It is weird because the last time I've heard about MTurk was about developing countries being rather reliant on it for doing AI grunt work. If am not totally wrong this must mean that the data work has moved to other services.
I think the bigger issue is that a lot of the demand for labelling training data is now in highly-specialised fields (i.e. things like medical imaging), and mechanical turk's focus was on the generalist problems
I don't think it's superficial, but two problems adding up. Previous poster is talking about general latency issues because everything is networked and potentially quite far away.
What you point out is slowness once you hit the entry point. Go, or similar languages, as a server language platform could have solved that problem from a computational perspective. But it did not for the most part. In my opinion people choose the faster stuff because it's cool and they have more wiggle room to cram in to get back to the slow status quo.
Everything is overengineered, software or distributed architectures, sound to naive human logic but alien to computers. It's an cultural problem, development is so deeply entrenched into "business logic" that the minimal viable and computational economic solution isn't even on the table. I don't even think it has to do with cost or feasibility, it's just that your random e-com manager wouldn't know what to do with you, if a programmer really starts talking about hardcode tech stuff.
A friend of mine was once tasked with writing a kind of simulation that simulates millions of scenarios per session/run, and searches for a best-so-far solution while doing so. He proposed writing it in Rust (justifying it as: fast, low level, fewer memory bugs, fewer parallelism bugs (so potentially faster than "fast")), and management over-ruled them, and insisted on using raw/plain Python (without even an underlying C library), "because that is the industry standard", and "premature optimization is the root of all evil", and "nobody else knows Rust"[0].
Another friend, worked at a company, that got a new manager (I think as a result of a merger), and that manager halted all work on "yak shaving" projects. These "yak shaving" projects were things like logging, and debugging, and some kind of integrity-verification. When asked why they were being halted, the new manager said: "none of our customers asked for any of these things". When told that these things enable the team to produce a better product for the customers, the manager (I am told) looked at them with confusion and suspicion. Those projects were never improved since, and the product stopped improving as well. I am not sure if it affected their business (the pandemic was much more distortive).
What you call "business logic", is not even logic, and it has little to do with business. It is what Feynman called a "cargo cult". The obvious name for it is "cargo cult business management/logic".
It truly is embarrassing and shameful that after decades of idiotic decisions, it took a _trillion_[1] dollars of investment into a chat-bot technology, to finally crack open _one_[2] door to slightly less idiotic decisions, while opening dozens of new doors to decisions of an unknowable character.
Most companies (and, consequently, their engineering organizations) are simply _cosplaying_ as the things they are supposed to be.
I do not see how an AI assistant (or any kind of assistant or consultant) can save these fools from themselves. The only logical explanation is that most software companies are cursed -- you would have much better luck engaging a witch-doctor.
[0]: Nobody else knew C or C++ either. The fact is, that nobody cared. In fact, even Go would have been a better choice than raw Python, but nobody cared. Even Common Lisp (which is at least as abstract as Python, and has native execution speeds (GC and runtime type-checking can be turned off for compute-heavy workloads that mutate data in-place)), is a better choice, and yet, an _abundance_ of obviously superior options (all implemented and maintained by obviously superior engineers) was not enough to prevent the organization from choosing an inferior one, and using it stupidly (without a fast native-code component).
[1]: I see estimates from hundreds of billions to a trillion, depending on how you count it.
LLM aren't logic machines. It's concepts of "root cause" and "faster" are purely linguistic, including all the internal conflicts of those loose definitions.
In that sense an LLM wouldn't even think it "lied" being confidently incorrect, in human terms it's just a "whoopsie". Apparently we want exactly that.
The comment is removed. I was also a bit confused, so I've looked it up. So a very rough overview: Under Trudeau in Canada some regulations around gender politics and climate change, got a bit out of hand in terms of absurd requirements to state how they are helpful in the matter. Even for trivial things, they were not a hard requirements but helpful.
Unlike the US gov in this post, they didn't slash projects with good intentions, they just changed and clarified the requirements.
Correction welcome, I am far away from canadian politics.
Same. I welcome correction, but I need evidence first. I'm not saying there wasn't something silly going on, but the commenter made it seem like the Canadian government did the opposite of DOGE to the same degree rather than just encourage connections to broader societal impact. Such a claim needs to be sourced.
Interesting that an entirely true comment has been removed via flagging. I not only helped write grants during the peak of that trend, but reviewed applications where I was expected to evaluate how other applicants satisfied those priorities of the funding body.
I think warning about the other extreme is valid. But the way you wrote your comment it could be perceived as justification of the categorical slashing of grants by the trump administration. Which doesn't seem right either, because the progressive canadian policies are still in place, just less nonsensical.
You comment was also just made invisible due to low rating. Which can be disabled in settings. So my fault thinking it was deleted.
I can still read it; it’s just been downvoted afaict.
But it does seem like a bad comparison if what the other commenter said is true. I mean, here we’re talking about a lot of legitimate research being cut for absurd reasons.
There's a way of saying "we need to acknowledge that it's probably bad when either 'side' does this, due to our commitment to a deeper desire for truth", and the original comment ended up sounding more like "Well, liberals did it too". I think what we aspire to here is the former, which is helpful; the latter is polarizing and gets us further from core principles.
FWIW, I have a few professor friends who are generally liberal but were required to write yearly personal diversity statements by their administrations, and knew they were rewarded for putting pathos and hardship in their stories. They hated everything about it but felt that it would set their careers back to speak out against it. I think it's very valuable to have unpolitical discussions about these things, align on deep values, and come to a deeper understanding of how we can support one another--rather than falling into camps and pointing fingers.
And also it doesn't justify the absurd overcorrection this admin has created.
This is not at all a reasonable response to a legitimate criticism of what many considered a pretentious overreach of the progressive movement. We can have a constructive discussion about all that.
But this level of insanity is another thing, and pointing out that it came about because the previous admin was incentivizing absurd behavior in the name of DEI or whatnot, is not doing their argument the kind of favour they expect
And a mention of morons being a transversal party of just occasional color, and a phenomenon that we have not finished assessing - a root cause in the shape revealed in this topics - is important here.
You need to see the facebook part in context, back then it was actually a hot place to be, the company and the platform, and devs were dedicated to leave a mark. Zuck was also perceived as the nerd buddy that disrupted the industry. Well until people found out he is a lizard.
Just the other day I found out about a study that measured coding productivity. They compared CLI tooling to simple actions. The CLI users _felt_ more productive, but they were not.
Then again, the question is, if the simple action needs to be changed, how hard will that be?
It’s not really about speed (at least for me). It’s about mental friction. Because you’re fluent in your tooling, you don’t spend time thinking about them.
