So, I guess it depends on how close to the tail you consider the “best startups”. Google, for instance, had Larry Page and Sergei Brin at 25 when they formed it. It does seem like, taken literally, younger = better.
However, I imagine most people, if they were to consider this question, wouldn’t particularly care about the odds of being the next Google vs. being the next Atlassian—both would be considered a major success if they’re thinking of starting a startup! But someone like Paul Graham actually would care about this distinction. So, in this case, I’d say that the LLM’s response is actually correct-in-spirit for the majority of people who would ask this query, even though it’s factually not well specified.
This implies potentially interesting things about how LLM’s answer queries—I wonder if there are other queries where the technically correct answer isn’t the answer most people would be seeking, and the LLM gives the answer that isn’t maximally accurate, but actually answers most people’s questions in the way they would want.
Interestingly, the average startup founder does appear to be in their 40′s (A quick Google search says 42 for most sources but I also see 45), and the average unicorn (billion-dollar) startup founder is 34. https://www.cnbc.com/2021/05/27/super-founders-median-age-of-billion-startup-founders-over-15-years.html
So, I guess it depends on how close to the tail you consider the “best startups”. Google, for instance, had Larry Page and Sergei Brin at 25 when they formed it. It does seem like, taken literally, younger = better.
However, I imagine most people, if they were to consider this question, wouldn’t particularly care about the odds of being the next Google vs. being the next Atlassian—both would be considered a major success if they’re thinking of starting a startup! But someone like Paul Graham actually would care about this distinction. So, in this case, I’d say that the LLM’s response is actually correct-in-spirit for the majority of people who would ask this query, even though it’s factually not well specified.
This implies potentially interesting things about how LLM’s answer queries—I wonder if there are other queries where the technically correct answer isn’t the answer most people would be seeking, and the LLM gives the answer that isn’t maximally accurate, but actually answers most people’s questions in the way they would want.
There’s most definitely a category of people who would think a billion-dollar startup was decidedly not best, and in fact had failed their intention.