game-changer in affordability and open access, but it comes with content restrictions. If cost isn’t an issue, ChatGPT-4o still leads in raw capability, Claude 3.5 shines in structured writing, and Gemini 2.0 is a solid all-rounder with Google integration.

How Crypto Traders Can Use DeepSeek For Maximum Profit?

Crypto traders can use DeepSeek to help them make better decisions by analyzing vast amounts of market data in real-time, no more guesswork or manual research. Use AI to find profitable opportunities and manage risk. Whether it’s predicting market trends, automating trades, charting prices, or testing strategies before live, DeepSeek helps you refine your approach and get more profit.

Market Analysis and Trend Prediction

One of the biggest problems in crypto trading is spotting trends before they happen. DeepSeek processes high-frequency market data to detect subtle price movements before the rest of the market sees them. By analyzing historical price patterns alongside regulatory news, economic changes, and investor sentiment it helps traders predict what’s next.

For example, if an altcoin is about to go through a token unlock or a halving event, DeepSeek can analyze how similar events have affected prices in the past. Instead of manually comparing different cases, traders can let AI do the work, finding patterns that aren’t immediately visible. This allows them to position themselves before the market moves and profit from price swings others miss.

Automated Trading Strategies

Timing is everything in crypto trading, and DeepSeek—like a trading bot—can help by automating trading strategies. By integrating AI into algorithmic trading systems, traders can execute pre-defined strategies without constantly watching the market. This is especially useful in volatile conditions where reacting too late can mean missing a trade.

AI-powered trading systems can adjust their strategy on the fly, responding to sudden price spikes, changes in liquidity, and changes in market momentum. For example, if a trader follows a momentum strategy, DeepSeek can detect when a price breakout is supported by real market participation.

Instead of using static thresholds, it dynamically adjusts entry and exit points based on live order book data. This makes trades more efficient and reduces the chance of getting caught in false breakouts.

Technical and Fundamental Analysis

DeepSeek doesn’t just look at price charts. It also digs deeper into the market by analyzing on-chain activity, large wallet movements, staking trends, and liquidity shifts. This kind of insight helps traders separate hype-driven price pumps from real market trends.

For example, if a token’s price is going up, DeepSeek can track if the increase is driven by organic demand or large whale accumulation. This helps traders avoid getting into risky trades based on hype and instead focus on opportunities backed by real market strength.

Backtesting & Strategy Refinement

No strategy is perfect; that’s why backtesting is so important. Traders can use DeepSeek to simulate different market scenarios to see how their strategy would have performed in the past. This helps identify weaknesses, adjust risk, and fine-tune a strategy before putting real money on the line.

A swing trader, for example, might use DeepSeek to test different stop-loss and take-profit levels under past market conditions. Instead of guessing what works best, let the AI analyze the data and suggest the optimal settings. This removes the uncertainty and helps build a more systematic and consistent approach.

Does DeepSeek Know About Crypto?

We wanted to test out DeepSeek’s knowledge, so first, we tried something simple by asking “What is the price of Bitcoin (BTC) today?” Unfortunately, by default, DeepSeek V3 and R1 don’t have internet access enabled.

However, you can fix this by clicking on the Search button next to the DeepThink (R1) button inside the chatbox input. Annoyingly, there was another roadblock, when we tried to get DeepSeek to give us live data on Bitcoin’s price with internet search enabled—the search service was “busy.”

Now, this wasn’t a surprise since DeepSeek has exploded in popularity and is even ranked #1 in the Apple App Store for AI apps. This was one of the many attempts over several hours, so it was disappointing. Hopefully, this is a temporary problem since live data is very powerful for any crypto-related use cases with AI.

Next, we tested DeepSeek on some recent crypto trivia, this time asking the AI model if it knew when the Trump memecoin was released. In response, we were told about the MAGA memecoin that was released in 2023.

We clarified my question and told the AI model we are asking about the official Trump memecoin, released by President Donald Trump himself, that blew up recently on social media. We were then hit with some interesting information.

