Longreads + Open Thread

Precision, Art, Psychic Scams, Attention, Scenius, Discount Rates, Macquarie, Tech Adoption



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In last week's Longreads, Calvin McCarter raises a fun question:

There was an interesting conversation on Twitter today about what adoption rate says (or does not say) about the quality of a technology: https://twitter.com/charleskfisher/status/1682832279284899845. Francois Chollet remarked on the slow rollout of self-driving AIs since 2016, as evidence that they were not better than humans in 2016. Charles Fisher responded that this is not sufficient evidence, due to the inherently slow pace of tech adoption. This makes me curious whether we should expect tech adoption rates to follow a super-exponential distribution, such as the "unreliable friend distribution", or the exponential distribution with its memoryless property? For example, does each passing year since 2008 where blockchains are not widely used for non-speculative purposes provide evidence against them ever being used for non-speculative purposes? How many technologies have had slow beginnings and then eventually taken off? One might might point to the failure of IBM's Watson, followed by the success of ChatGPT, but I'd argue that these were fundamentally different technologies.

There are some cases where a technology exists for a long time before it finds a use case with positive feedback loops, and then grows fast once those are in place: using computers to design better computers is one example, using the output from crude oil to 1) fuel cars, 2) build roads, 3) increase the efficiency of oil exploration, and 4) sequester CO2 by using it to pump more oil might be another. And sometimes, adoption is a bet on experience curves: if you expect a product to get much cheaper with scale, you can underwrite what looks like overinvestment in it.

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