How can you decide what should you have for food

Deciding what should we have for food is a classic problem dating back to the dawn of humanity, maybe even life itself.

Every person has had to encounter this problem at some point, which is incredibly unfair since this is harder than proving the reimann hypothesis.

Nevertheless, I am trying to do something that has never been done before, trying to provide a clear an concise way of solving this, with minimal violence resulting from the finished meal's reception.

I propose we use a state-of-the-art technique, utilizing multiple datacenters worth of compute and memory and terabytes or even petabytes of data.

We may use the transformer architecture for machine learning, create a multi trillion data point model using the aforementioned data, which is obviously trained on, but not limited to different kinds of recipes from the internet, finetune it for text generation, and then further finetune it for a conversation with a human.

Then, we may feed it to a similarly trained model, but trained on filtered speach data to convert that output given by the previous model to this "text to speach" model, convert that output to analog and send it through precisely caliberated coils, making them vibrate a membrane with a purpose of producing sound.<br /> Upon feeding this multi model architecture with a text based input such as "I have the following ingredients and this much time, what can i make for dinner", I should be able to do a decent-ish job,