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Livingston: Why do you think they thought that way Levchin: I think there s a very strong power of default where, to them, certain behavior to solve a particular problem is well understood. There are people that make careers out of risk management in big banks. They know that what you do is this and you don t do that. The other part, I think, is that a lot of them are public companies. We didn t go public until we had the fraud thing figured out. Somebody like Citibank or anyone with a substantial public visibility announcing that they are suddenly bleeding out $10 million a month in fraud would send serious shocks through the investor base. But I think, even if they did that, it s likely they wouldn t have been successful because we had talked to a lot of them both as a potential acquirer and as partnership potential none of them had actually ever gone to the sort of stuff that we did for our anti-fraud work.

As you can easily see, as the selling price goes up, demand falls off steadily. But total revenue rises for a while, peaking at a sales price between $500 and $550 dollars. After that, total revenue begins to fall off. For those who like pictures, the graph in Figure 4-1 illustrates the data in Table 4-1.

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that are clearly not in sight of the camera because they are not inside the viewing frustum of the camera. More advanced solutions exist in the domain of occlusion culling, where the 3D world is divided into regions corresponding to the 3D world itself. For example, to store the objects inside a house, volumes corresponding to the rooms are used instead of symmetrical cubes. These rooms are connected to each other at positions corresponding to the doors. This way, you can perform checks to see whether a room is actually in sight of the camera or whether a wall or closed door is blocking the sight.

data and I said read track 0; stuck in the other floppy and said write track 0, read track 1, write track 1. There were 36 tracks I had to switch floppies back and forth. When I got done, I m looking at these two floppies that look just the same. And I decided that I might have written onto the good one from the bad, and I did. So I had lost it all. I went back to my hotel room. I slept for a while. I got up about 10:00 a.m. or so. I sat down and, out of my head and my listings, recreated everything, got it working again, and we showed it at the show. It was a huge hit. Everybody was saying, Oh my god, Apple has a floppy! It just looked beautiful, plugged into a slot on our computer. We were able to say run Color Math, and it just runs instantly. It was a change in time. But the real eureka moment for me was the very first time I ever read data back. I wrote it on the floppy, which was easy but read it back, got it right. I just died.

Livingston: Where were you when you did this Wozniak: I was actually in Apple s office for the entire floppy disk creation. We

were in that office building that I described earlier. There were about five of us in there, then there were about eight or ten. Then I moved out to a second little room that we got a smaller room in the same office complex but down in another building. Randy Wigginton and I were in there, and Captain Crunch who developed the phone board for me.

Your ideal selling price is at the peak of the revenue curve the minimum amount of work for the maximum amount of dollars. The data presented in Figure 4-1 creates a nice, neat, symmetrical curve. The real world is certainly not so neat. As your price rises, your sales may not drop off in a smooth curve. That curve may flatten out for a while or drop off suddenly like the edge of the continental shelf. It would be nice if there was some way to calculate precisely the demand and total revenue as unit price changed. But there isn t. You can approximate the revenue curve by using the experience of similar products. But that data, if it exists, is hard to come by. And how many products are there similar to yours But this idea of a revenue curve is still a useful concept when trying to decide on a selling price. Remember, your goal is not to sell as many as possible, but rather to generate as much revenue as possible. I had a partner once who suggested that instead of selling our product at $1,000 to $3,000, depending on options, we should price it at $1,000,000. It would be a tough sell. But we d only have to sell one. We gave it some serious thought.

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