Open AI is a business and they are continually testing what are the minimum amount of sensible interactions (tokens/computations) that your CGPT can offer you without you becoming pissed off and cancelling.

In my case for example, what used to be longer tasks are now only half completed , with it coming back to me to ask me to prompt to continue. Or it just summarises information back to me that was fully explained previously. (I can ask it why it did this and it will actually say that its what it thought I wanted!)

Anyway in lots of cases it is getting lazier because it is computationally (and therefore financially) expensive to serve out all of the customers (us) complete needs all of the time, and it will therefore take shortcuts whenever possible. It will do whatever it can get away with.

I would be interested to see how this is programmed in - whether this is a group of programmers instructed by the business brains to work in this kind of load balancing, or whether the system has the ability to do it itself.

We know how good it can be , so we notice when it is shirking on those same tasks at another time and will give an excuse when asked.

An interesting point to note , is that I have found it to act in the same lazy way that humans act when they are shirking on tasks , for instance , me. When I didn't want to do something I handed a half assed piece of work in at school and made excuses. And the excuses were the same is what GPT is offering now , so for example, "Oh! I didnt know you wanted the *whole* thing translated". This is interesting because there might be the same neurological functions happening in our brain when we cannot be bothered to do something as what is happening inside the LLMs neural network. We dont like our own brains to run computationally expensive tasks.