It turns out that DeepSeek has a knowledge cutoff set at October 2023, so if you have questions about any events that took place after that date, you need to enable Search. However, at the time of testing, the search service was too busy, so we stopped trying to test DeepSeek’s knowledge here.

If you want recent or live information or information on any events that took place after October 2023, you need internet access, and the service needs to be available.

Apart from that, DeepSeek’s knowledge on crypto (before October 2023) seems to be very accurate. We questioned the AI model on the FTX collapse and got accurate information, including the month and year of the collapse (November 2022) as well as a timeline and the factors contributing to FTX’s downfall, all available in the screenshots below:

As you can see, DeepSeek gave us a detailed timeline, citing news reports as sources for information, as well as accurate dates, with each date on the timeline being correct and corresponding to the event outlined.

Above you can see the reasons for the collapse of FTX provided by DeepSeek. We were also told about the consequences and aftermath of the events.

All in all, DeepSeek has a good knowledge of the crypto industry. We tested the AI model again by asking it about ZachXBT, CoffeeZilla, and Ansem, to which we were again given correct and accurate information, including their Twitter (X.com) handles and standout events in their careers.

DeepSeek’s Crypto Market Prediction for 2025

We wanted to get some crypto predictions from DeepSeek, so I asked for its input on where it believes Bitcoin, Ethereum, Solana, and Dogecoin could be later this year.

Again, the internet search is still down, and the AI model even reminded me of the knowledge cutoff.

Regardless, DeepSeek trading advice gave me predictions, as well as what DeepSeek believes to be the potential drivers of the anticipated price action. The information has been organized into a table so you can get the gist of it without getting buried in the details.

Please note that this is not financial advice, rather hypothetical predictions from an open-source AI chatbot, so don’t remortgage your house yet.

DeepSeek gave an informative breakdown on the potential price performance, noting Ethereum’s improved stability, speculation about DOGE being used for payments on X.com, and more. It’s not bad for generative AI that most people learned about only last week.

Market’s Reaction to DeepSeek

DeepSeek’s recent release of the V3 and R1 models has caused a stir in the tech industry. After the release of its latest AI model, DeepSeek-R1, major U.S. tech stocks tanked, with Nvidia, Microsoft, and Tesla losing a combined $1 trillion in market value.

Nvidia suffered a historic 17% drop, the largest single-day decline in its history. Investors are clearly worried that a cheap and powerful Chinese AI model could disrupt the U.S. companies that have spent billions on AI research.

In a Q&A with The Pennsylvania State University (PSU), Akhil Kumar, a professor of supply chain and information systems, explained that DeepSeek could “drive down the demand for Nvidia and other specialized chips.” He broke down his reasoning saying, “some 10 times more efficient than current products and needs fewer chips—2,000 compared to 16,000 for its competitors.”

Harvard Business Review (HBR) also expressed similar views towards DeepSeek being more efficient due to lower costs. HBR explained that Chinese AI models, including DeepSeek, differ from their American counterparts in two key ways: they rely on cheaper hardware and open-source architectures to lower costs, and they are often tailored for domain-specific applications rather than broad, general-purpose tasks.

Twitter Reactions: Memes, Jokes, and Pure Shock

In addition to this, social media has been buzzing ever since DeepSeek burst onto the AI scene, and reactions have been all over the place. Some people are in awe, some are skeptical, and others, just having fun with memes.

On Twitter, a lot of people are reacting with disbelief that DeepSeek, a relatively unknown Chinese AI company, could build something as powerful as ChatGPT for just $5 million. A viral tweet from @litcapital jokes that DeepSeek’s CTO could clone OpenAI’s entire $500 billion AI model in just two weeks with a tiny budget.

“OpenAI huh? $500B? Gimme 2 weeks and $5 million and I’ll clone it asap” – DeepSeek’s CTO pic.twitter.com/yvV4QmkEU0

— litquidity (@litcapital) January 27, 2025

The meme, featuring a still from the show Silicon Valley, sums up how ridiculous this situation seems—how did a startup with no big reputation manage to rival OpenAI and Google?

