What is Deepseek AI and why is it disrupting the market?

DeepSeek: The AI Model Shaking Up the Industry

Artificial Intelligence is the most transformative technology of our time, but up until now, most of the power has been concentrated in a few key players — OpenAI, Google DeepMind, and Meta. These companies have built massive AI models that require billions of dollars in funding and huge server farms to operate.

But what if an AI could perform just as well — or even better — at a fraction of the cost?

That’s exactly what’s happening with DeepSeek, a new AI model from China that is raising serious questions about the future of AI dominance.

For business owners, this is not just another tech update — it’s a wake-up call. The AI industry is shifting, and understanding this change could be the difference between staying ahead or falling behind. What is DeepSeek?

DeepSeek is a new AI model developed by a team of young engineers in China, backed by a hedge fund named High-Flyer. It consists of multiple AI models, including DeepSeek-V3 and DeepSeek-R1, designed to compete with industry leaders like OpenAI’s ChatGPT and Meta’s Llama models.

Key Features:

• Powerful Performance: Benchmarks show that DeepSeek performs on par with or even better than the biggest AI models from the U.S.

• Affordable Training Costs: Training DeepSeek-V3 costs under $6 million, while models like GPT-4 require hundreds of millions of dollars.

• Efficiency: DeepSeek’s AI can run on laptops and phones, unlike OpenAI’s models which need massive data centers.

• Open Sharing: The engineers have shared much of their technology, allowing others to use and build upon their innovations.

These factors have led many investors to pause investments in U.S.-based AI companies, questioning whether they need to continue funding such expensive models.

What is DeepSeek and Why Does It Matter?

DeepSeek includes multiple AI models, the most notable being DeepSeek-V3 and DeepSeek-R1, both of which are shaking up the industry for three big reasons:

1. DeepSeek is Just as Good — if Not Better — Than U.S. AI Models

Early tests show that DeepSeek’s models are performing at the same level as OpenAI’s GPT-4o and Meta’s Llama-3. But it doesn’t stop there — on certain benchmarks, DeepSeek outperforms these models while requiring significantly less computing power.

This alone is a massive breakthrough. Up until now, most AI researchers believed that only the biggest, most resource-hungry models could deliver the best results. DeepSeek proves that assumption wrong.

2. DeepSeek is 10x to 100x Cheaper to Run

This is where things get even more shocking. AI models are incredibly expensive to train and run — OpenAI’s GPT-4 cost hundreds of millions of dollars to build. But DeepSeek-V3 was trained for less than $6 million.

Not only that but DeepSeek-R1 (the latest model) is reported to be 20 to 50 times cheaper to use compared to OpenAI’s models.

For businesses, this means AI is about to get a lot cheaper. If you’re running AI-powered tools, whether for marketing, automation, or analytics, you may soon have access to a model that delivers similar (or better) performance at a fraction of the cost.

3. DeepSeek Works on Laptops and Phones

One of the biggest limitations of today’s AI is that it requires huge cloud computing resources. OpenAI, Google, and Meta all rely on massive data centers packed with powerful GPUs just to keep their AI running.

DeepSeek, however, is designed to work on much smaller devices — including laptops and phones.

This could be a game-changer. Instead of relying on cloud services, companies may soon be able to run high-performance AI locally, which could:

• Reduce dependency on Big Tech (no more being locked into OpenAI or Google’s APIs)

• Improve privacy (since data doesn’t need to be sent to the cloud)

• Lower costs (since you don’t need expensive cloud computing)

DeepSeek is an Open Book — Unlike OpenAI

Another major reason why DeepSeek is shaking things up is that its creators have openly shared much of their technology. Unlike OpenAI and Google, which keep their latest breakthroughs behind closed doors, DeepSeek has published technical papers explaining how they built their AI.

This means that other companies can take DeepSeek’s innovations and apply them to their own AI models. This could accelerate AI progress worldwide and make it harder for any single company to dominate the market.

Why Business Owners Should Pay Attention to This

DeepSeek isn’t just another AI model — it’s a threat to the current AI hierarchy.

