DeepSeek: Next Big Thing or Just a Fading Trend?
Yet again, China made it into the headlines, not for a deadly virus or Tiktok, but for an AI model that challenges OpenAI’s dominance (China has mastered the art of trending!). The Chinese artificial intelligence company’s large language model was important in offering cost-effective AI assistance. Built up in a fraction of OpenAI’s budget and much fewer chips, DeepSeek has become a leading chatbot.?
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The AI startup released DeepSeek at the beginning of 2025, and the tech geeks quickly analyzed the tool to give it a 5-star rating. Observing how DeepSeek has recently appeared everywhere on our social media feeds is amazing. Being the “talk of the world,” not just the town, it gained overnight popularity by claiming the 1st position in Apple’s App Store.?
The sudden rise in fame of DeepSeek, tagging itself as an ‘Intelligent AI assistant”, has sent shockwaves in the global tech market. Needless to say, it’s currently causing a mixture of concern and enthusiasm in the sector. Some see it as a groundbreaking discovery. Others are becoming quite concerned about it, further supported by the significant decline in most of NASDAQ’s tech stocks on January 27.??
Regardless of how the news and excitement cycle changes in the upcoming weeks and months, we have covered the ups and downs of DeepSeek to help tech enthusiasts and business leaders get a sense of what a progression in AI currently refers to.?
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What is DeepSeek AI?
DeepSeek is an AI development company headquartered in Hangzhou, China. It focused on creating open-source LLMs. The company’s initial model was published in November 2023, and it has iterated numerous times on its main LLM, developing several distinct varieties.??
Liang Wenfeng, a seasoned businessman who also manages the hedge fund High-Flyer, created the Hangzhou-based DeepSeek in late 2023. Although not well-known outside of China, Liang has a long history of fusing investing with emerging technologies.?
However, it was not until January 2025, following the introduction of its R1 reasoning model, that the business gained global recognition.?
Key Features of DeepSeek AI
Open-Source Technology
DeepSeek differentiates because it employs open-source technology. Its AI models, including the latest releases, DeepSeek-V3 and DeepSeek-R1, are open-source, allowing developers and researchers to collaborate and make improvements within the AI community. Open-source models can result in faster breakthroughs since users offer enhancements and changes.?
Cost-Efficiency
The DeepSeek development strategy prioritizes cost-effectiveness. The company claims that it built the models for one-tenth of the cost that competitor giant OpenAI charged. While OpenAI is said to have invested billions of dollars in the model, DeepSeek only spent less than $6 million to create the most recent version. This raises the problem of price sustainability in AI and highlights emerging enterprises that may alter the entire picture compared to a high-price model due to low-cost techniques.?
Performance Capabilities
DeepSeek AI models are optimized for complex reasoning performance. According to reports, DeepSeek-V3 outperforms other mathematics, programming, and natural language processing models.??
Strategic Developments Even With Restrictions
Many AI companies have encountered geopolitical issues, particularly those relying on US vendor’s high-end technology. DeepSeek has responded to US sanctions that limit access to high-performance CPUs like Nvidia’s A100 series by mixing them with less-priced options. This flexibility has enabled the company to develop powerful AI solutions without relying too heavily on expensive technologies.?
DeepSeek’s Interesting Approaches
DeepSeek trains its R1 model differently from the strategy used by OpenAI. AI accelerators were required to spend less time and money to attain artificial general intelligence. The company advanced reasoning capabilities that became the key steps forward in AI development.?
DeepSeek employed a large-scale reinforcement learning strategy aimed at reasoning challenges.?
AI solves problems step by step, like how humans think, making answers more accurate and reliable.?
Reward engineering is developing an incentive structure to guide an AI model’s learning during training. Researchers created a rule-based reward system for the model, which outperformed more commonly used neural reward models.??
DeepSeek researchers used efficient knowledge transfer approaches to efficiently compress capabilities into models with as little as 1.5 billion parameters.?
DeepSeek’s emergent behavior breakthrough reveals that complicated reasoning patterns can emerge organically from reinforcement learning without being actively programmed.?
AI learns better by simultaneously improving multiple responses, making it faster and more efficient.?
DeepSeek has adopted the MoE (mixture-of-experts) paradigm to achieve a 20x calculation reduction utilizing only 37 billion parameters out of 671 billion.??
It is particularly unique for the literature-savvy since it has moved away from the conventional fine-tuning techniques and brute-force pre-training. Instead, it chose to employ a carefully selected combination of multiple methodologies, the purposeful strategy of which was made clear when choosing the training objectives and data.??
If there is one thing that all experts appreciate about it, it is the tremendous amount of work that goes into training foundation models.?
All in all, the implications are as follows (which many in the AI community know about):??
DeepSeek substantially supports the long-held notion that more intelligent implementations can outperform AI algorithms by an order of magnitude.??
These strategies remain critical to achieving significant improvements over other ways.?
Synthetic data production is the key to outperforming benchmark accuracy in basic models.?
