I don't get how this is unique to GPU clusters. As a general rule, underwriters are not qualified to operate and maintain the assets they underwrite loans for. That's why houses, cars, equipment, ... go at auction at a fraction of their value. And why lenders have insurance.
The better parallel is "why did Google make Kubernetes open-source" or "why do large for profit entities engaged in competition, use open-source as a strategy against their competitors"?
I wrote "lightweight polices" not policies. The police presents itself as benign looking in a public context. Enforcement of day to day offences is done mechanically by machines. A state trooper doesn't stop you on a speed check with his hand on his gun.
Yes, online policies are wild and not lightweight at all.
Something missing as cultural context is that deepfake, involuntary "porn", and all sorts of abuse of personal image, are a rampant and omnipresent problem in Korea. Many things are great here, but the sexual landscape when it comes to men versus women and kids, is nasty. You can't really apply a Western mindset to this without understanding just how messed up some of that stuff is. So whatever you think of the mechanism, the problem behind it is very real.
I do think a proposal that AI-filters content on small forums is a bit weird, and probably clumsy. But Korea faces a real problem and usually leans toward a bias to action and "just do it". It leads to weird stuff but also to dynamic problem solving.
The part I'm trying to preempt here is measuring this against so called "universal" values; these French Revolution/Enlightenment ideas of universal rights aren't really universal, they're one culture's logic, consistent inside its own bubble but exported like it's the default for everyone. I'll say, I do like them. But other self-consistent logics exist, and I think Korea's set is one of them. It's going to sound cliché but it leans on harmony and the group where the Western one leans on the individual. Both produce aberrations, only different ones.
For example, first time I came here I thought it's crazy to have so many speeding cameras and CCTVs everywhere. Years later I didn't so much "got used to it" but I think it's a tradeoff that mostly works and I grew to appreciate it.
Korea prefers lightweight polices (literally friendly looking) with a lot of automated, bulk enforcement, instead of sparse enforcement backed by the occasional armored truck. That's a design choice, not a slide into dystopia.
So all I'm trying to convey is, keep an open mind, and don't apply some supposed "universal" mindset blindly. Critique the mechanism all you want. Just don't do it by treating one culture's values as the yardstick everyone else gets measured by.
Fwiw I think it's a misfire. But I don't think it's a slippery-slide down dystopia. It's just Tuesday.
TLA+, P, Lean... formal methods and previously esoteric testing methods (property based, mutation... testing) should become the default. I think it's the only way we can really reap the benefits of agentic coding.
I wrote about this a bit on my blog[1], different angle but along the same line. You explain TLA+ and model checking well which makes the case concrete.
I'm curious of you have thoughts on these other methods and tools like P, Lean, Dafny, etc?
The problem IMO is that they filled GitHub with Microsoft folks who just don't have the engineering self-sufficient hacker culture that is required to balance the "attraction park" vibe that GitHub paired it with. So now it's just an attraction park for Microsoft employees to go and do silly work with teams of 100 that should have been done by a skilled team of 5 hackers.
I was there for a couple years after the acquisition and just couldn't stand seeing it. I felt I was becoming useless working in a mad house that was becoming more maddening everyday. And MSFT just keeps replacing leadership with more and more disconnected people who just don't get it, who just never used GitHub like the OG users did. Two years ago I interviewed again for my old team, largely out of curiosity, and the Microsoft engineering manager asked me some brain teaser question as my interview. The disconnect is just too large.
They don't take GitHub seriously. It's a toy to MSFT and vibes matter more than the product itself. And they hire for it using MSFT drone logic, fill it with people hired and profiled to be MSFT-lifers, and these two things don't mix.
Sorry I don't have anything great to say. And of course, many of these MSFT folks were actually damn good, but they were swimming in a sea of MSFT drone.
This reduces writing to one concept: thinking and the writing is just a byproduct. But writing is also presentation and also communication.