If you’re running a business, this could mean:
✅ Lower AI costs — Whether you’re using AI for marketing, automation, customer service, or analytics, DeepSeek could help cut costs significantly.
✅ More AI competition — If OpenAI and Google start losing their monopoly, you’ll have more options for AI services — and more affordable alternatives.
✅ AI running on your own devices — Instead of relying on expensive cloud-based AI, future models might run directly on your laptop or phone.

✅ DeepSeeks model weights and code are still publicly available, meaning developers and companies outside restricted environments can download and integrate them into their own applications and systems. 

This is just the beginning. Now that we understand what DeepSeek is and why it matters, let’s dive into the real disruption it’s causing in the AI industry.

Part 2: Why DeepSeek is So Disruptive

DeepSeek isn’t just another AI — it’s turning the AI industry upside down. For the past few years, the biggest assumption in AI has been:
👉 “The bigger, the better.”

Companies like OpenAI, Google DeepMind, and Meta have followed this rule, spending billions of dollars to build larger and larger AI models, believing that only massive models trained on enormous supercomputers could dominate the market.

DeepSeek proves that assumption wrong — and that’s why it’s so disruptive.

Let’s break down the three main ways DeepSeek is shaking up the AI world.

1. AI Can Be Powerful Without Being Massive

OpenAI’s GPT-4o, Google’s Gemini, and Meta’s Llama-3 all follow the same trend:

• They require enormous amounts of computing power

• They need massive data centers to run efficiently

• They cost hundreds of millions of dollars to train

DeepSeek doesn’t.

DeepSeek-R1, released just last week, is small enough to run on laptops and mobile phones — yet in many tests, it matches or even outperforms OpenAI’s best models.

This completely flips the script on AI development.

Until now, the idea was that only companies with billions of dollars could build cutting-edge AI. But DeepSeek shows that smaller, smarter AI models can compete at the highest level — at a fraction of the cost.

🚀 Implication: We could be moving toward an AI world where every business and developer can run advanced AI locally instead of depending on cloud giants.

2. DeepSeek is So Cheap That It Changes Everything

💰 DeepSeek-V3 was trained for just $6 million.

Compare that to OpenAI’s GPT-4, which likely cost hundreds of millions of dollars to train.

💰 DeepSeek-R1 is 20 to 50 times cheaper to use than OpenAI’s models.

This is a game-changer for AI-based businesses.

Right now, most AI startups and enterprises are locked into expensive API fees from OpenAI, Google, or Anthropic. Using powerful AI isn’t cheap — it costs real money every time an AI model is used in chatbots, automation, research, or analytics.

DeepSeek’s cost efficiency threatens to undercut these major AI providers.

✅ Cheaper AI means more businesses can integrate AI without breaking the bank.
✅ Startups won’t need massive funding just to afford AI models.
✅ Companies might move away from OpenAI and Google in favor of lower-cost AI solutions.

ChatGPT Plus: Priced at $20 per user per month, this plan offers general access to ChatGPT, even during peak times, faster response times, and priority access to new features and improvements.

API Usage: DeepSeek charges per token processed. Uploading 1 million tokens costs approximately $0.55, while downloading 1 million tokens is about $2.19.

🚀 Implication: If DeepSeek keeps pushing AI costs down, companies like OpenAI and Google will lose pricing power — and that could trigger a major shift in the AI industry.

3. DeepSeek’s Open Sharing Model Could Break OpenAI’s Grip

One of the most shocking things about DeepSeek is that its creators are openly sharing their research.

Most AI breakthroughs from OpenAI and Google are closed-source — meaning businesses must use their services and can’t build their own AI models.

DeepSeek, on the other hand, has published detailed papers explaining exactly how they built their models.

This means:
✅ Other AI developers can copy, improve, and build upon DeepSeek’s innovations
✅ Companies can train their own AI models instead of relying on OpenAI or Google
✅ AI research can move faster as more people collaborate on making AI better

This is a major philosophical difference.

👉 OpenAI started as an open-source company, but now it keeps everything locked up.
👉 DeepSeek is freely sharing its knowledge to help others build on its work.

🚀 Implication: If DeepSeek’s model proves successful, more companies may move away from closed-source AI and build their own models using DeepSeek’s methods. This could accelerate AI progress and weaken OpenAI and Google’s control over the industry.

