One question I have on this - if rail travel became more ubiquitous, would it become a more enticing target for malevolent actors and/or a higher priority for security screenings, etc? We marvel at how easy it is to walk on a train today, but would that change / how might it change if rail carried a more significant portion of travelers?
Amtrak already does some screening and they increased their security like all others did from rental cars to busses to trains to planes. However the nature of flying has a much higher reach in terms of potential damage which was realized on 9/11 really.
Trains are less of a threat. Attackers can only really cause damage on a train to a section and maybe a derailment.
Plane terrorism is broader. With a plane everyone is at risk and the plane could be used to attack other things.
Train terrorism is limited. A train can't be taken off course. A train can't be all blown up. Even a massive derailment only affects a section. An attack would be a tragedy but it has rails so to speak on the reach of the damage. Maybe if they blew it up over a bridge or by a building in a city it could cause more damage or some other trigger like causing another disaster. You to have the threat of people setting explosives on the track. There was one of those in 1995 in Arizona where 1 died and 78 were injured, supposedly the attackers were avenging the Waco Siege. [1] Looks like that is the only terrorism event on trains in the US. [2] Subways and metros are probably more targeted in the city.
Another tool to look at might be Dendron[1]. It's a VS Code plugin with similar functionality to Obsidian (according to the docs, it actually evolved from being a standalone app like Obsidian into the plugin form). My understanding is the client/plugin are FOSS, and the developer plans to implement some (optional) server-side functionality to fund ongoing development.
Have to second this comment. The Audible version of it had me riveted. A great story well-told, with a raft of good quotes, such as "People didn’t like game changers in the 90s anymore than the owners of of the Erie Canal liked the transcontinental railroad. New technology always leaves a battlefield littered with bodies."
Knowing very little about the topic, I recently saw an article talking about how the first wave of wind turbine blades was starting to be decommissioned, and running into difficulties with what to do with them. While they're no longer useful on the tower, since they're designed to withstand incredible forces, it's difficult to destroy, recycle, or otherwise dispose of them, and indicated they're ending up in storage.
Do you happen to know more about this particular phenomenon and what the end game is for that? Granted, this is likely less of a concern than the waste that coal creates, or the long term storage of spent nuclear fuel. I'm just curious about it.
I asked a person from one of the biggest wind manufacturers on earth that on Monday evening at an energy networking event. At the moment they plan to either put then all in landfills or chop then up and burn them.
We all agreed that the people will likely not worry about this nearly as much as they worry about burying vastly less but vastly more hazardous spent nuclear fuel (even though spent nuclear fuel in actual fact has a sound safe geological story).
The call out to make are the fields device.d(p)idmd5, device.d(p)idsha1 (both now deprecated), and device.ifa, as well as the user/data/segment fields. That's where user ID's (and potentially other data) are passed around. Some exchanges pass a bunch of data, others pass less data but allow you to do a cookie or device-ID exchange/sync so that one side of the transaction can map the other's ID's to theirs, so that the bidder can look up their user profile information. (which they've either bought or accumulated somehow).
Looks like MoPub doesn't pass ID/buyerId any more (it's strikethrough'd), but they do still pass data/segment fields. Not sure what those contain though, perhaps others can chime in.
For what it's worth, getting approved as an ad network is potentially non-trivial. I don't know all the steps involved, but you do need to demonstrate that you can at least meet minimum network response latencies, among other things. Additionally, most exchanges do have some sort of bidrate/winrate monitoring that will eventually throttle you if you're not participating "in good faith" or with reasonable bids/expectations of winning (it's costing them processing power and bandwidth to send you a request even if you don't win). Most also have ToS (for whatever good that does; enforcement may or may not be strong) restricting your ability to collect and store data received from bids (you're typically only allowed to store data from the bid IF you've won the auction). I've heard anecdotes of companies trying to tap into bid flow as "passive observers" this way and ending up getting cut off.
Without meaning to quibble with the numbers in the article, they point out that the bottom 50% of income has gone up $8,000, while the top 1% has gone up $800,000, which is indeed a 100x difference in absolute numbers. But on a relative basis, the bottom 50% of earners' incomes have gone up 42%, and the top 1% have gone up ~250%. Still a large difference, but not nearly as extreme as 100x.
Is there merit to analyzing these numbers on an absolute vs. relative scale, and/or is that beside the point? Does it miss the point if analysis like this doesn't also look at the cost/standard of living in those time periods too? E.g. if a particular standard of living that cost $19k in 1970 (manageable in the bottom 50%) now costs $21k, that's a great boon, but if it now costs $30k, that's probably a bad sign.
I agree a data diff would be challenging, especially at scale, but one tool I think is lacking is schema diffs. For sure one can see the sequence of migrations that were applied, but if all you have is a series of sql files that add/remove/update column definitions, by the end of one or more diffs, you may not actually know or remember what's IN the table you're trying to understand. And if you don't have prod access to show create table (or equivalent), you're left with tracing the diff operations and reconstructing the table schema yourself. Have you seen a tool that can do that?
I'm the author of a schema management tool, Skeema [1], designed to solve this problem for MySQL and MariaDB.
There are a number of other existing tools that can compare/diff schemas on 2 live databases, but Skeema is designed to also actually manage your database structure through a declarative repo of CREATE statements. It works at any scale (natively supports sharding and external OSC tools) and is trusted by several large users, including GitHub [2] and Twilio SendGrid [3].
jOOQ is an SQL library, which in addition to an internal SQL DSL for Java also includes other goodies like an SQL parser and since very recently (still under active development) also a schema diff tool (also available as CLI): https://www.jooq.org/diff/.
One thing which sets jOOQ apart from most other tools out there is the fact that it supports many different SQL dialects. Thus the schema diff tool can for instance also parse DDL in one dialect and render the diff in another SQL dialect. For certain applications this could be of interest.
Disclaimer: I am an active committer on the jOOQ project.
I run migrations locally and on dev on sanitised snapshots of live data, and have easy access to those, so I just use the db to view the schema if required. Regular snapshots of the data are useful too.
If migrations are kept small there isn't usually much confusion over what changed (see migration), or what exists (see db).
Does that sort of regulatory capture accomplish the same effect though? If you're a competitor in the space, you'd either a) not have any access to an ingredient you want, or b) would have to go through the trouble of finding a new company to import it AND get them licensed (which I assume is likely a difficult thing to do).
To an extent, the barrier to entry could end up so high that it's effectively _as if _ Coca-Cola has a legal stranglehold.
Often, at least in the US, and perhaps other places as well, money is a pretty strong proxy for power, and so concentrating wealth can end up concentrating power as well. I can appreciate the semantic difference between the two, and conceptually agree that breaking up companies _should_ distribute power. But I'm wondering about the long-term implications/success rate of breakups?
Antitrust action against Microsoft has been argued to have led to the oligopolistic state of affairs today [1].
The break up of AT&T/Bell System worked in the short term, but the market has re-consolidated into a few big TelCo players.
And that's just at the company level. I'd be interested as well whether the increased wealth/increased concentration of wealth among former owners also leads to (in the long term) increased regulatory capture or other side effects spearheaded by those individuals with their increased war chest.
At least a few years ago, Facebook did publish about partnering with Twitter and Microsoft to build tools for sharing image/content hashes [1], presumably to better aid in removal or prevent dissemination of certain types of content. It's not outlandish to suggest the partnership runs deeper 2-3 years later to cover more vectors.
