Pinboard (jm)
https://pinboard.in/u:jm/public/
recent bookmarks from jmMDN can now automatically lie to people seeking technical information · Issue #92082023-07-01T10:54:30+00:00
https://github.com/mdn/yari/issues/9208
jmThe generated text appears to be unreviewed, unreliable, unaccountable, and even unable to be corrected. at least if the text were baked into a repository, it could be subject to human oversight and pull requests, but as best i can tell it's just in a cache somewhere? it seems like this feature was conceived, developed, and deployed without even considering that an LLM might generate convincing gibberish, even though that's precisely what they're designed to do.
and far from disclaiming that the responses might be confidently wrong, you have called it a "trusted companion". i don't understand this.
Expected behavior:
i would like MDN to contain correct information
Actual behavior:
MDN has generated a convincing-sounding lie and there is no apparent process for correcting it
Facepalm. (via Abban)]]>mozilla fail llm ai ml features mdnhttps://pinboard.in/https://pinboard.in/u:jm/b:a73dc5ca5344/Amazon S3 is quietly deprecating BitTorrent support2021-06-14T15:40:39+00:00
https://github.com/awsdocs/amazon-s3-userguide/commit/0d1759880ccb1818ab0f14129ba1321c519d2ac1#diff-72be9d82d9be9bda6a297a4fbd11aca66ecde97e4f90de6f86bdf95c5f6b72c0
jmbittorrent aws s3 deprecation featureshttps://pinboard.in/https://pinboard.in/u:jm/b:19ac597c23ba/12 Signs You’re Working in a Feature Factory2020-02-17T13:00:29+00:00
https://cutle.fish/blog/12-signs-youre-working-in-a-feature-factory
jmI’ve used the term *Feature Factory *at a couple conference talks over the past two years. I started using the term when a software developer friend complained that he was “just sitting in the factory, cranking out features, and sending them down the line.”
heh, this rings a bell....]]>features product-management agile teams work management product companies prioritization planninghttps://pinboard.in/https://pinboard.in/u:jm/b:c4f2ce936374/Abusing hash kernels for wildly unprincipled machine learning2013-04-04T23:01:51+00:00
http://jeremydhoon.github.com/2013/03/19/abusing-hash-kernels-for-wildly-unprincipled-machine-learning/
jmai machine-learning python data hashing features feature-selection anti-spam spamassassinhttps://pinboard.in/https://pinboard.in/u:jm/b:28d641a0b96e/