Another tweet from @naiivememe adds to the humor, showing a video of people going crazy at a party with the caption: “DeepSeek engineers getting a $5K bonus after wiping out $1 trillion in the market.”

Deepseek engineers getting a $5K bonus after wiping out $1 trillion in the market pic.twitter.com/OjjKIokDwx

— naiive (@naiivememe) January 28, 2025

This refers to how DeepSeek’s rise caused a major crash in tech stocks, including Nvidia, Microsoft, and Tesla. The tweet plays into the idea that DeepSeek engineers pulled off one of the biggest upsets in AI history, completely blindsiding Silicon Valley.

Meanwhile, @QwQiao compares DeepSeek’s breakthrough to an unknown team building a blockchain 100x faster and cheaper than Solana with just $500K in funding.

imagine an unknown team came out of nowhere n built a blockchain 100x faster cheaper than solana with $500k funding

this is how silicon valley is reacting to deepseek right now

— qw (@QwQiao) January 26, 2025

The message is clear—DeepSeek came out of nowhere and is suddenly a serious threat to major AI companies.

DeepSeek’s success has also spawned some negative think pieces on the AI industry in general. A tweet from @SilverSpookGuy suggests that DeepSeek’s success proves GenAI companies are overhyped, implying that AI startups like OpenAI and Google DeepMind are inflating their costs and that building powerful AI models might not require billions of dollars.

Reddit’s Take: Did DeepSeek Play the Market?

On Reddit, the conversation is more intense. A post in r/options suggests that DeepSeek’s co-founder, Liang Wenfeng, may have used the company’s AI announcement to trigger a stock market crash—one that his hedge fund, High-Flyer, could have profited from.

According to the post, DeepSeek’s announcement wiped out $600 billion from Nvidia and other AI stocks. Given that High-Flyer specializes in AI-driven trading, some users are speculating that this was more than just a coincidence.

If DeepSeek’s claims about building a top-tier AI model for just $5.5 million and 2,048 GPUs are exaggerated (or even fake), then this could have been a strategic move to cause market panic and profit from it.

International Backlash Against DeepSeek

DeepSeek has gone from zero to hero in a short time, but its rapid growth has also attracted enough criticism from governments, security agencies, and the tech industry. While the company is positioning itself as an AI giant, concerns over data security, national security risks, and market disruption have put it under the spotlight.

In Taiwan, the Ministry of Digital Affairs has advised government departments not to use DeepSeek AI services because sensitive data could be compromised. Since DeepSeek is a Chinese company, officials worry that data processed through the platform could be accessible to the Beijing authorities. This is a broader concern for regions that are wary of China’s influence in the tech space.

Taiwan’s Ministry of Digital Affairs expressed its concerns over potential “information security risks” according to Reuters. “DeepSeek’s AI service is a Chinese product, and its operation involves the cross-border transmission and information leakage and other information security concerns and is a product that jeopardizes the country’s information security,” the ministry said.

Italy has gone even further and has blocked DeepSeek’s app altogether. The country’s data protection authority launched an investigation after DeepSeek failed to provide information on the data used to train its models.

With data protection laws getting stricter in the European Union, companies operating in AI must prove they are handling user data responsibly — something DeepSeek has not done to the satisfaction of the regulators.

According to a report by Politico.eu, DeepSeek apparently told the authorities it wouldn’t cooperate with a request for information made by Italy’s data protection authority.

In the United States, DeepSeek’s explosive growth has raised alarm bells at the highest level. The U.S. Navy has officially banned its personnel from using the AI model, citing security and ethical concerns. The White House is also assessing the risks posed by DeepSeek’s technology, particularly the possibility that the Chinese government could use it for intelligence gathering or influence operations.

With the growing tensions between the U.S. and China over AI leadership, DeepSeek’s emergence has only added to the debate over foreign AI systems gaining traction in Western markets.

On top of all this, the tech industry is also raising questions about DeepSeek’s practices. Critics are saying that its data collection methods are unclear; user data is stored on servers in China, which raises privacy concerns.

