It doesn’t cost much to keep the lights on. As far as I know, X post-acquisition is not investing in innovation anymore.
Musk might have been right that shifting to KTLO mode was a good idea, but the company would still be better off if someone other than him had bought it and done the same thing.
Valuation is not important. These are private market transactions. Ultimately all the investors made out well, and it seems the company is more profitable than it was before. At least expenses are way down and if those expenses are correct then they are paying off the debt and making a good profit.
I couldn't possibly disagree with this more. Since the acquisition Twitter/X has had far more features at a far faster pace than in the 10 years prior. They've added all sorts of great stuff, and recently have been near the top of the charts in the Apple App Store.
I've been telling people, this is Uber in 2014, you're getting a benefit and it's being paid for with venture capital money, it's about as good as it's going to get.
I have yet to run a Java program that I haven't had to later kill due to RAM exhaustion. I don't know why. Yeah an Integer takes 160 bits and that's without the JVM overhead, but still. Somehow it feels like Java uses even more memory than Python. Logically you'd point the finger at whoever wrote the software rather than the language/runtime itself, but somehow it's always Java. It's like the Prius of languages.
Ok, just glanced at my corp workstation and some Java build analysis server is using 25GB RES, 50GB VIRT when I have no builds going. The hell is it doing.
GC usually only runs when the process wants to allocate an object but there's no space left on the heap. It's entirely possible that it did a bunch of work previously which created a bunch of garbage now waiting to be cleaned up. See the G1PeriodicGCInterval flag to enable idle collections (assuming G1).
Java is also fairly greedy with memory by default. It likes to grow the heap and then hold onto that memory unless 70% of the heap is free after a collection. The ratios used to grow and shrink the heap can be tuned with MinHeapFreeRatio and MaxHeapFreeRatio.
Before I even went on my rant, I was guessing there's just some confusing default like this but there's also some historical reason why it's like that.
> Ok, just glanced at my corp workstation and some Java build analysis server is using 25GB RES, 50GB VIRT when I have no builds going. The hell is it doing.
Allocating a heap of the size it was configured to use, probably.
Nothing broken about it. It's optimized for a particular situation, that situation being a long running process on a server. This is where the JVM typically runs. If you don't want that behaviour there are a myriad of GC options, which could be better documented but are not that hard to find.
It's not a big issue for a server deployment where if you got that memory from the OS and didn't get killed, there's probably nothing else running on the box and you might as well keep it for the next traffic spike. But yeah not ideal on the desktop/workstation.
Different processor and JVM. My understanding is that early versions of the Java card runtime didn't even support garbage collection. It was a very different environment to program, even if the language was "Java".
Java is fast for long-running server processes. Even HFT shops competing for milliseconds use it. But yeah every user-facing interactive Java application manages to feel clunky.
Learned from an NYC exchange 10 years ago that Java can be written so as to not use garbage collection. Fast and no pause for GC.
1. Resource and reuse objects that otherwise are garbage collected. Use `new` sparingly.
2. Avoid Java idioms that create garbage, e.g. for (String s : strings) {...},
substitute with (int i = 0, strings_len = strings.length(), i < strings_len) {
String s = strings[i]; ...}
I would also argue that software (and the people that write it) have a "correctness" bias that is not fully aligned with business goals.
Tech debt is real, but so is the downside of building a system that has constraints that do not actually align with the realities of the business: optimizing for too much scale, too much performance, or too much modularity. Those things are needed, but only sometimes. Walking that line well (which takes some luck!) is what separates good engineering leadership from great engineering leadership.
> I would also argue that software (and the people that write it) have a "correctness" bias that is not fully aligned with business goals.
Hey, I resemble that remark!
Yeah, I get where you're coming from but i do really feel that it's more of a communication issue, along with the abstract nature of software. I mostly do data related stuff, and have often had the experience of finding "wrong" data that doesn't have a large impact, and every time I need to remind myself that it might not matter.
You can also see this in the over-valuation of dashboards vs data engineering. Stakeholders lurve dashboards but value the engineering of pipelines much less highly, even though you can't have dashboards without data.
To be fair, this bias for "correctness" is both logical and necessary, and not something that stems from inability or unwillingness to understand business goals.
