Misunderstood DeepSeek Controversy

The DeepSeek controversy recently stirred up many people, with events outside the AI scene often being interpreted as "USA vs. China". From our perspective, this is wrong – the innovation that enabled DeepSeek R1 could just as well have emerged in Northern Italy or Canada. It was a logical continuation of research into using Reinforcement Learning (RL) for training large language models. Amusingly, Nvidia (whose stock price suffered heavily under the DeepSeek event) had already achieved great success with RL approaches: Their Nemotron was already a benchmark summit climber in October 2024, despite the model having only 70 billion parameters.

The crucial debate is rather Closed-Source vs. Open-Source AI models. This public discussion was often misrepresented and overshadowed the actual topic: the importance of transparency and collaboration in AI development. DeepSeek R1 as an open-source AI model has proven groundbreaking by challenging traditional approaches and highlighting the transformative potential of open-source innovations.

The Real Debate: Closed Source vs. Open Source

AI models are often divided into Closed Source, like OpenAI's ChatGPT, and Open Source, like Meta's Llama 3, which is often used as a base model for newer open-source models. Closed-source models keep their data and algorithms secret, while open-source models promote transparency and innovation. DeepSeek R1 stands out by embracing open-source principles without being based on Llama 3, enabling global developers to freely access it. DeepSeek R1 was also trained with a novel approach to Reinforcement Learning (RL), which improves its adaptability and reasoning capabilities. This innovative approach is described in detail in this paper and sets it apart from the competition.

DeepSeek R1: A Unique Approach

DeepSeek R1 stands out in the AI landscape by not following the path of Meta's Llama 3. Instead, it has created something novel by integrating Reinforcement Learning (RL), a method that enhances its learning and adaptability. This approach is described in detail in this paper and shows how DeepSeek R1 achieves impressive capabilities in logical reasoning and mathematics. Its open-source nature means that developers worldwide can access and build upon its framework, fostering a collaborative environment.

The Irony of Nvidia's Nemotron

In October 2024, Nvidia released Nemotron, a robust medium-sized open-source model that ranked among the top models in many benchmark rankings. Ironically, the introduction of DeepSeek R1 led to a sharp decline in Nvidia's stock, despite their own earlier contribution to the open-source movement. For more insights into Nemotron, check out our blog post. This situation illustrates the unpredictable dynamics of the AI market and the growing influence of open-source models.

Our Approach: Integration of DeepSeek R1

At Evoya AI, we have recognized the potential of DeepSeek R1 and integrated it into our model suite. This addition allows our users to explore and compare its capabilities with other leading models like ChatGPT and Claude. We invite you to try DeepSeek R1 and experience its unique features firsthand. Sign up here.