GoonThe Rise of DeepSeek R1: A New Era in AI
The recent launch of DeepSeek R1 has sent shockwaves through the AI community, with many hailing it as a game-changer. But what does this new technology mean for the future of AI, and how does it compare to existing models?
Introduction to DeepSeek R1
Introduction to DeepSeek R1, a new AI startup that has created a new open weights model called R1
DeepSeek R1 is a new AI startup that has created a new open weights model called R1, which allegedly beats Open AI's best models in most metrics. This achievement is even more impressive considering that DeepSeek R1 was able to accomplish this feat with a relatively low budget of $6 million, using GPUs that run at half the memory bandwidth of Open AI's Pony Stark.
The Significance of DeepSeek R1
The significance of DeepSeek R1 lies in its ability to distill other models, making them run better on slower hardware. This means that even a Raspberry Pi can run one of the best local Quen AI models, which is a significant achievement. However, it's essential to note that the Raspberry Pi can technically run DeepSeek R1, but it's not the same as running the full 671b model, which requires a massive amount of GPU compute.
Running DeepSeek R1 on Raspberry Pi
Running DeepSeek R1 on Raspberry Pi, which can run the 14b model but not the full 671b model
Running DeepSeek R1 on a Raspberry Pi is possible, but it's essential to understand the limitations. The 14b model can run on the Raspberry Pi, but it's not going to win any speed records. Testing a few different prompts, the Raspberry Pi can achieve around 1.2 tokens per second, which is sufficient for simple tasks like rubber duck debugging or generating ideas for YouTube titles.
The Importance of GPUs
The importance of GPUs in running DeepSeek R1, which can significantly improve performance
GPUs play a crucial role in running DeepSeek R1, as they can significantly improve performance. With an external graphics card, the Raspberry Pi can achieve much faster speeds, around 20-50 tokens per second, depending on the type of work being done. This is because GPUs and their VRAM are way faster than CPUs and system RAM.
Running DeepSeek R1 on Other Hardware
DeepSeek R1 can also be run on other hardware, such as a 192-core server, which can achieve around 4 tokens per second. This server is more affordable than a high-end GPU setup and consumes only around 800 watts of power, making it a more accessible option for those interested in running DeepSeek R1.
The Future of AI and GPUs
The future of AI and GPUs looks promising, with AMD GPUs working great, Intel open-source drivers working somewhat, and Nvidia potentially joining the fray. This means that there will be more options available for those interested in running AI models on their hardware, and we can expect to see significant improvements in performance and accessibility.
The AI Bubble
The AI bubble is still very much alive, with Nvidia losing over half a trillion dollars in value in one day after the launch of DeepSeek R1. However, their stock price is still eight times higher than it was in 2023, indicating that the hype surrounding AI is still very much present. Despite this, there are some positive takeaways, such as the realization that we don't need to devote massive amounts of energy resources to train and run AI models.
Conclusion
The rise of DeepSeek R1 marks a new era in AI, with significant implications for the future of the technology. While there are still many challenges to overcome, the potential for AI to improve and become more accessible is vast. As we move forward, it will be essential to separate the hype from the reality and focus on developing AI models that are practical, efficient, and accessible to all.