AI advancements are accelerating at a rapid pace, and DeepSeek AI is making waves as a potential challenger to established giants like OpenAI. Recently, DeepSeek’s revolutionary AI model has generated significant attention for its ability to deliver a high level of performance at a fraction of the cost. But what does this mean for businesses, the AI industry, and the future of artificial intelligence? Let’s look at DeepSeek AI, its potential impact, and why its emergence could reshape the way businesses think about AI.
What is DeepSeek AI?
DeepSeek is a new AI player that has captured attention for its remarkable ability to create powerful artificial intelligence models, all at what it claims is a fraction of the cost required by competitors like OpenAI. While OpenAI has historically been the gold standard for AI models like GPT-3 and GPT-4, DeepSeek has emerged with a compelling alternative that offers cost-effective and efficient solutions. Since its release in January, it has become the number 1 downloaded Apple App, surpassing ChatGPT.
DeepSeek claims it has created an AI model for just $6 million—a stark contrast to the hundreds of millions spent by OpenAI and Meta on similar technologies.
If these numbers alone don’t cause widespread suspicion, the affect it had on the market might.
The Claims vs The facts
According to an article published on January 31st of this year by Yahoo News, DeepSeek’s low training cost figures could have been grossly under-reported. Citing a third-party report by SemiAnalysis, it says:
“The $6 million estimate primarily considers GPU pre-training expenses, neglecting the significant investments in research and development, infrastructure, and other essential costs accruing to the company.” The article goes on to say, “The report highlights that DeepSeek’s total server capital expenditure (CapEx) amounts to an astonishing $1.3 billion.”
Another article, published by Forbes on January 27th titled, “What Is DeepSeek? New Chinese AI Startup Rivals OpenAI—And Claims It’s Far Cheaper,” addressed the sudden affect DeepSeek’s popularity has had on the market. It reports that NVIDIA stocks were down 17%, along with Microsoft (down 3.7%), Tesla (down 1.3%), and Broadcome (down 16%). This, it says was a direct result of a, “selloff spurred by DeepSeek’s success, and the tech-heavy Nasdaq was down 3.5% on the way to its third-worst day of the last two years.”
Berestein analyst Stacey Rasgon calls the claim that it only cost $6 Million to develop “highly misleading,” saying further that, “Did DeepSeek really ‘build OpenAI for $5M?’ Of course not.” (Source.)
So for all the popularity and even performance, the cost for development claims have had a huge impact on the market–perhaps unfairly, however, the cost savings to users is significant given the efficiency of operation.
Claims About Efficiency
The difference between DeepSeek and its competitors doesn’t stop with dev cost claims. DeepSeek’s model is reported to be 20 to 50 times more efficient than its competitors.
The efficiency is tied into the number of GPUs required to train and run what Rasgon calls a “mixture-of-experts” model that doesn’t require the compute capabilities of larger, established ones. The need to run on fewer GPU clusters is also due to US export regulations. This efficiency of operation and less cost for development both owe to the fact that they were built using established technologies. The paper that made the claims about the low cost for development, according to Rasgon, “…did not quantify the additional resources that were required to develop the R1 model (presumably they were substantial as well).”
For users, this efficiency isn’t just about performance—it also means businesses and individuals can access state-of-the-art AI capabilities without the massive overhead costs traditionally associated with AI development (whether development costs were exaggerated or not). With DeepSeek, the AI world becomes more accessible, offering companies of all sizes the opportunity to tap into AI’s power without breaking the bank.
The DeepSeek OpenAI Competition: How Do They Compare?
DeepSeek AI is not just another alternative in the growing list of OpenAI competitors—it is a true contender. OpenAI has set the standard in the AI industry, but DeepSeek’s model is challenging that dominance by offering a significantly more efficient and cost-effective solution.
- DeepSeek Model Efficiency vs. GPT: One of the most notable features of DeepSeek is its ability to provide more efficient results at a lower cost. While OpenAI’s models like GPT-3 and GPT-4 are widely used, they come with high infrastructure costs and resource demands. DeepSeek’s ability to deliver a comparable (if not superior) performance at a fraction of the cost could be a game-changer, particularly for small businesses or startups that want to incorporate AI without committing to large-scale investments.