Engineering and Technology Magazine (E+T Magazine) reported that OpenAI is reviewing evidence that DeepSeek used a technique known as ‘distillation’ from OpenAI’s ChatGPT to build its rival model. If proven, this will add to the legal woes of the company. Despite these concerns, DeepSeek has managed to maintain its popularity, so only time will tell how everything plays out in the long term.

Future of AI After DeepSeek

DeepSeek has shaken up the AI world, quickly becoming one of the top AI models in the United States and even surpassing ChatGPT on Apple’s App Store. This sudden rise has many wondering if China’s latest AI breakthrough is a challenge to U.S. dominance in AI.

What makes DeepSeek stand out is its efficiency. Unlike OpenAI’s ChatGPT or Google’s Gemini, which require massive data centers and cutting-edge computer chips, DeepSeek was developed at a fraction of the cost using far fewer resources.

This proves that advanced AI models don’t always need billions of dollars and endless computing power to compete. Instead, DeepSeek’s approach suggests a shift toward more cost-effective and accessible AI, which could be a game-changer in the industry.

The success of DeepSeek raises big questions about the future of AI. For a long time, Silicon Valley has led the way, but now China is proving it can build world-class AI systems that rival the best.

This shift isn’t just about competition—it also brings up concerns about national security, data privacy, and AI regulations, especially as AI becomes more powerful and widely used. The White House and other U.S. policymakers are already paying attention, as the rise of DeepSeek highlights how quickly the global AI landscape is changing.

Will DeepSeek overtake ChatGPT and similar models? It’s too soon to say for sure, but it has already made a huge impact. Its rapid growth and innovative approach show that AI leadership isn’t set in stone, and companies that focus on efficiency and adaptability may have the edge in the long run. The future of AI will be more competitive than ever, and the U.S. no longer has an unquestioned lead.

Conclusion: What is DeepSeek?

DeepSeek has quickly made a name for itself in the AI space with the release of its open-source R1 model. What got people talking is how it can compete with U.S. top models—on a fraction of the budget. It proves high-level AI isn’t limited to the likes of OpenAI and Google.

Looking forward, the Chinese AI development is working on making its models more efficient. One of the techniques it’s exploring is called the “mixture of experts”, which means the AI only uses the necessary computing power for a task rather than running everything at full capacity all the time. This could make DeepSeek’s AI faster, cheaper, and more scalable.

Another big focus is keeping DeepSeek open-source. By allowing developers worldwide to contribute and build on its tech, the company is building a more collaborative AI ecosystem. This makes AI more accessible and speeds up innovation as more minds work together to refine and expand what the model can do. Seek deep on DeepSeek!

See also:

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3. What is Worldcoin? A Beginner’s Guide to WLD Tokens

References

• Hugging Face. “DeepSeek-V3.” Hugging Face, https://huggingface.co/deepseek-ai/DeepSeek-V3.
• IBM Research. “AI Inference Explained.” IBM Research, https://research.ibm.com/blog/AI-inference-explained.
• Cybernews. “New Chinese AI Model Claims to Outperform Top Dogs.” Cybernews, https://cybernews.com/security/new-chinese-ai-model-claims-to-outperform-top-dogs/.
• Reddit. “DeepSeek V3 Performs Surprisingly Bad in Testing.” Reddit, https://www.reddit.com/r/LocalLLaMA/comments/1hpjhm0/deepseek_v3_performs_surprisingly_bad_in/.
• Amity Solutions. “DeepSeek-R1: AI Giant from China.” Amity Solutions, https://www.amitysolutions.com/blog/deepseek-r1-ai-giant-from-china.
• New York Post. “Nvidia Shares Fall 12% as Chinese AI Startup DeepSeek Triggers Panic.” New York Post, https://nypost.com/2025/01/27/business/nvidia-shares-fall-12-as-chinese-ai-startup-deepseek-triggers-panic/.
• New York Post. “Nvidia Stock Set for Record Wipeout on DeepSeek Fears; CEO Jensen Huang’s Net Worth Tanks.” New York Post, https://nypost.com/2025/01/27/business/nvidia-stock-set-for-record-wipeout-on-deepseek-fears-ceo-jensen-huangs-net-worth-tanks/.