My buzzspeak is a little rusty, but this sounds suspiciously like "Beat monkeys to code faster, send code out the door without testing, and just let the users figure it out". Did something get lost in translation?
They deploy to internal users -- LinkedIn employees -- via Enterprise Enrollment for iOS devices, and via Google Play’s alpha testing functionality and the developer console API. So it's not like they are sending the code without testing, and it appears that at any time, an internal user can torpedo a particular release candidate, so that what they end up with at the end of the week might be the same thing they had at the end of last week.
This still has a bunch of holes, just as any continuous integration process does, but at least by staging a 3 hour limit on things, they avoid falling into the trap that Google and Apple have leapt into willingly, where "it takes as long as it takes" to do integration acceptance testing.
In particular, both Google and Apple engage in reactionary testing paradigms. They build tests based on bugs they've previously encountered (because they are in fact able to test for those, since they've been well characterized during the process of being fixed), and stack them on top of all the previous tests.
This results in an ever-growing set of tests that test for regressions, but which do not test for correct behaviour of the products, overall. Instead, it lets you know when you've encountered a bug which you have previously encountered.
Further, since the testing is unbounded (and in fact, will stop the build process at Apple or Google by throwing a stick into the bicycle wheel of progress -- an event which is called "closing the tree", necessitates the existence of a "tree sheriff" role to deal with automated closures of the tree, and fails to automate the back-out of code leading to failure -- it leads to flaky tests.
The flaky tests come about because there's a human involved in making the decision, and in structuring the situation that way, with an unbounded closure interval -- practically bounded only by people showing up in your office (Apple) or open plan desk/cubicle (Google) and breathing down your neck -- there's a strong encouragement toward flaky tests, and there's a strong tendency do disempower the "tree sheriff" in favor of getting the expensive engineers back to work. And because of this, it's very hard to deep dive into flaky tests.
So we are left with the situation that flaky tests are both tolerated (as long as they are not "too flaky" -- or in Google-speak -- as long as they do not exhibit "too much 'jank' when run"), and the flaky tests do not get cleaned out eventually because the set of tests that you run are not pruned occasionally to run in bounded time, and if you try to do a deep dive to actually resolve the flakiness, you get the disapproval of your peers.
So a bounded time is a good thing, if you insist on having continuous integration, but it doesn't necessarily fix the other problems with continuous integration, and it doesn't fix the fact that most testing in organizations where engineers are involved in "agile methods", such as "Scrum Runs", where the primary goal is code base stabilization, rather than forward progress on the product for 2/3rds or more of the engineers time... well, combine that with an iterative process and it's a recipe for engineers who don't know about testing writing a lot of useless tests, because you are moving the goalposts on them iteratively anyway.
So they've done something relatively innovative, but it's probably not innovative enough. And it's probably an interesting experiment, but I would be wildly surprised if other organizations adopted their framework.
P.S.: The other problem with iterative models, particularly constant integration iterative models, is that you tend to only ever do evolutionary things, and never revolutionary things. There's not always a drunkards walk that gets you "from where we are" to "someplace new and fantastic". There are saddle points, and once you are in a saddle point, an iterative model will not get you out.