AI's Timekeeping Woes: Still a Long Way to Catch Up with Humans
AI's Struggles with Time and Calendar Interpretation: Study Reveals Insights
Artificial intelligence (AI) may have blown our minds with its ability to write code, ace exams, and even compose music, but when it comes to deciphering clocks and calendars, it seems we're still in the Stone Age. A recent jaw-dropping study presented at the 2025 International Conference on Learning Representations (ICLR) and published on the preprint server arXiv, sheds light on some tough truths about AI's timekeeping ineptitude.
Humans have been clock and calendar whizzes since, well, since we first gazed at the sky and started scribbling on cave walls. But our AI pals, it appears, are finding themselves in a bit of a pickle when it comes to these seemingly simple tasks. According to Rohit Saxena, the research leader from the University of Edinburgh, this is a big ol' problem because if we wanna have AI assisting us in the real-world applications that involve time, like automation and scheduling, we need that robot brain to get its shiz sorted.
So, researchers fed a slew of clock and calendar images into various large, multi-purpose language models (LLMs). These fancy-pants AI lads, such as Meta's Llama 3.2-Vision and Google's Gemini 2.0, were intended to figure out the time from a clock pic or the day of the week for a specific date. But spoiler alert—they flat-out bombed more than half the time. Clock reading and date calculations, it seems, are kryptonite to these clever machines.
Turns out, AI grapples with spatial reasoning when it comes to clocks—due to complicated designs, overlapping hands, and the lack of the brain power required to make sense of those angles and positions. Calendar interpretations are equally erratic, with LLMs having a hard time with date calculations and even calculating the day of the year. Seriously, folks! This is like kindergarten stuff.
Intriguingly, arithmetic—which we're told is supposed to be a walk in the park for computers—proves tricky for these intelligent gadgets because they rely on patterns in their training data rather than actual math skills.
Long story short, this study highlights that while AI has some pretty cool tricks up its sleeve, it's still got a long way to go when it comes to grasping things like humans do. And going forward, it seems wise to keep a hawk-eye on AI, not just blindly swallowing everything it spits out. You know, when it comes to tasks involving both perception and reasoning, a human brain might not be such a bad safety net.
In summary, AI's got some powers worth gawking at—but it's certainly not perfect. And when it comes to tasks that call for a mix of logic and spatial reasoning, we might wanna reconsider fully trusting these mechanical minds. Just a friendly reminder!
Food scientists are exploring the potential of AI in health-and-wellness by developing AI-powered systems to analyze food components and suggest nutritionally balanced meal plans. On the other hand, the study revels that AI technology struggles with basic temporal tasks, like understanding the time and days of the week, which is crucial for automation and scheduling in various fields, including food preparation and delivery services. Furthermore, the advancement of technology could create a mixed reality where AI assists humans in complex tasks, emphasizing the need for continuous development in AI's ability to reason spatially and perform calculations accurately.