There is nothing wrong with speechwriters. Various authors spilled out their thoughts in rough format and had writers turn them into better structured, prosed and understandable projections. Hand writing each sentence that is presented as an end-product to the reader doesn't solve that problem.
Forcibly coupling the two is an arbitrary choice that may be a valid tradeoff for some and not so for others, and not so for _all_ writing.
I'm not good at looping through a document with proper english prose. My writing is raw, particular, and I gloss over a lot of details. LLMs help me turn my shitty extensive notes in bad grammar and syntax, into shareable and understandable artifacts. They help me turn more of my thoughts into ingestable communication by others. Without AI, I communicate less of my thoughts due to friction. My thoughts are formed and authored and written, but not in a format consumable by anyone else.
Let's say 100k files is 300k syscalls, at ~1-2us per syscall. That's 300ms of syscalls. Then assume 10kb per file, that's 1GB of file, easily done in a fraction of a second when the cache is warm (it'll be from scanning the dir). That's like 600ms used up and plenty left to just parse and analyze 100k things in 2s.
If a human asked me this question, I would be confused by the question as ambiguous since it suggests something odd is implied but underspecified. I think any confident answer either way by AI is lacking in pedantry.
For some reason, I always found the arguments for "it's better to not know" for these tests to be strange and slightly infantilizing. But of course this must not be the end of it, and there might be some more well thought out arguments from bioethicists that go beyond "the patient can't handle the truth". Because this argument seems like it's doing a lot of heavy lifting without much evidence.
I think it's a mistake to believe that this money would exist if it was to be spent on these things. The existence of money is largely derived from society scale intention, excitement or urgency. These hospitals, machine shops, etc, could not manifest the same amount of money unless packaged as an exciting society scale project by a charismatic and credible character. But AI, as an aggregate, has this pull and there are a few clear investment channels in which to pour this money. The money didn't need to exist yesterday, it can be created by pulling a loan from (ultimately) the Fed.
the rebuke is that lack of chaos makes people feel more orderly and as if things are going better, but it doesn't increase your luck surface area, it just maximizes cozy vibes and self interested comfort.
It feels like we're doing another lift to a higher level of abstraction. Whereas we had "automatic programming" and "high level programming languages" free us from assembly, where higher level abstractions could be represented without the author having to know or care about the assembly (and it took decades for the switch to happen), we now once again get pulled up another layer.
We're in the midst of another abstraction level becoming the working layer - and that's not a small layer jump but a jump to a completely different plane. And I think once again, we'll benefit from getting tools that help us specify the high level concepts we intend, and ways to enforce that the generated code is correct - not necessarily fast or efficient but at least correct - same as compilers do. And this lift is happening on a much more accelerated timeline.
The problem of ensuring correctness of the generated code across all the layers we're now skipping is going to be the crux of how we manage to leverage LLM/agentic coding.
My point is that the chemical complexity (manufacturing uses) can be reproduced, and the energy storage density also can be. So really the gift of hydrocarbons under the ground is more that readily available energy is under our feet to help propel us towards higher levels sources of energy. IMO it’s a stepping stone and that’s effectively how humanity is using it.
You can chose to see it as astroturfing, or see it as people actually thinking the superlatives are appropriate.
To be honest, it makes no difference in my life if you believe or not what I'm saying. And from my perspective, it's just a bit astounding to read people's takes that are authoritatively claiming that LLMs are not useful for software development. It's like telling me over the phone that restaurant X doesn't have a pasta dish, while I'm sitting at restaurant X eating a pasta dish. It's just weird, but I understand that maybe you haven't gone to the resto in a while, or didn't see the menu item, or maybe you just have something against this restaurant for some weird reason.
The fact that as many engineers are on payroll doesn't mean that "cloud" is not an efficiency improvement. When things are easier and cheaper, people don't do less or buy less. They do more and buy more until they fill their capacity. The end result is the same number (or more) of engineers, but they deal with a higher level of abstraction and achieve more with the same headcount.
https://aybabt.me/