Why This Matters to You

DeepSeek’s rise isn’t just a tech story — it’s a business story.

If you’re a business owner, entrepreneur, or AI user, here’s why you should pay attention:

🔹 AI is about to get cheaper.

• If you’re using AI-powered tools, expect big price drops in the near future.

• If your business is paying OpenAI for API access, DeepSeek could give you a much cheaper alternative.

🔹 AI will soon run on smaller devices.

• No need to rely on cloud AI if local models become just as powerful.

• This could mean more privacy, lower costs, and faster AI responses.

🔹 AI innovation is about to speed up.

• Open-source AI could grow faster than closed models like GPT-4.

• If you’re building AI products, you might not need to depend on OpenAI’s tools anymore.

The Bottom Line: DeepSeek is Forcing an AI Industry Rethink

DeepSeek proves that:
✅ AI doesn’t have to be massive to be powerful.
✅ AI can be trained for a fraction of the cost of today’s biggest models.
✅ Open-source AI might be the future — not closed ecosystems like OpenAI.

And the impact is already being felt.

💡 Many investors are now pausing their AI investments into OpenAI and Anthropic to reassess their strategies.

💡 Tech companies are rethinking how they build AI models — and whether they need to spend billions just to compete.

💡 Businesses may soon have more AI choices — meaning lower costs, more control, and fewer dependencies on Big Tech.

DeepSeek is still in its early days, but it has already sent shockwaves through the industry.

Now that we understand why DeepSeek is disruptive, let’s take it one step further:

👉 How does DeepSeek actually work?

That’s what we’ll cover next. Stay with me.

Part 3: How DeepSeek Works — And Why It’s Better

Now that we’ve covered what DeepSeek is and why it’s disruptive, let’s dive into how it actually works and why it’s so much more efficient than existing AI models.

From the images and research provided, we’ll break this down into three core elements:
✅ Reinforcement Learning and the “Aha” Moments
✅ GRPO: A Smarter AI Training Method
✅ Benchmark Performance: DeepSeek vs. The Competition

Let’s get into it.

1. Reinforcement Learning and the “Aha” Moments

One of DeepSeek’s biggest breakthroughs is how it learns and corrects itself during problem-solving.

In traditional AI models, the system is trained on a massive dataset and then fine-tuned with human feedback. However, DeepSeek’s reinforcement learning system takes this further.

The slide you provided shows an example where DeepSeek-R1-Zero stops, reflects, and corrects itself while solving a math problem.

💡 What’s happening here?

• The AI is not just blindly following the math steps — it realizes when something seems wrong and rethinks its approach.

• This is an advanced form of reinforcement learning, where the AI improves by learning from past mistakes, much like a human.

• The phrase “Wait, wait. That’s an aha moment!” is the AI actually recognizing that something doesn’t add up, then debugging its own logic.

🚀 Why this matters:
✅ AI models like GPT-4 don’t naturally rethink their own responses — DeepSeek does.
✅ This means DeepSeek is better at complex problem-solving and avoids common AI mistakes.
✅ It’s a step toward AI models that “think” more like humans.

2. GRPO: A More Efficient Training Method

To understand why DeepSeek is so efficient, we need to talk about how it’s trained.

Most AI companies use a training method called Proximal Policy Optimization (PPO), which is the system OpenAI uses to train ChatGPT. However, DeepSeek introduces a better method called Group Relative Policy Optimization (GRPO).

🔍 What’s the difference?

• PPO requires a separate “value model” to evaluate how good an AI’s response is.

• GRPO removes the value model and instead estimates rewards based on grouped scores.

• This significantly reduces computing power while still achieving better training results.

🚀 Why this matters:
✅ OpenAI’s models require huge amounts of computing resources — DeepSeek does the same job using less power and money.
✅ The efficiency of GRPO is why DeepSeek can train powerful AI models for $6 million, while OpenAI spends hundreds of millions.
✅ By eliminating unnecessary computations, DeepSeek achieves cutting-edge AI without the insane costs.

This is one of the core reasons why DeepSeek is so disruptive — it proves that AI can be trained better without burning billions in GPUs.

3. Benchmark Performance: DeepSeek vs. The Competition

Numbers don’t lie — DeepSeek is outperforming some of the world’s top AI models while being far more efficient.

