The ongoing discourse surrounding Artificial General Intelligence (AGI)—AI that possesses human-like cognitive abilities across a wide range of tasks—often conjures images of superintelligent machines capable of revolutionizing or perhaps endangering humanity. However, a recent experiment by a Business Insider journalist with Google's Gemini music tool offers a more grounded, albeit humorously dystopian, perspective. The journalist set out to create a rap song about AI data centers, a subject not typically associated with lyrical prowess or artistic merit. The outcome, while not indicative of true AGI, certainly showcases the rapid advancements in AI's creative capabilities. The tool, integrated within Gemini, allowed the journalist to generate a musical piece based on a specific theme. The experience, however, was met with mixed reactions, most notably a colleague's blunt assessment of the rap as 'an abomination.' This reaction, while harsh, highlights the subjective nature of art and the current limitations of AI in consistently producing aesthetically pleasing or universally acclaimed creative works. The article emphasizes that while we are far from achieving AGI, AI is already capable of engaging in creative endeavors, even if the results are sometimes questionable. The focus on data centers as a subject matter is particularly interesting, as it represents a technical and abstract concept that AI managed to translate into a musical format. This suggests that AI's understanding and generation capabilities extend beyond simple data processing into more complex forms of expression. The experiment serves as a cautionary tale and a testament to the evolving nature of AI. It demonstrates that AI can be a tool for creative exploration, but human judgment and artistic sensibility remain crucial in shaping and evaluating its output. The journalist's experience, documented in Business Insider, underscores the idea that AI can be a fascinating, and sometimes bewildering, partner in creative processes. It's a step towards understanding what AI can do now, while acknowledging the vast distance still to cover before reaching the hypothetical capabilities of AGI.