This looks incredibly cool; I'm wowed by the fact that the model has learnt to negate words in if-else statements, though I struggle to think of a case where that particular completion would have been useful.
At the same time, I'm less excited about the fact that the model is cloud-only, both for security/privacy reasons and because I spend a not-insignificant amount of my time on limited-bandwidth/high-latency internet connections.
I'm also curious as to why the survey didn't ask about GPU specifications; most of the time I use my laptop to code whilst plugged in, and I'd happily use only LSP completions when on battery, so power consumption wouldn't be an issue (though fan noise might), and allegedly my GPU (a GTX 1050) can pull off almost 2 TFLOPs, which is well over the "10 billion floating point operations" mentioned in the post.
The issue is that the current OOM killer doesn't support this usage at all.
To extend the analogy: what do you do if grandma comes and fills your house with stuff? You need space to work, so you go and drop it off at the self storage place, but what if she just keeps filling your house up?
The OOM killer will do absolutely nothing until both your house and the whole self storage place are totally full. By that point, you've spent a huge amount of time just driving to and from self storage, so you haven't had time to do any actual work; it would probably have been better to tell grandma that you don't want any more stuff once she filled up your house for the first time.
At the same time, I'm less excited about the fact that the model is cloud-only, both for security/privacy reasons and because I spend a not-insignificant amount of my time on limited-bandwidth/high-latency internet connections.
I'm also curious as to why the survey didn't ask about GPU specifications; most of the time I use my laptop to code whilst plugged in, and I'd happily use only LSP completions when on battery, so power consumption wouldn't be an issue (though fan noise might), and allegedly my GPU (a GTX 1050) can pull off almost 2 TFLOPs, which is well over the "10 billion floating point operations" mentioned in the post.