Researchers have developed AI4AI-Bench, a benchmarking tool to evaluate the ability of large language models (LLMs) to design and improve their own training algorithms. The tool tests whether an LLM can rewrite its training algorithm to achieve better performance. In initial experiments, even the strongest LLMs were only able to reach about 25% of the optimal performance, with most submissions not changing how the model learns at all. The researchers release the task suite and scored submissions for further evaluation. --- Why it matters: This matters because it tests a fundamental aspect of recursive self-improvement in AI: whether an agent can design better training algorithms to improve its own capabilities. This has implications for the development of more advanced and autonomous AI systems. Source: https://arxiv.org/abs/2608.20318