Yes I was specifically thinking of the latter with larger models, I think many many shot ICL still tends to outperform but you're right it's worth trying both for your use case
I am building in the mortgage origination space and have these sorts of enhancements on the drawing board... you hit the nail on the head that the bottleneck will be in QC and legal review, as 3rd-parties (especially regulators) may want to manually see the data you used to reach the conclusions you did. Although I'm still digging. You'd be interested in what we're creating btw, it's a crypto-based mechanism that enables instant digital mortgage origination, we should chat!
Today's revenue is not tomorrow's, and companies are valued based off of the future. Where did Amazon's revenue come from (and still primarily, afaik) for most of its life?
Your conclusion may be true but your examples aren't. You can definitely predict the stock market based on past prices, and I suspect you can with weather as well.
TikTok's success is primarily about the creator tools, not the viewing experience. Making video editing mobile-friendly and accessible to more people is what enabled the proliferation of short-form content.
Jhanas are achieved a particular way and should be readily accessible once your concentration is strong enough (yours likely is). You may have not experienced them if you haven't accidentally pulled the right levers, so to speak. There are a few guides online of what to do, I suspect you'd succeed quickly
you don't need access to the weights though, unless I missed something? this is akin to the various groups using GPT-3.5/4 to generate data for fine-tuning smaller models