Why does Google Gemini give less information each time?

Understanding the Decline in Response Detail from Google Gemini: An Exploration

In the evolving landscape of artificial intelligence and machine learning, tools like Google Gemini have become invaluable for writers, educators, and researchers alike. Recently, users have observed a perplexing issue: the AI’s responses appear to diminish in depth and detail over successive interactions. This article aims to shed light on potential reasons behind this phenomenon and offer guidance for optimizing your experience with Google Gemini.

Observations from User Experiences

A common pattern has emerged among users, particularly those employing Google Gemini for creative and educational purposes. Initially, when inputting a new prompt—be it a chapter of a book or a paragraph from classwork—the AI responds with comprehensive insights. For instance, during a writing project, the first interaction might yield detailed feedback, specific questions, and a discussion of preferences and uncertainties.

However, subsequent prompts—especially ones that follow after clearing the chat history or starting anew—often receive markedly less information. Responses tend to be brief, sometimes merely suggesting to “show more description” or highlighting a single aspect without further elaboration. In classroom settings, similar behavior manifests: initial responses provide extensive guidance, while later ones are minimal, sometimes even dismissive of further questions.

Potential Causes for Diminished Responses

1. Context Reset and Loss of Prior Information

One of the primary reasons for decreasing response detail is the management of conversational context. Clearing chat history resets the AI’s memory of previous interactions. When prompts are presented without the surrounding context, the AI may default to more concise or generic replies. This behavior ensures efficiency but can limit depth if not managed carefully.

1. Model Behavior and Response Optimization

Language models are often designed to respond concisely after initial detailed interactions, especially when they interpret subsequent prompts as clarifications or follow-ups. If the prompts explicitly request detailed feedback, the AI is more likely to provide comprehensive responses; otherwise, it might produce briefer outputs.

1. Token Limitations and Processing Constraints

AI systems operate within token limits (the amount of text they process at once). As conversations progress, these limits can influence response length, especially if the model perceives the prompt as a brief or low-priority query in comparison to the initial detailed input.

1. User Interface and Settings

Some AI platforms or implementations include settings that modulate the response length or detail level. If such settings are enabled, they might cause response brevity after initial interactions, particularly if the system is configured for efficiency over depth.