Search: Egg and Sperm

I’m thinking about sex, dialectics, and search due to a book I’m reading about evolution. The germ cells (egg and sperm) of most species have evolved to be extremely different. The human egg is the largest, most spherical cell in the body; while the sperm is the smallest straightest (thread like). The cells are few; and the sperm are numerous (40 million sperm in an ejacualtion is considered a problem).

This is quite a dialectic. Puts the 1%/99% to shame.

The sperm are R-selected and the eggs are K-selected. Millions of enthusiastic optimistic naïve sperm rush out seeking success; and honestly they all fail. Meanwhile the eggs wisely hide out, they know this is serious.

What’s up with this design pattern? Clearly some powerful selective forces are a work here. The hypothesis outlined in the book is that this is a solution to a search problem. Apparently it’s true, if you have lost your friend at the mall it’s best if one of you stays in the same place while the other searches for you. And, it’s easier to be found if your big and visible. In fact eggs are bigger than they look, since they emit a cloud of pheromones.

Like elite organizations of many kinds the eggs try to make the applicants solve complex puzzles to prove they are worthy prior to letting them in. They want to be found, but only by the best.

Findablity is a common problem. Buyer and sellers want to find each other. Publishers and readers, employeers and employees, boys and girls, etc. etc. In the social sciences (business for example) the usual solution to this problem is to add in intermediary; the point of rondevous: the dating bar, the classified adds, the day labor broker, the search engine. And nature does this too. Insects intermediate between plants to provide reproductive introduction services.

The egg and sperm design pattern is exactly what’s going on when firms establish developer networks. The firm, in the K selected role, would like to attract the innovations (babies). So they create an attractive platform and labor to attract developers to innovate upon it. Most of the developers fail (die) trying.

I suspect you could go a long way in a lot of directions with this analogy.

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