The Global AI Battle: Challenge to OpenAInbsp;
In 2020, OpenAI launched ChatGPT, which went on with a storm with mixed reactions but eventually got accepted. The technological marvel, which has over $13 billion in funding, received massive adoption, corporate integrations, and even regulatory scrutiny as it reshaped the AI landscape.?
But suddenly, in 2025, all of the funding and processing power that Elon Musk, Mark Zuckerberg, and Sam Altman have been claiming are essential to their AI projects and, thus, to America’s sustained dominance in the field could be greatly exaggerated.??
With DeepSeek’s entrance into the market with only $6 million of investment and 2000 Nvidia chips (due to export restrictions), it has grown more efficient and capable than ChatGPT; instead, according to Sam Altman, more than $100 million as the cost to build ChatGPT-4.??
After investors in the US and Europe became alarmed by the growing popularity of DeepSeek, the US tech firm Nvidia lost more than a sixth of its value. It suffered the largest one-day market cap loss in history, shedding nearly $600 billion in value.?
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ChatGPT’s Reign in Question: Is the Era of OpenAI Ending?
DeepSeek was released when OpenAI announced the $500 billion Stargate project, a partnership to rally resources for data centers, chips, and power required for AI growth. Ironically, DeepSeek’s breakthrough proved that massive investments into AI infrastructures might be unnecessary, throwing all of OpenAI’s claims into doubt.??
Now, the doors to investment may be closing; as such, investors may be wary of continuing to pump billions into AI companies, lacking a credible route to efficiency. It will become more interesting whether OpenAI will change course or double down on what they are doing today.?
However, OpenAI’s engineers are probably not afraid because an open-source model cannot keep pace with the speed at which it updates its models based on millions of implicit and explicit feedback signals.?
ChatGPT has maintained its lead primarily due to its widespread use. Their operational costs may also not be as high as reported. They’re already on the same level as DeepSeek or even cheaper.??
Given how frequently queries are repeated, it’s difficult to think they don’t use cache for many responses. Closed-source models are more than just simple AI models; they are complete systems, and caching is an apparent approach to significantly cut inference costs for real users.?
A fitting example can be taken from Google. There were many advanced search engines then, but once Google achieved a certain usage level, the others became history. The more pertinent question is how much, and at what pace, DeepSeek will continue to improve — that will decide if they can even become a serious competitor.?
When does an AI model care about the cost of training? All the user wants is a functioning chatbot.???
In other words, AI is not dead. However, the situation is evolving quicker than anyone predicted.?
Will DeepSeek Make AI More Affordable?
DeepSeek-R1 has several smaller distilled sizes and can run on commodity hardware. The importance of running a model anywhere that performs like ChatGPT instead of being chained by third-party API costs cannot be emphasized enough, especially if you are trying to explore advanced areas of AI, which may require multiple cycles to deliver a solution.?
It is tough to ascertain the heavy price difference. Still, DeepSeek’s hardware is 20-50 times cheaper than OpenAI’s (which some industry voices challenged, but strong evidence supports the claims). If that assumption remains true, it should effectively reduce AI costs for the business: the foundational model itself is cheaper to train, plus using and running it and integrating it with an application is cheaper.?
However, this is a mere assumption; many questions remain. For example, one would speculate whether DeepSeek is implementing trade-offs regarding its cheaper infrastructure, which is the opposite of what is now known.??
Even more reverberating in your mind will be the Jevons Paradox: where any efficiencies, rather than leading to lower prices as you would expect, create a demand that outstrips the ability of any price drop to offset. This is more complex than would seem on the surface.?
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Will DeepSeek Reduce Energy Consumption?
The models developed by DeepSeek indicate that it is possible to achieve grand performance levels without needing as much electricity as conventional models require. Several power companies took a share-price hit. However, one possible good effect of this is to drive a green computing agenda that addresses computing’s environmental impacts through efficiency.?
What this means for OpenAI and Google remains in limbo. The companies have sandbagged huge sums of investment in data centers and resources for the years to come; if DeepSeek has shown that less can be more, then the companies may pivot. That’s merely conjecture; to the discredit of all, DeepSeek is forcing the industry to reevaluate how much energy is needed to build an operational AI system?
Market Reaction Due to Competitive Threat
It’s only a matter of time until people realize that AI may be considerably cheaper than previously thought. The focus had previously been on model cost, but it has become evident that prioritizing capabilities over architecture can result in 10-100 times more efficient systems.?
This is excellent news for AI users, as costs are projected to fall dramatically. However, if your AI expenses remain high, this is most likely due to a lack of investment in alternative, more efficient AI.??
AI optimization will likely become the next major emphasis, particularly for firms that have invested extensively in AI, given that the potential for considerable cost savings has been publicly recognized.?
Some market reaction on the rising splurge of DeepSeek AI at a glance.?
Tech Stocks Feels the Pressure:
The debut of DeepSeek has produced waves in the stock market, particularly among AI-focused firms. Investors now wonder whether OpenAI and other IT behemoths can continue their dominance or if DeepSeek can take a sizable portion of the industry. Some AI-related stocks have experienced small losses as competition heats up.?
