I think the better argument is about the direction of change versus the current magnitude.
If we are to believe that the models will get bigger, use more tokens, work for longer, this calculation can easily become very very skewed in the other direction.
Consider an agentic system that runs continuously for 6 hours. It is possible this system processes billions of tokens. That could more than equal a transatlantic flight in this hypothetical world.
Now compare this with non-AI work, like a CRUD app. Serving millions of queries in that same period would consume a tiny fraction of what ChatGPT consumes.
Rather than being a “win” for AI, the fact that we’re even 3 or 4 orders of magnitude away from this being a problem means that its already grounds to be concerned.
If we are to believe that the models will get bigger, use more tokens, work for longer, this calculation can easily become very very skewed in the other direction.
Consider an agentic system that runs continuously for 6 hours. It is possible this system processes billions of tokens. That could more than equal a transatlantic flight in this hypothetical world.
Now compare this with non-AI work, like a CRUD app. Serving millions of queries in that same period would consume a tiny fraction of what ChatGPT consumes.
Rather than being a “win” for AI, the fact that we’re even 3 or 4 orders of magnitude away from this being a problem means that its already grounds to be concerned.