| Title | How Much Can We Afford to Forget, if We Train Machines to Remember? |
|---|---|
| Contributor | Gene Tracy (author) |
| DOI | https://doi.org/10.32376/3f8575cb.c0097cd0 |
| Landing page | https://www.mediastudies.press/pub/tracy-afford |
| Publisher | mediastudies.press |
| Published on | 2021-07-15 |
| Short abstract | WHEN I WAS a student, in the distant past when most computers were still huge mainframes, I had a friend whose PhD advisor insisted that he carry out a long and difficult atomic theory calculation by hand. |
| Long abstract | WHEN I WAS a student, in the distant past when most computers were still huge mainframes, I had a friend whose PhD advisor insisted that he carry out a long and difficult atomic theory calculation by hand. This led to page after page of pencil scratches, full of mistakes, so my friend finally gave in to his frustration. He snuck into the computer lab one night and wrote a short code to perform the calculation. Then he laboriously copied the output by hand, and gave it to his professor. Perfect, his advisor said—this shows you are a real physicist. The professor was never any the wiser about what had happened. While I’ve lost touch with my friend, I know many others who’ve gone on to forge successful careers in science without mastering the pencil-and-paper heroics of past generations. |