OpenAI has introduced a new benchmark, MLE-bench, aimed at evaluating the performance of AI agents in comparison to human data scientists. This benchmark is part of a broader trend in AI research, where various studies are assessing the reasoning capabilities of large language models (LLMs). Recent findings indicate that top human performers outscored AI agents in a rigorous Q3 Benchmark, with a statistical significance of p=0.036. In the upcoming Q4 series, which offers a prize pool of $30,000, researchers are eager to see if AI can surpass human performance. Additionally, WecoAI's AIDE has been recognized as the leading Machine Learning Engineer Agent, outperforming competitors like OpenAI's models in several competitions. However, concerns persist regarding the reasoning abilities of LLMs, with studies revealing that they struggle with mathematical tasks and exhibit inconsistent performance when faced with slight variations in problems. Researchers are investigating the cognitive limitations of these models, questioning whether they can genuinely reason or if their outputs are merely sophisticated pattern matches.