LanguageGamer
Joined 10 years ago
Joined 10 years ago
This sort of methodology sounds sketchy to me - how much can we really learn from this? Does it reproduce? If it does, how do we know there isn't some other cause?
[0] https://commercial.ft.com/our-products/financial-times/ [1] https://abcnews.go.com/Business/IndustryInfo/story?id=342198... [2] https://www.census.gov/library/publications/2023/demo/p60-27...
The geometric mean (6.9) is all that really matters for investors, not the arithmetic mean (8.4) - the arithmetic mean under-weights the importance of negative years to long term performance.
For example, if the market is down 20% one year and up 20% the next year, the arithmetic mean will be 0%, but you'll be down 4% (0.8*1.2 = 0.96), which is reflected in the geometric mean of (about) -2%.
https://www.thelancet.com/journals/lanpsy/article/PIIS2215-0...
My experience would suggest shipping higher quality software is a lot cheaper in the long run, but has up-front costs that often times startups can't afford.
The cost of nuclear energy has been flat for decades, but the cost of sources like solar has been plummeting. Nuclear doesn't have much of change without some technological break through.
In other words, it's not clear to me LLMs are going to eat into the market share of search engines, rather than just providing a tool with largely orthogonal use cases. But we'll see how the tech develops from here.