jonnycat
Joined 16 years ago
Joined 16 years ago
Although that's really selling it short - it's so much more than that! But in the context of this conversation, it's a good place to look.
And that’s completely fine. I was never forceful about it and they have their own deep interests in things that I just never got into or understood. I just find it surprising that in some families, these exceptional skills and interests are so readily passed from one generation to the next.
In fact, if the author feels confident in this theory, I suggest they replace the blog post with this AI-generated bullet-point summary I just made...
Consumers hate ads, but they hate paying for things even more apparently.
If you believe, as I do, that these things are a lot further off than some people assume, I think there's plenty of time to build a successful business solving domain-specific workflows in the meantime, and eventually adapting the product as more general technology becomes available.
Let's say 25 years ago you had the idea to build a product that can now be solved more generally with LLMs–let's say a really effective spam filter. Even knowing what you know now, would it have been right at the time to say, "Nah, don't build that business, it will eventually be solved with some new technology?"
If you can see past some of the more dubious, overly technical-sounding details and treat it as a metaphor, there is for sure a "behavioral landscape" that we all find ourselves in, filled with local minimal, attractors/basins and steep hills to climb to change our own behaviors.
Thinking about where you are and where you want to be in the behavior landscape can be a useful mental model. Habit changes like exercise and healthy eating, for example, can be really steep hills to climb (and easy to fall back down), but once you get over the hump, you may find yourself in a much better behavioral valley and wonder how you were stuck in the other place for so long.
Of course, other kinds of life are possible, which would require other "just right" conditions - but in that case, we'd all be living in that universe, marveling at those coincidences!
Again, I definitely trust them to get it right in the long term, but in the meantime, the progress has been a bit confusing to me.
The reason is that objects in collision detection systems tend to move relatively small steps between frames, meaning you can keep lists from the previous frame that are already mostly sorted. For sorting these mostly sorted lists, insertion sort tends towards O(n) while Quicksort tends towards O(n^2)!