AI Is Starting to Build Better AI
This IEEE Spectrum feature examines how far AI has come toward recursive self-improvement (RSI), the long-imagined idea of machines that design better machines. The article traces decades of stepping-stones, from machine learning and AutoML to today's large language models writing the code for their own successors. It argues that while many systems now help build better AI, they still rely on humans to set goals, define success and decide which changes to keep, so the question is how much of the self-improvement loop has actually been closed.
Key Takeaways
- The field of artificial intelligence was built on the premise that machines might someday improve themselves.
- At its strictest, researchers use the term to describe systems that can improve not just their outputs but the process by which they improve-generating ideas, evaluating results, and modifying their own methods with zero human direction.
- One of their biggest use cases is to write code, including the code to produce future versions of themselves.
In February, OpenAI reported that GPT‑5.3‑Codex was instrumental in creating itself, helping to debug training, manage deployment, and analyze evaluation results.
- "Often you look at what the system discovers, and you actually learn from that discovery."
- Other projects focus on AI agents modifying their own behavior.
The field of artificial intelligence was built on the premise that machines might someday improve themselves. In 1966, the English mathematician I. Good wrote that "an ultraintelligent machine could design even better machines; there would then unquestionably be an 'intelligence explosion,' and the intelligence of man would be left far behind."
AI researchers have long seen recursive self-improvement, or RSI, as something to both desire and fear. Today, advances in AI are raising the question of whether parts of that process are already underway. RSI means many things to many people.
Some use the idea as a bogeyman to scare up regulation, while others brandish it in marketing. For some, it means a fully autonomous loop, while for others it's nearly any use of tech to build tech. At its strictest, researchers use the term to describe systems that can improve not just their outputs but the process by which they improve-generating ideas, evaluating results, and modifying their own methods with zero human direction.
For more details please read the original article at IEEE Spectrum AI.
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