* By some accounts Toyota's electronic throttle control system (ETCS) had bugs that could cause sudden unintended acceleration
* The Boeing 787 Dreamliner experienced an integer overflow bug which could shut down all electrical generators if the aircraft was on for more than 248 days
* In early 2019, the transportation-rental firm Lime discovered a firmware bug with its electric scooters that can cause them to brake unexpectedly very hard, which may hurl and injure riders.[6
* A bug in the code controlling the Therac-25 radiation therapy machine was directly responsible for at least five patient deaths in the 1980s when it administered excessive quantities of beta radiation
Yeah and that's what, 0.1% of all software devs globally that can potentially do physical harm? Most of us just hurl data between places and worst damage is financial. You can't even compare the scales.
If you're a construction engineer, any serious flaw in any building you design can kill, sometimes hundreds.
How many engineers of those few cases you mention went into jail and were forbidden to work in software industry forever?
- teachers : if you have let's say 30 students, you need one teacher, in you have 300 you probably need 10 teachers. I don't know how can you one person deal with 300 students giving them the required attention. Since you have the school program you can start paralyzing the tasks.
- doctors : If you have 10 sick peoples... 1 doctor, with 100 you probably need 10 doctors. A doctor need time with a single patient to study the case.
There is probably plenty of good examples, but not that ones.
About building softwares, even if you pick the right guys and split the task properly (which requires peoples, time and a high level of understanding) and let peoples work on their own, you lead to inconsistency. Splitting an existing task to add new developers and save time requires redesign and headaches to avoid incompatibilities, probably breaking new things or requiring some rework in the work done by the others.
I find it more irritating when people try to score greybeard points by saying *nix (or Unix) when it's obvious that they're talking about a Linux-only mechanism and quite possibly haven't ever used Unix (or a direct derivative).
Also, the most popular Unix-like OS (far more than Linux) is macOS, basically the least “leet greybeard affectation” thing I can imagine. Your irritation is way off base.
Perhaps nothing? I was responding to the complaint in general terms.
> Your irritation is way off base.
Please allow me to feel irritated when people refer to obvious Linux things as something that's supposedly got something to do with Unix. It happens often enough.
Most popular Unix-like OS on consumer devices is Linux (Android).
Most popular Unix-like OS on servers is Linux.
Most popular Unix-like OS in embedded is Linux.
Most popular Unix-like OS on supercomputers is Linux.
Most popular Unix-like OS on IBM PC compatible computers or notebooks is MS Windows with WSL.
Android is not a Unix-like OS, other than having a kernel that was originally devised as a Unix clone. Beyond that, I’m not sure what your point is. Is it just that “most popular” is ill-defined?
To bring us back to the context of this post: I am quite willing to bet that “grep” and “cat” are used by humans more times per day on macOS than on any other OS.
Linux is a kernel, which is irrelevant; I've run the GNU tools on many different systems, including MS-DOS, over the years. POSIX now defines UNIX anyway.
To be fair, in many cases (such as grep), the GNU commands have additional features and are more intuitive to use than the standard POSIX implementations.
This article is purely theoretical and I don't think they do such brainstorming about how to train the IA. It's proved that they just take a brunch of poor peoples poorly paid to deal with real messages and try to moderate them sometimes with a poor understanding of the context, and use it as an input to teach the IA how to do "proper" moderation.
> It's proved that they just take a brunch of poor peoples poorly paid to deal with real messages and try to moderate them sometimes with a poor understanding of the context, and use it as an input to teach the IA how to do "proper" moderation.
That's exactly what the article says: "you’d write up some guidelines (...) and then contract with some external company to have human beings read those guidelines and rate lots of examples that you send them" and then it mentions people from places with low salaries, like rural India and the Philippines.
And then in the possible solutions, it mentions hiring people well steeped into the specific cultural context of those you're trying to moderate.
This is where I think the article undermines itself, because if paying for some different (and probably more expensive) set of people may be a solution, then the question that was supposed to be answered remains: "why do companies with unbounded resources not do that?"
While hiring those people might be more expensive, I expect it isn't much. Annotators willing to read a set of guidelines and perform rating tasks long term are generally not cheap. I suspect that for something like twitter, identifying people most suited to moderate a particular piece of content is itself a very difficult technical and social problem. So even assuming you can figure out how to find these people and hire them, there's still a long path from there to improving moderation.
