Image created using DALL·E 3 with this prompt: An embodiment of ChatGPT getting lazy or lethargic due to cold weather and seasonal depression.

Recent observations suggest ChatGPT-4 may be getting lazy. This trend was first noticed in late November when users began reporting that the model started providing simplified responses or avoiding certain tasks altogether. OpenAI has acknowledged the issue, though the cause remains uncertain.

I’ve experienced this issue several times in the past month; it usually manifests itself as an unwillingness to finish a task. For example, a prompt asking ChatGPT to output a list in HTML might elicit a response such as, “Due to the length of the list, I’ve created an HTML template you can follow to fill in the rest of the data.”

A theory, dubbed the “winter break hypothesis,” proposes that ChatGPT-4 might be mimicking human seasonal behavior: slowing down in December, reflective of the training data it has processed. This hypothesis gained a bit of traction because ChatGPT-4 has shown responsiveness to human-like encouragement, but it is unproven and hard to replicate.

Developer Rob Lynch’s experiment adds to the discussion. He found shorter outputs from ChatGPT-4 when given a December date compared to a May date, suggesting a possible date-related influence on the AI’s performance. However, AI researcher Ian Arawjo could not replicate these findings with statistical significance, highlighting the variability and unpredictability in LLM behaviors.

While these observations have sparked curiosity and various tests within the tech community, definitive conclusions are yet to be drawn. The situation presents a unique insight into the complexities of AI and the challenges in understanding and predicting its behavior. As investigations continue, they offer a glimpse into the nuanced interactions between AI and the data it is exposed to, underscoring the importance of ongoing research and analysis in this field.

Have you noticed ChatGPT getting lazy? If so, please share.

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