- DeepSeek’s Open-Source Approach: Unlike some AI models that are locked behind proprietary systems, DeepSeek is open-source. This means that anyone can access and modify the model to suit their needs. This open-source nature aligns with the growing trend of democratizing AI—making it available not just to the large enterprises, but to individuals and small businesses as well.
- DeepSeek vs. GPT: The Cost Factor: The massive price difference between DeepSeek and OpenAI’s offerings cannot be ignored. While OpenAI requires extensive infrastructure and investments to run its models effectively, DeepSeek provides a much more affordable solution that still delivers high-quality results. The cost savings—potentially up to 10x—could significantly impact companies’ bottom lines and allow for more innovation across industries.
The Impact on the AI Landscape
- NVIDIA Stock Drop: The introduction of DeepSeek has had ripple effects across the AI industry. NVIDIA, a leader in hardware for AI training, saw its stock drop 17% in a single day following the announcement of DeepSeek’s efficiency and cost-effectiveness. Why? Because the need for expensive, high-end hardware may diminish if AI models like DeepSeek can run efficiently on less powerful machines. This could alter the market dynamics for hardware companies that rely on the high demand for GPUs to power AI systems.
- A Level Playing Field for Small Companies: The arrival of DeepSeek means that small companies now have access to powerful AI technology that was previously out of reach due to the high costs associated with AI model development. With the democratization of AI, smaller businesses can now compete with larger tech giants, reducing the competitive gap and fostering innovation across the board.
- Redefining AI Architecture: The rise of multi-LLM (Large Language Model) flexibility is a key factor in the DeepSeek revolution. Many businesses are still locked into single AI providers like OpenAI, which limits their ability to adapt to the evolving landscape of AI. DeepSeek advocates for building flexibility into AI architectures, enabling businesses to switch between models and utilize a variety of AI tools. This shift could reshape the way tech stacks are built in the AI age.
What Will Happen to Established Hardware Companies?
With the market hits chip producers experienced, some are wondering whether their stocks will recover and what kind of GPU and compute needs will follow the new DeepSeek technology. Some analysts predict a rising need for compute and semiconductors, citing what is called the Jevons paradox which asserts that gains in efficiency can also increase the demand for a given resource. Said TD Cowen’s Joshua Bchalter:
“Rather than lead to less consumption of accelerated hardware, we believe this Jevons Paradox dynamic should in fact lead to more consumption and proliferation of compute resources as more impactful use cases continue to be unlocked.”
Established companies will be able to grow and scale while cheaper alternatives that might run more efficiently, won’t be able to scale due to their inability to acquire the GPUs needed for increased AI applications and need.
The Need for Flexibility in AI Architecture
One of the main takeaways from the DeepSeek revolution is the importance of flexibility in AI architecture. Traditional tech stacks have often relied on a single AI provider, but as AI costs drop and more efficient models like DeepSeek emerge, businesses need to reconsider this approach. Here’s why:
- AI is Changing Rapidly: As we’ve seen with the sudden rise of DeepSeek, the AI landscape is shifting quickly. What works today may not be the best solution tomorrow. Therefore, companies must build flexible systems that allow for the integration of new models and technologies as they become available.
- Middleware Solutions: A middleware layer can provide the flexibility needed to switch between different AI models. Consider, for example, that Gemini is still more cost effective than DeepSeek when access through APIs.
Flexibility is essential for businesses that want to remain competitive in an ever-changing market. Middleware can help manage the integration of multiple models, offering businesses the ability to optimize their AI usage across various platforms.
The Future of AI with DeepSeek
As DeepSeek continues to make waves in the AI world, businesses must adapt to the changing landscape. The days of locking into a single AI provider like OpenAI may soon be behind us. With the cost of AI models dropping and models like DeepSeek offering unparalleled efficiency, the message is clear–build for flexibility because it is now more important than ever. Embrace the future of AI—flexible, cost-effective, and innovative—and start thinking beyond traditional AI architectures.
