When DeepSeek R1 was released in late January of 2025, we held a special AIMX Meetup webinar to discuss its implications with the community in the ⁠AIMX Network⁠.

The hour-long discussion was a spirited one and our guests also addressed comments from the community.

We have released an AIMX Podcast episode featuring the webinar, and extracted the key discussion points to generate this article.

Introduction

The AI landscape is rapidly evolving, and one of the most significant developments in recent times is the introduction of DeepSeek. This new LLM is poised to revolutionize the field of artificial intelligence, bringing with it a host of innovations and challenges.

DeepSeek has garnered attention for its ability to integrate seamlessly with various hardware and software platforms. Unlike traditional AI models that rely heavily on specific frameworks like CUDA, DeepSeek offers a more flexible approach. This flexibility is particularly evident in its compatibility with a wide range of chips, including those from Huawei and AMD. This opens up new avenues for innovation, especially in regions where access to certain technologies is restricted due to embargoes.

Open-Source as an Advantage

One of the most notable aspects of DeepSeek is its open-source nature. This has led to a surge in interest from both developers and businesses looking to leverage its capabilities. The open-source model allows for greater transparency and collaboration, fostering an environment where new ideas can flourish. For instance, companies like Perplexity AI have already begun to unbundle DeepSeek and create new products that are significantly cheaper and more efficient.

Possibilities for Hardware Development

The impact of DeepSeek is not limited to software development. It also has significant implications for hardware optimization. By moving closer to machine-level code, DeepSeek enables more efficient use of hardware resources. This is particularly important in the context of edge computing, where resources are often limited. The ability to run complex AI models on devices like smartphones and IoT sensors opens up a plethora of new opportunities.