It's finally been updated: https://status.cloud.google.com/incidents/Xs2XTHzAVC9YnafnPy...
Way too slow for the scale of the outage.
197 karma · joined April 1, 2013
Way too slow for the scale of the outage.
Another HN thread mentioned their Google rep said the cause is a power outage [1] which is being resolved.
It’s kind of a huge deal that I can give a Markdown file of plain text content to somebody non-technical and they aren’t overwhelmed by it in raw form.
HTML fails that same test.
Absolutely zero regrets, the cumulative savings across everything that is faster and the massive step up in DX is worthy of the hype.
Apparently there are already 5k TX electric taxis out there, which is a good start:
https://levc.com/levc-celebrates-sale-of-5000th-tx-electric-...
[0]: https://github.com/rust-lang/rust/pull/82834
It had so many compatibility issues with real JS that it was kind of untenable to use it with scripts designed for other JS environments: https://jaxenter.com/nashorn-javascript-engine-deprecated-14...
The only real way to deal with JS now is Rhino (which still exists!), or some custom binding to V8 or something via JNI (yikes).
Our work uses Nashorn a lot for scripting and this is a big blocker for us to move to newer Java versions.
We absolutely agree this tool only solves the easiest part of anonymising data, and internally we rely on our team of data scientists to do the difficult parts. This tool is absolutely not up to the task of anonymising a dataset in such a way as to make it able to be made public. For us, it's about risk management vs effort: from a security perspective there are scenarios where we can use samples of data that have gone through this process and decrease the risk of holding data internally in multiple places substantially without significant effort. If we were to go onto to make any of these datasets ultimately public, we'd be looking for a better suited tool (eg. ARX [2]).
Regarding one part of your comment:
> My concern is that helping the user with the easiest part of anonymizing data stands to encourage the user to go full steam ahead without slowing down to stop and think very carefully about what they're doing.
We're going to try to add something to the README addressing this exact question from both of you as it's one I anticipate we're going to get asked a lot - or one that carries risk if it's not made obvious form the outset - so thanks for the constructive line of questioning as it really will ultimately help us and people who choose to use this tool make a decision that's right for them and their use-cases.
What you see today in this project is really a means to scratch an itch we had - mainly to quickly and easily sample/obfuscate some delimited data in a way that is "good enough" for use for demonstrating a visualisation tool without using the original dataset. It's important to note that that we intend to use this data still within a secure environment.
This tool is absolutely not up to the task of anonymising a dataset in such a way as to make it able to be made public. For us, it's about risk management vs effort: from a security perspective there are scenarios where we can use samples of data that have gone through this process and decrease the risk of holding data in mutliplate places substantially without significant effort. If we were to go onto to make any of these datasets ultimately public, we'd be looking for a better suited tool.
As a result, tools like ARX are not something we really want to compete with - they're aiming for a complete solution whereby the results are good enough to potentially make public. It goes perhaps without saying really that the reality of this goal is debatable given the research you linked, but some people might be comfortable with those risks.
One thing we've done to try and bridge the gap a bit is to make it really easy to add new functions as we need them, and I think we can get to a point whereby for a good portion of use-cases this tool is good enough (for example, making datasets you can use in a development environment that are representative, but a manageable size and anonymised to a reasonable degree).
We'll also try to add something to the README addressing this exact question from you as it's one I anticipate we're going to get asked a lot - so thanks for the constructive line of questioning as it really will ultimately help us and people who choose to use this tool make a decision that's right for them and their use-cases.
I suppose the difference between this and Walmart's move is that we are not entitled to buy the things we want from every shop, whereas these drivers are probably entitled to employment without discrimination in regards to other customers they provide services to?
As a vinyl collector myself, another thing that interests me is the feeling of quality you get when you buy vinyl. I love looking through the lyric booklets in 10/12" format, beautifully printed and often a piece of art in its own right. I actually feel like I _want_ to sit there and listen through a whole album when you have all that to gaze through at the same time.
You can define Swift enumerations to store associated values of any given type, and the value types can be different for each case of the enumeration if needed. Enumerations similar to these are known as discriminated unions, tagged unions, or variants in other programming languages. [1]
Haskell and other ML family languages also have similar constructs, although these are usually modelled using "Algebraic Data Types", or "sum types". [2] [3]
[1]: https://developer.apple.com/library/content/documentation/Sw...
[2]: https://wiki.haskell.org/Algebraic_data_type
[3]: https://www.schoolofhaskell.com/school/to-infinity-and-beyon...
Add to that the fact that they made it, with a recent update, insanely likely for anything half-decent to simply run or be impossible to catch, and you have a recipe for declining interest in playing and paying to be bored.
For either method, you can audit the activity of your account on the GitHub security page: https://github.com/settings/security. For example, upon having deliberately got my 2FA token wrong, "user.two_factor_requested" and "user.failed_login" events were logged for me.
This looks fantastic, and shows a true commitment to reducing friction with the language - a goal which often goes too long without attention.
These are really useful. Whether we like it or not, mathematics underpins most of computer science and often beginners don't even know what to search for to get started. A resource like this is an excellent way to get somebody going.
It seems perfectly reasonable that they can and will moderate channels, but not conversations.
[1]: https://developer.android.com/google/play/expansion-files.ht...