(Roughly) Daily

“Reality is frequently inaccurate”*…

Machine learning and what it may teach us about reality…

Our latest paradigmatic technology, machine learning, may be revealing the everyday world as more accidental than rule-governed. If so, it will be because machine learning gains its epistemological power from its freedom from the sort of generalisations that we humans can understand or apply.

The opacity of machine learning systems raises serious concerns about their trustworthiness and their tendency towards bias. But the brute fact that they work could be bringing us to a new understanding and experience of what the world is and our role in it…

The world is a black box full of extreme specificity: it might be predictable but that doesn’t mean it is understandable: “Learn from Machine Learning,” by David Weinberger (@dweinberger) in @aeonmag.

(image above: source)

* Douglas Adams, The Restaurant at the End of the Universe


As ruminate on the real, we might send carefully-computed birthday greetings to Grace Brewster Murray Hopper.  A seminal computer scientist and Rear Admiral in the U.S. Navy, “Amazing Grace” (as she was known to many in her field) was one of the first programmers of the Harvard Mark I computer (in 1944), invented the first compiler for a computer programming language, and was one of the leaders in popularizing the concept of machine-independent programming languages– which led to the development of COBOL, one of the first high-level programming languages.

Hopper also found and documented the first computer “bug” (in 1947).

She has both a ship (the guided-missile destroyer USS Hopper) and a super-computer (the Cray XE6 “Hopper” at NERSC) named in her honor.


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