But it does work. If you open a cafe and want to let people know the cafe is there, sending an ad (either by mail or on Facebook or via Google) to 10,000 people in your zipcode is going to be more effective than sending it to 10,000 random people around the planet.
Agreed. The call is honored by time but not execution.
The story is used to teach the wisdom of evaluating a plan on not only how desirable the outcome would be but also how it can be executed. It provides a moral lesson about the fundamental difference between ideas and their feasibility, and how this affects the value of a given plan.
But they might not be able to reach people who are hidden under the rubble of a collapsed building, for example. Ideally the drones would be built using nanotechnology, allowing them to be so small that they're almost invisible. Of course, coordinating their movements would require quite a powerful AI...
I always saw the hormones that regulate our emotions as primitive forms of memory, older than neurons. So an organism can remain in a certain state for a while.
There is also the possibility that RNA is used for memory:
This article [1] has a section with several references on that, with the most used technique [2] being depicted in fig. 3 (this is from 2016 so there might be a more recent technique around now).
The basic principle is to mix a solution with lipids and one with the mRNA and pump it through a channel with herringbone-shaped incisions that generate turbulence in the fluid. Apparently, the turbulence makes lipids surround the mRNA and stick together to form the nano-particle.
So to quickly summarize they use fluid dynamics and force and whatever sticks through this process will be useful.
I wonder what the rate of lipid-surrounded mRNA is after the process. Say you fire 100 mRNAs through this construct, will 90 of them be surrounded by lipids afterwards? Or 30? Or 100?
That was a great article! The last paragraph, however:
"By the way, Knuth is interested in these algorithms mainly for the interesting mathematical problems (...) not because they’re in any way efficient algorithms! "
Made me wonder, these kind of algorithms, where there is a lot of comparing and swapping of adjacent records might be more efficient on a tape-based architecture. Or an architecture with a lot of prefetch caching.
Insertion sort is known to be the fastest option for small ranges, which is why it often is the sorting option hybrid sorts switch to for that case (like when the partitions in quicksort or merge sort are small enough).
AFAIK, this is mainly because even though it is expected O(n²), it has a really tiny overhead because insertion sort is incredibly simple, so for small enough n it wins. However, being very cache-friendly is also part of it (it's a linear search over the array).
IIRC some people found similar results for bubble sort.