That tech debt you took on to meet the latest oh-so-important deadline? Prepare to live with it forever, because the next hare-brained initiative is right around the corner.
Frankly, the business's goals are not my goals, and unless I own the place, I'm not sacrificing good work for it.
Maybe but most endowments actually have "legally?" bound or otherwise contracted uses in universities. Thats why Harvard can't just tap it's endowment to fund research the current Admin has cut. So I'm doubting that endowments are being used in this way to pay coaches.
Sure, but if an endowment is paying for, say, the football coaching staff, then that leaves that much more money free in the general fund to pay for other things.
If the endowment is paying for something that otherwise wouldn't be paid for generally, that's a different story.
This isn't really fair I think. Academic money is actually not fungible - it can't be used to fund athletics, and vice versa. Just because both pots are relatively large doesn't mean that the money itself is fungible.
You pay for one or two people with real experience and 4 reasonably new hires whose job it is to answer questions posed by the senior team and to build documentation.
You want the senior people focusing on the problems, strategy, and comms and not data aggregation and power point formatting.
Half the time it doesn't actually matter who the consultant is, the business is just looking for an arbiter to provide a second opinion or justify a decision.
>Half the time it doesn't actually matter who the consultant is, the business is just looking for an arbiter to provide a second opinion or justify a decision.
It's much easier to feel good about a decision if you can get some McKinsey people to hold your hand and tell you it will be ok while making it.
How does this not vindicate their viewpoint? Do you really need a team of ivy grads to make power points or inexperienced people to give unqualified answers?
Modern consulting seems like one of the better deaths inflicted by GenAI. The entire industry is a means to commit corporate espionage legally.
They can do something more useful with that education.
I think the group of people that work on this should petition for their tax data to be the first to be used. Seems to align the incentives on internal controls of PPI.
Then those who vote for higher public services should be the ones to pay.
Which, if they did, would solve the left/right dichotomy. But no, those who want the public services want the money taken from the other half.
Here’s what I always remind myself about this current government: It is really the worst ideas conflated together, but it was that, or elect leftists in power.
At the thought of leftists in power, I think open data day at the IRS is really not bad.
Worse: I think the leftists are the firsts to be afraid of having the tax data spilled in public. We’d Trump’s records, but we’d also see the Dems’ records. And that’s something they’re afraid of.
> Here’s what I always remind myself about this current government: It is really the worst ideas conflated together, but it was that, or elect leftists in power.
"We destroyed the economy for a generation, but at least we stopped people from making us put pronouns in our bio."
It‘s the worst ideas together, but the alternative is even worse? That does not make any sense, logically. But I guess this summarizes the current situation quite nicely.
> Here’s what I always remind myself about this current government: It is really the worst ideas conflated together, but it was that, or elect leftists in power.
There were basically no leftists running under any major party banner for any federal office in the US, and the small number of arguable center-leftists doing so in the general election were mostly incumbents, and mostly reelected.
It was not, in fact, a choice between leftists and what we got, it was a choice between the center-right corporate capitalist wing of the Democratic Party and what is, at best, lawless kleptocracy and at worst outright fascism.
> At the thought of leftists in power, I think open data day at the IRS is really not bad.
LOL. You're not even an American. He's a tip: U.S. states with the highest GDP per capita are mostly run by Democrats[1] (who, by the way, aren't leftists).
I've never this at Google, but at my company, if you pass the technical screen you're offered to hiring managers. If they don't want you on your team because they want more leadership (or less leadership), or if there were 5 senior python roles and you were the 6th person to pass the interviews, you still won't get hired.
Unironically yes. Although it's arguably a win-win. Google constantly keeps its pipeline of candidates open which means that if you're looking for a job and you clear the resume bar, you'll get an interview. Meanwhile teams are constantly hiring so they'll want a steady stream of candidates.
The alternative would mean that unless your timing for a job search is perfect, you won't even get a foot in the door and teams within Google will also struggle to fill open positions since it would take a while to interview the candidate pool.
>
People still line up for their purported incentives, despite these stories.
The reason why nerds nevertheless apply at MAANG companies is thus the same reason why "ordinary" people buy lottery tickets - nerds are not that different. :-)
That caused Apple, Coke, and many other large clients to stop advertising.