Stuart J. Russell (he of the AI textbook) claims in Human Compatible that YouTube is already an example of a runaway feedback loop between AI (YouTube's recommender "algorithm") and humanity (viewers, content producers, YouTube staff, and society at large). The AI doesn't have a body, a voice, a conscience, or a purpose yet it is busily working away to maximize engagement by changing people's minds, and in particular by bringing extremism into mainstream discourse.
(It seems to me that framing it this way does seem to absolve YouTube executives of responsibility by making the AI, not them, seem like the agent.)
Inferring pronunciation from spelling is very regular in French; the reverse, not so: there may be many ways to spell a sound like “o”, each with a different meaning.
This trend is far older than the AI era. The British magazine Private eye for many years in the 1990s had a running joke in which each issue displayed the new logos of old companies that had spent a fortune on rebranding. All of them were variations on circles.
Naomi Klein in her book No Logo interprets it as a form of abstraction away from the passé and less profitable business of whatever concrete task those industries used to do, and towards outsourcing, branding, and financialization as an end in itself.
Understood. My point is that the job requirements are almost mutually exclusive: must be physically and mentally fit enough for arduous travel and harsh work, yet basically suicidal.
I'd be surprised if there's a single person alive who would volunteer for a suicide mission to a miserable cold dark planet and could travel there for nine months in a tin can through a harsh radiation/muscle atrophy/psychological environment and arrive in any condition to conduct useful scientific work.
It seems quite common for the infrastructure teams to put up a dashboard just to keep a sense of what is going on, but it is then misinterpreted as a “leaderboard” and encourages the most prolific users to find creative ways to squander more to stay the “winner”. Management is slightly disappointed by the waste but also happy that staff are engaging with their future replacements.
For a while we’ve been fixing telemetry-reported crash bugs in the project I maintain, and now hardware bugs are showing up with some frequency. I was amazed how common they are. Sometimes data values (e.g. SP register) are corrupted, but other times even infallible operations (e.g loads of rodata constants) crash, indicating that the instruction itself was corrupted. So, yeah, I believe you’ll eventually see UUID collisions, but not because the underlying cryptanalysis was wrong.
Does the ground source heat up (or cool down) over time, making it less effective? The deep ground is very well insulated, which is why after a century of operation the London Underground is 10 degrees warmer. I wonder whether GSHP users need to balance their load by (say) consuming more heating than they actually need in winter so that summer cooling remains effective.
Another situation to avoid the XOR trick, even when registers are tight, is when swapping pointers in a garbage-collected language, since the intermediate bit patterns are invalid pointers: if a GC mark phase occurs at that moment, you might lose some objects, or spuriously mark others as live.
I once wrote a contract document in PostScript that changed the wording based on the date. Two parties could cryptographically sign an agreement in the document, which would change when printed on a later date.
One of the reasons we don’t use PostScript so much any more.
Also weird phrasing: "a staggering 1.8 degrees" begs the reader to think of it as a large number (which in fact it is, as you point out) yet their intent seems to be, ironically and paradoxically, to diminish it.
(It seems to me that framing it this way does seem to absolve YouTube executives of responsibility by making the AI, not them, seem like the agent.)