Addressing the Elephant in the Room

Hello to all you LocalLLaMA jockeys,

I want to address something that has been on my mind for a while now, and I am curious to see if anyone else shares my sentiment.

Having experimented with various "homebrew" LLMs, I have found myself continually comparing their performance to ChatGPT. After all, aside from the privacy and control aspects, the whole thing has to measure up, right?! I have to be honest, it seems that none of my custom concoctions come close to the answer quality that ChatGPT provides. Whether it's the depth of understanding, the ability to maintain context, or just the general responsiveness - my RTX-4090 ain't got shit on ChatGPT for a normal conversation - even when I'm extra patient.

Of course, there are many factors to consider, such as the vast resources available to OpenAI for running the thing, and the various proprietary techniques and algorithms they might be using. Still, I can't help but feel a bit disheartened by the noticeable gap in performance.

I'd like to open up a discussion about this. Am I missing something or is it just my expectations that are way off? For those who have managed to significantly narrow the gap, what techniques or strategies did you use? Is there a particular aspect where you think some Vicuna breed can provide a decent conversation that is worth all the tinkering or am I better off going to Goolge's cloud option to play with their PaLM2 stuff?

Looking forward to hearing your thoughts and experiences on this matter.