A new era of AI and DeepSeek-r1's breakthrough
Imagine: you give an AI model time to really think. Not a fraction of a second, but plenty of time to explore, evaluate and choose the best solution. The result? A fundamental change in the AI landscape. That is exactly what DeepSeek-r1, a groundbreaking deep ai system, delivers. In just a few months, DeepSeek has developed an ai deep model that performs just as well as OpenAI's top models, but for an amazing 3% of the costs. This performance even exceeds that of other advanced models such as Claude and Qwen.
How did they do this? Through a revolutionary approach to AI training, including using a mixture of experts, and using “System 2” thinking — also known as test-time compute. This blog post explores the impact of this breakthrough and what it means for the future of AI, innovation, and businesses around the world. Get ready, because the game has changed in the world of large language models, including platforms like Llama and Hugging Face.
The core of the innovation: System 2 thinking and unsupervised learning
At the heart of DeepSeek-R1's breakthrough lies in embracing “System 2” thinking. While traditional AI models, such as GPT-4 and Qwen, work primarily via “System 1” (fast, intuitive decision making), DeepSeek-r1 uses “System 2” (slow, analytical thinking). This means that the model generates multiple solution directions, evaluates them internally and then chooses the best one, resulting in improved reasoning capabilities.
This has been made possible by a revolutionary training method: uncontrolled reinforcement learning. Until now, AI models have relied on expensive “supervised fine-tuning” with human feedback and large amounts of computing power. DeepSeek-r1 learns independently, without human labels or corrections, resulting in a significant cost reduction. This method, similar to techniques used in platforms such as LMStudio and vLLM, uses advanced distillation processes.
Remarkable Results: This leads to amazing results: DeepSeek-r1 performs at the level of the best human programmers, with a 97% cost reduction compared to similar models. Scalability also seems limitless: the longer the model “thinks”, the better the result, as shown by various performance benchmarks such as MMLU and LiveCodeBench.
The impact: costs, accessibility and growth
These developments have an enormous impact. First, it makes AI drastically cheaper. Second, AI is becoming more accessible because DeepSeek-r1 is open-source. This means that any country, company or developer can now build similar models themselves, without being dependent on major tech companies. And with hardware innovations such as NVIDIA Digits and AI PC dev kits, AI models can be run locally via local inference instead of in the cloud, significantly improving GPU performance.
Companies benefit in the short term of lower costs and more safety through local AI implementation. In the long term, the price of AI will fall further, making large-scale AI applications feasible for any company. This opens the door for advanced deep ai chat systems and AI-powered assistants.
The Jevons Paradox teaches us that technology efficiency actually leads to more use. This will also apply to AI. Cheaper and more efficient AI makes many more applications profitable, from legal analysis to marketing and even healthcare.
With DeepSeek-R1's open-source release, Europe has a unique opportunity to play a leading role in AI. We can develop AI that complies with our privacy and ethical guidelines. Companies can innovate without relying on US or Chinese technology, and a level playing field is created for SMEs and startups.
A European AI model, with privacy and transparency at the forefront, can provide a strong competitive position in the global market, comparable to other leading platforms such as Hugging Face and Llama.
Concretely: what does this mean for you?
The combination of DeepSeek-r1, open-source AI, and affordable hardware makes AI as accessible as electricity: always available and affordable. This opens the door for a wide range of applications, from simple chatbots to advanced AI-powered assistants with comprehensive vision capabilities.
For companies, this means in concrete terms:
- AI-driven agents that perform complex tasks independently, using advanced model parameters.
- Automation of knowledge work and product development, similar to what we see on platforms such as CodeForces and AIME.
- New AI-driven products and services, such as personalized chatbots and advanced data analysis.
For Entrepreneurs and Innovators, it's time to take action:
- Experiment with open-source AI models such as DeepSeek-r1, Llama, and Ollama, and compare their performance with other models such as Qwen.
- Invest in test-time compute and reasoning AI to unleash the full potential of these models.
- Get ready for the rise of agentic AI — software that performs tasks independently with improved reasoning capabilities.
How do we take advantage of this AI revolution?
DeepSeek-r1 has changed the playing field. The question now is: how do we ensure that companies and governments seize this opportunity? Which business processes can be optimized with AI? How can Europe play a leading role in ethical AI? And what new applications do you see as a result of this AI revolution? Together, let's think about how we can use these technological developments to stimulate innovation, efficiency and economic growth. Whether it's using DeepSeek-v3 for advanced tasks, implementing sGlang for more efficient communication, or exploring the possibilities of new hardware requirements for local AI deployment with AI PC dev kits, the possibilities are endless.
The future of AI is now. What are you going to do with it?