Investors are Watching Closely:
DeepSeek’s lower-cost AI strategy has raised questions about the viability of more expensive AI services. Investors are now questioning if companies like OpenAI will be forced to decrease their prices, impacting revenue. Some investors are delighted about the competition, while others are concerned that it could lead to instability in the AI business.?
Good for Startup Enterprises:
DeepSeek could be the game-changer for those who have been ready to embrace AI but have been held back by the hefty expenses. Consider a future in which you don’t need to spend millions of dollars to train and run AI agents, don’t need highly complex gear, and don’t require massive, AI-skilled teams.??
Many AI businesses that formerly intended to compete with ChatGPT are now battling to distinguish themselves. With DeepSeek providing a cheaper option, smaller AI companies may need to adapt their tactics, cut costs, or focus on specific industries to survive. Some entrepreneurs are already exploring new ways to stand in this quickly changing industry.?
What will OpenAI Do Next?:
With powerful competition like DeepSeek, experts are speculating how OpenAI may react.??
The Internet is still divided about which model outperforms the others. The early test results indicate that DeepSeek R1 has an edge over the competing models in some testing benchmarks. The industry is looking forward to seeing OpenAI’s next move.?
OpenAI CEO Sam Altman called his post on X “legit invigorating to have a new competitor” and found the DeepSeek R1 to be “an impressive model, particularly around what they’re able to deliver for the price.” He promised that this would motivate OpenAI to accelerate some of its releases.?
Days later, after the frenzy surrounding the Chinese upstart DeepSeek cast fresh doubt on AI funding, OpenAI Chief Executive Sam Altman briefed U.S. policymakers on why heavy physical infrastructure investments are necessary for future AI developments.??
Altman and his guests provided teasers about advances in OpenAI products. They shared visions about how AI developers are evolving to provide services that can “do increasing complex tasks for you.” However, as companies build more sophisticated products, he said, “We will need much more compute” to grow the AI models further and support an expansive user base.??
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Pros and Cons of DeepSeek
AI was already evolving, and with the entrance of DeepSeek AI as a strong competitor, there was a paradigm shift. Unlike expensive Western AI models, DeepSeek provides a low-cost, high-performance alternative that has the potential to disrupt the market. Here’s why corporations and developers care:?
Prosnbsp;
AI That Is Powerful Yet Affordable:?
Most AI models today require enormous funding, making them expensive to build and use. DeepSeek, however, has managed to develop high-quality AI models at a fraction of the cost.?
Strong in Reasoning and Problem-Solving:?
DeepSeek’s AI, especially its DeepSeek-R1 model, has been praised for its logical reasoning skills.?
Open-Source and Developer Friendly:?
Unlike many AI companies that keep their technology proprietary, DeepSeek encourages open-source research.?
Designed For a Global Audience:?
DeepSeek is created with excellent support for both Chinese and English, making it effective in various marketplaces.?
A New Competitive Force in AI:?
DeepSeek’s progress threatens the supremacy of Western AI firms such as OpenAI, Google DeepMind, and Anthropic.?
Cons
While DeepSeek is making waves in AI, it’s not perfect. Here are some challenges businesses should consider before adopting it:?
Limited Tools and Integrations
Unlike OpenAI and Google, DeepSeek does not currently provide diverse third-party app integrations or development tools. Organizations may need to put more effort into customizing and deploying DeepSeek AI to meet their needs. However, if the platform expands, these functions may improve over time.?
Uncertain Future Support and Updates
DeepSeek is a very new player in the AI market, so no one knows how frequently it will issue updates or how long it will be supported. Businesses that rely on long-term AI solutions may be hesitant to convert unless DeepSeek demonstrates its stability and dedication to continuous improvement.?
Challenges in Non-Chinese Markets
DeepSeek is based in China, which raises concerns regarding accessibility and possible restrictions for overseas users. Government laws or restrictions may limit its availability in certain countries. Companies outside of China should monitor how DeepSeek manages global expansion.?
Less Computing Power Compared to Bigger AI Companies
DeepSeek is intended to be efficient, yet it lacks the raw computer power of giants like OpenAI, Google, and Meta. This could result in slower advances and a smaller dataset to train on, thus restricting its capacity to compete with the most powerful AI models in speed and size.?
Adoption Hesitation from Businesses
Because OpenAi’s ChatGPT is already well-established, many businesses may hesitate to transition to a different AI program. They can be concerned about compatibility, customer trust, or whether Deepseek will be competitive in the long run. Overcoming this hesitation will challenge DeepSeek as it seeks market share.?
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Conclusion
DeepSeek, with its cost-efficient approach, open-source philosophy, and strong reasoning capabilities, has positioned itself as a real contender in the AI space.?
However, as a newcomer, it still faces challenges competing with tech giants like OpenAI and Google, requiring continuous improvements, strategic partnerships, and a clear roadmap for expansion.?
The future of DeepSeek depends on how well it adapts to market demands and scales its operations. If it continues refining its models while maintaining affordability, it could redefine AI development and force the industry to rethink its approach. Whether it remains a competitor or eventually collaborates with larger players, one thing is clear: DeepSeek has made an impact, and the AI race has just become more interesting.?