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capitalsigma

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People don't write blog posts about how they wake up at 3AM to assign new tasks to their intern, nor do they build "orchestration frameworks" that involve N layers of interns passing tasks down between eachother

Money allows for economic specialization, leading to greater productivity. You don't build an economy that produces cell phones when you're stuck bartering goats for wheat.

There are overheads in server workloads that scale with the number of machines (network traffic, serializing/deserializing requests). There are also fixed costs per server that don't scale with core count, or at least scale sublinearly (storage, physical data center space, motherboard, ease of maintenance). So running 10 machines with 100 cores can be cheaper and more performant than running 1,000 machines with 1 core even if $/core is higher. And of course individual cores can be beefier: wider SIMD units, application-specific extensions like bfloat support for ML workloads, etc.

Of course Moore's law is slowing down, but cores/$ is an extremely silly metric to use

We're not talking here about being overly critical in a code review, or even criticizing someone who pushed bugs to prod. This is someone who intentionally violated company policy in a way that harms everyone who works there. It is not business as usual. Getting mad about this sort of thing is like getting mad about somebody keying your car or spreading false rumors about you: entirely reasonable and justified and not an interaction where professionalism is expected.

It's unclear to me how making these divisions dramatically increase their infrastructure costs (by either pulling them in-house or paying a premium to the original parent company) will "help them compete"

These models are very impressive, but the issue (imo) is that lay people without an ML background see how plausibly-human the output is and infer that there must be some plausibly-human intelligence behind it that has some plausibly-human learning mechanism -- if your new hire at work made the kinds of mistakes that ChatGPT does, you'd expect them to be up to speed in a couple of weeks. The issue is that ChatGPT really isn't human-like, and removing inaccurate output isn't just a question of correcting it a few times -- it's learning process is truly different and it doesn't understand things how we do.

Stock traders already use ML models. "Replacing traders with ML models" means "making the job 'trader' into a job that develops ML models, rather than more traditional things like doing research on companies (or whatever)." My understanding is that this transition basically already happened over the course of the last two decades or so.

I'm personally happy to accept this volatility in return for higher comp and the opportunity to be part of a leaner, higher performing team. I don't want to work with people who are here to coast.

It's supposed to be a joke, comparing the process of drift in the codebase with physical disintegration. Much like technical debt is not literally a balance owed to another party, or an object is not literally a physical lump of mass, and a class doesn't have a literal parent because it was never born.

Two days of actually trying allowed me to accomplish more on this particular goal than 7 previous months of cowardice had, and (maybe) about as much as a full semester college course would have.

The article then goes on to explain that OP basically spent a weekend writing a book report about some pop science YouTube videos. What a joke.

I mean, yes, of course OP should be aware that they are on the clock during the day. I just feel like you are really misrepresenting the scale of the worry here.

A senior candidate has a serious, revenue-generating side business, maybe in a competing product area? Yeah, that seems like cause for concern: this candidate's potentially-dropped cycles working on their business could mean a significant loss in team productivity, we might worry that they're on the verge of quitting to focus on their own product, whatever.

An intern candidate has a side hustle? Awesome, sounds like they're not totally clueless, likely they'll be able to ramp up quicker than someone with less experience. Ideally they put it on the back burner for the internship duration but nothing is going to collapse if they're not functioning at 100%. I feel like it's a much bigger risk that you hire someone with a weaker resume and get nothing from them even when they try their best.

I mean, the NY transit system will take you pretty much anywhere in an area with a population of 8M. For scale, note that New York State alone is about 4x larger than Taiwan. I agree that having walkable cities is a good thing but it's not like all of the US is one giant suburb, and it's not like the US has anywhere near the density that would be required to justify "high speed rail across the whole country, just an hour away"