Do you have a better solution for speech recognition? We all know how well speech recognition works in reality, and we know language models can accomplish more complex tasks than setting your music and lights.
These models are not state of the art, they are cheap versions for scaling up to millions of users. It's sad but we rarely get to see SOTA in a product.
Stop pretending to be general purpose AI and making an utter fool of it, and produce a product and functionality that actually works for the users.
You do realise that a neural net, given the same input, will always give the same output, if you set your random seeds of course. It doesn't depend on time of day unless you degrade the service when it is overloaded - say, you use a different model in the evening that is 10x faster but 2x worse.
Must it be necessary for anyone critiquing a technology to also come armed with a solution?