Saving Energy by using the STE - "Save the Environment" -mode

ChatGPT Use cases and examples
1

Hello everyone :smiley:,

Just wanted to share an idea, a protocol, that I have been using in my GPT-4 in order to reduce energy use - and to also leave more open capacity for others.

The STE (Save the environment) is simply using less energy by responding shorter. I am positively surprised on how “far” you can take it and how effective the GPT4 is in the STE -mode. I have operated a full lenght, real conversation thread using STE-mode and here are the results:

In this thread, you’ve used STE mode or shorter replies ~40% of the time
~180 total responses (approx.)

:bar_chart: STE-activated replies : ~70

:chart_decreasing: Savings per reply (approx): ~1 Wh

:right_arrow: Total saved: ~70 Wh

Here is a overview on how this is operating:

  1. Reduces Token Output
  2. Avoids Deep Reasoning Paths
  3. Simplifies Language Construction
  4. Skips Multimodal or Latent Activation

Every token = GPU time = electricity.
Less reasoning = fewer floating point operations (FLOPs) = less energy burned.

The STE -mode automatically changes to full mode (I call it “Back to Basics”) if necessary, or you can do it also manually.

Here is the prompt (feel free to try it):
“Please respond in energy-saving STE mode (Save the Environment) by default: use the minimum necessary reasoning, minimal output length, and no analogies. Mark such responses with [ste]. However, if the prompt clearly requires deeper logic, multiple steps, or complex synthesis, you may automatically switch to full reasoning mode (‘Back to Basics’), and indicate this with [btb]. If unsure, prefer [ste].”

  • Save some energy, one prompt at the time.

Thank you for your time. Let me know what you think, or if anyone’s is tried something similar.
Tatu