Let’s break it down.

🧠 Reasoning Performance (MMLU, GPQA, Frames, etc.)

DeepSeek-R1 achieves:
✅ 92.9% on MMLU-Redux, beating OpenAI’s top models.
✅ 83.3% on IF-Eval, one of the hardest prompt evaluation benchmarks.
✅ Better performance than Claude 3.5 and GPT-4o in many key benchmarks.

� Key takeaway: DeepSeek-R1 isn’t just competing — it’s winning on multiple logic-based AI tasks.

💻 Coding Performance (LiveCodeBench, CodeForces, SWE Verified)

AI models are often judged by how well they write and debug code.

DeepSeek achieves:
✅ 65.9% on LiveCodeBench, outperforming OpenAI’s o1-mini model.
✅ 2,029 on CodeForces (higher is better), beating many top models.

🔥 Key takeaway: DeepSeek is one of the strongest AI models for coding, making it a direct competitor to OpenAI’s Codex and GitHub Copilot.

📊 Math Performance (MATH-500, CNMO, AIME 2024)

Math reasoning is one of the hardest challenges for AI models, and DeepSeek excels here.

✅ DeepSeek-R1 scores 97.3% on MATH-500, outperforming GPT-4o.
✅ 88.8% on DeepSeekMath-RL, making it one of the best AI math solvers available.

🔥 Key takeaway: DeepSeek isn’t just good at general language tasks — it excels in structured, complex reasoning like math.

Why This Matters for Businesses and AI Users

DeepSeek isn’t just another AI model — it’s a proof of concept that AI can be:
✅ Faster to train (thanks to GRPO)
✅ Smarter at reasoning (due to its reinforcement learning abilities)
✅ Cheaper to run (because it doesn’t need massive data centers)
✅ More competitive than OpenAI and Google’s best models

💡 For businesses, this means you will soon have access to:

• Cheaper AI tools that perform just as well as OpenAI’s expensive models.

• More AI choices, reducing dependency on a handful of Big Tech firms.

• Stronger AI automation, especially in reasoning-heavy tasks like math, coding, and logic.

The AI landscape is about to shift — and DeepSeek is one of the biggest reasons why.

Last week DeepSeek launched out of nowhere

OpenAI responded, “We’ll speed up releases”

And they did!

OpenAI launched “Deep Research” yesterday.

I test it against DeepSeek

The Task: A lead magnet explaining how the 2025 US tariffs on China and Mexico will impact online sellers.

Here’s the result:

Context:
❌ DeepSeek starts working immediately
✅ ChatGPT asks clarifying questions

Output Quality:
❌ DeepSeek's output was too high-level
✅ ChatGPT provided well-explained insights

Citations:
❌ DeepSeek lacked citations
✅ ChatGPT cited all sources

ChatGPT’s Deep Research output was amazing.
DeepSeek’s output was lackluster

Maybe DeepSeek wins at simpler outputs?
While ChatGPT delivers on the more complex?

Either way, the competition is on!

Final Thoughts: What Comes Next?

Recent developments indicate that the U.S. government is considering stringent measures against the use of Chinese-developed AI models, particularly DeepSeek. A bill introduced by Senator Josh Hawley (R-MO) aims to prohibit U.S. individuals and entities from engaging with AI technologies originating from China. If enacted, violations could result in penalties of up to 20 years in prison and fines reaching $1 million for individuals and $100 million for corporations.

theregister.com

This legislative move reflects growing concerns over national security and data privacy associated with Chinese AI applications. Lawmakers fear that such technologies could expose U.S. users to risks, including potential data breaches and the promotion of censorship.

cbsnews.com

In response to these concerns, some U.S. states are taking proactive measures. For instance, Texas has become the first state to ban DeepSeek and other Chinese-backed apps from government devices, citing data security and potential foreign influence as primary reasons for the ban.

nypost.com

These actions underscore the escalating scrutiny of foreign AI technologies and highlight the importance of evaluating the security implications of integrating such applications into domestic systems.

The question is no longer whether DeepSeek will change AI — it’s how soon.

🚀 Stay tuned — because this is just the beginning.