In a significant development for artificial intelligence, DeepSeek R1 has demonstrated the ability to improve its own performance, achieving a 2X speed improvement through self-modification.
This breakthrough, revealed in a blog post by Simon Willson, marks a potential turning point in the field of AI as we approach what some experts call the “intelligence explosion.”
The most striking aspect of this achievement is that 99% of the code for the improvement was written by DeepSeek R1 itself.
The human involvement was limited to developing tests and writing prompts, with the AI model figuring out how to enhance its own capabilities.
This self-improvement feat was accomplished using a series of prompts in an iterative loop. The AI was tasked with converting C++ ARM Neon code to WebAssembly SIMD, a process that involves optimizing parallel processing for ARM chip architecture.
DeepSeek R1 not only completed this complex task but also demonstrated a clear chain of thought in its problem-solving approach.
Experts in the field are divided on the implications of this development.
While some see it as a sign of an imminent “hard takeoff” in AI capabilities, others, like Yann LeCun, head of AI research at Meta, suggest that the emergence of Artificial General Intelligence (AGI) will be more gradual and progressive.
The open-source nature of these developments is accelerating progress in the field. Just days after a Berkeley PhD recreated similar thinking abilities for $30, another team achieved comparable results for a mere $3.
This rapid replication and improvement cycle is making advanced AI capabilities increasingly accessible.
As we witness these rapid advancements, the AI community is exploring new paradigms.
There’s growing interest in developing numerous small, specialized models with core base intelligence, each excelling in particular tasks, rather than relying solely on massive generalized models.
These developments raise important questions about the future trajectory of AI and its potential impacts on various fields.
As AI continues to evolve at a breakneck pace, the need for ongoing research, ethical considerations, and public discourse becomes ever more critical.
