ABOUT THIS EPISODE
“The rules of the game are different in tech,” argues — and has long argued, despite his views not being accepted at first — W. Brian Arthur, technologist-turned-economist who first truly described the phenomenon of “positive feedbacks” in the economy or “increasing returns” (vs. diminishing returns) in the new world of business… a.k.a. network effects. A longtime observer of Silicon Valley and the tech industry, he’s seen how a few early entrepreneurs first got it, fewer investors embrace it, entire companies be built around it, and still yet others miss it… even today.
If an inferior product/technology/way of doing things can sometimes “lock in” the market, does that make network effects more about luck, or strategy? It’s not really locked in though, since over and over again the next big thing comes along. So what does that mean for companies and industries that want to make the new technology shift? And where does competitive advantage even come from when everyone has access to the same building blocks (open source, APIs, etc.) of innovation? Because Arthur — former Stanford professor, visiting researcher at PARC, and external professor at Santa Fe Institute who is also known as one of the fathers of complexity theory in economics — has written about the nature of technology and how it evolves, observing that new technology doesn’t come out of nowhere, but instead, is the result of “combinatorial” innovation. Does this then mean there’s no such thing as a dramatic breakthrough?!
In this hour-long episode of the a16z Podcast, we (Sonal Chokshi with Marc Andreessen) explore many of these questions with Arthur. His answers take us from “the halls of production” to the “casino of technology”; from the “prehistory” to the history of tech; from the invisible underground autonomy economy to the “internet of conversations”; from externally available information to externalized intelligence; and finally, from Silicon Valley to Singapore to China to India and back to Silicon Valley again. Who’s going to win; what are the chances of winning? We don’t know, because it’s a very different game… Do you still want to play?
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