All extropic systems -- economy, nature and technology -- are governed by self-accelerating feedback cycles. Like compounding interest, or virtuous circles, they are powered by increasing returns. Success breeds success. There is a long tail of incremental build up and then as they keep doubling every cycle, they explode out of invisibility into significance. Extropic systems can also collapse in the same self-accelerating way, one subtraction triggering many other subtractions, so in a vicious cycle the whole system implodes. Our view of the future is warped and blinded by these exponential curves.
But while progress runs on exponential curves, our individual lives proceed in a linear fashion. We live day by day by day. While we might think time flies as we age, it really trickles out steadily. Today will always be more valuable than some day in the future, in large part because we have no guarantee we'll get that extra day. Ditto for civilizations. In linear time, the future is a loss. But because human minds and societies can improve things over time, and compound that improvement in virtuous circles, the future in this dimension is a gain. Therefore long-term thinking entails the confluence of the linear and the exponential. The linear march of our time intersects the cascading rise and fall of numerous self-amplifying exponential forces. Generations, too, proceed in a linear sequence. They advance steadily one after another while pushed by the compounding cycles of exponential change.
Balancing that point where the linear crosses the exponential is what long-term thinking should be about.
An off-duty cop got into a fight with a group of children who walked on his lawn, dragged a 13-year-old unarmed boy into his yard, pulled his firearm, then fired a shot. Thankfully, he missed. The incident in Anaheim, California, was captured on camera and has already led to protests. Christian alleged in the video […]
We’ve all seen the uncanny, not-quite-there art produced by new AIs. Why Matt Reynolds reports on an area computers might be expected to excel at creatively: programming themselves. And this one’s doing it the same way humans do, by stealing and remixing. DeepCoder uses a technique called program synthesis: creating new programs by piecing together […]
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Python is immensely popular in the data science world for the same reason it is in most other areas of computing—it has highly readable syntax and is suitable for anything from short scripts to massive web services. One of its most exciting, newest applications, however, is in machine learning. You can dive into this booming […]
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