This has become a sort of unintentional skill in the ecommerce era. Everyone is using china, either the actual "first party" brand that is really just ordering bulk from china and reselling it stateside, or the various clones of that brand. The skill then becomes feeling out which of these various products and clones are coming from the better option of the couple chinese manufacturing companies everyone is using, then buying whichever of these is going for cheapest and least shipping headaches. Usually also if a product has been out for a couple years, there's an initial version widely available then an actual 2.0 version that solves a lot of the issues in the first, more sturdy at now known failure points, etc. That 2.0 version actually usually circulates in the no name brands for a little while before the "first party" brand eventually picks it up for their own line.
I grasp what you’re expressing, I really do. I’ve probably pondered this very thing too often in my life and can think of very specific examples where purchasing a non-brand name version of a particular product really froze up the decision making process.
However I think as I’ve gotten older, certain realities have occurred to me:
1. there is a fairly significant amount of people that would still pay more for the shirt the “right” logo and who would absolutely not pay less if it had the “wrong” (I.e., vs no logo). In fact, they wouldn’t wear the wrong logo even if the shirt was free. I include myself in this under certain circumstances and would conclude that some times the recognizable name actually helps put my mind at ease about the purchase, while being fully able to acknowledge that it was entirely a psychological thing.
2. Unfortunately there’s just simply no way of knowing this information (brand name product vs essentially same product without brand name) most of the time so letting that weigh too heavily on an otherwise thoughtfully considered purchase achieves effectively nothing.
3. The thing was probably entirely discretionary for my existence, so don’t buy it (otherwise, see #2…)
I got a pair of T-shirts from These Glory Days. Wore them like 20% of time last two years and they look better then some others after 2 washes (albeit changed from them after coming back to work, and use work clothes at work, so not like they were used THAT much. So it's not always the expensive stuff that's equal to the cheap stuff. And funny thing, got them on a sale because they were pretty cheap, not really because I knew that they were quality.
Though had my wife with me when shopping and she might have "felt" the material and said that it was good for that price. Her mum is a seamstress if I remember the word correctly as somebody who sews clothes.
It's like reading an entire article and pointing out a typo without engaging with any of the context. It's easy to find a single fault and point it out loudly, but if you don't even try to engage with the intent of the message, you aren't providing anything of substance.
I'm always surprised at how many people in the tech sector don't think that things can and will change. In the next couple of years? Sure. 5+? Who knows. Necessity is the mother of invention.
I'm always surprised at how many people in the tech sector assume overcoming fundamental LLM weaknesses is always “just a matter of time,” and that time will arrive quickly enough to be relevant. If you haven’t seen any of the videos of people trying to get frontier LLMs to count consistently, you might think we’re further from LLM accountant than you realize. It’s not a data problem— I’m pretty sure they’ve encountered numeric progressions between 1 ABs l and 100 before.
I'm not just talking about LLMs though. People thought the internet and email were just a fad that would never catch on. People thought that the idea of home computing was absurd. All because they only saw what was in front of them at the time.
Also, how many accountants do you know that are truly happy with their work? I'd like to think many of them would love to do something other than crunch numbers all day.
Ok, let’s cherry pick some more societal tech revolutions. People also thought Segways were not the revolution in transportation despite fans and industry proponents saying we’d need to redesign cities to accommodate them. People also thought blockchain ledgers were a niche, even if useful, technique despite fans and industry proponents saying they were going to change literally everything.(remember Web 3.0?) People thought NFTs were a fundamentally flawed solution in search of a problem despite fans and industry proponents asserting they’d revolutionize IP. People thought that the metaverse was kind of ridiculous despite fans and industry proponents saying we’d all live a significant portion of our lives there, and some were practically running victory laps at the beginning of the pandemic when everybody was forced online (but then still didn’t use the metaverse. Some thought immersive VR headsets were a niche technology with limited consumer appeal despite fans and industry proponents claiming they’d essentially be the default display for computing by now.
> People thought the internet and email were just a fad that would never catch on. People thought that the idea of home computing was absurd.
We're far removed from "we've sold all the computers the world can buy" (back from when computers were the size of a building).
This is a disingenuous argument. The web and email were basically instant hits and people realized it. Similar story for home computing once the computing power caught up.
Email was a hit well before the internet existed. The utility was immediately apparent. And while people had lots of concerns about the internet, like misinformation and consumer-level utility, it was never broadly considered to be as dubiously useful or ethically fraught as LLMs and diffusion models. You can definitely find articles criticizing the bubble-forming finances, and one or two written by dedicated serial naysayers, but it was not a common perspective. Anybody who lived through that era will remember a hell of a lot more pushback against mobile phone adoption than Internet adoption, and even that was culturally marginal.
> I'm always surprised at how many people in the tech sector assume overcoming fundamental LLM weaknesses is always “just a matter of time,” and that time will arrive quickly enough to be relevant.
Lots of techies are tech-optimists ("tech always improves quickly").
Lots of people also have dollar signs in their eyes (or related, such as increased visibility and scope).
I think those are more like two facets in the crowd rather than two distinct crowds. Almost all idealist tech industry workers in column A that believe this is the future of the tech business would also fit into column B. Column B folks believing this business isn’t a fantastically expensive mass delusion event (with regard to the financial impact predictions) would essentially fit into column a. Most that wouldn’t would probably be Wall Street types that told Leopold Aschenbrenner to get bent rather than handing him billions of dollars on blind faith.
Things can easily change for the worse, such as a stock market crash. Who knows? Will we get AGI or will we see more homeless? History says... AGI for sure!
It's very difficult for this sort of thing to change for the worse. It's basically impossible on the software side. If next year's model is worse then keep using this year's model. Hardware technology can potentially go backwards, but things have to get really bad for that to happen.
LLMs are inherently unreliable. We do already work with unreliable technologies for many things but there's this engineering principle called "use the right tool for the job".
And it's a lot more likely that LLMs can't be changed to become unreliable, it's just how they work. So we would need more basic research, that doesn't grow on trees and for which the timelines are basically open ended. Maybe tomorrow, maybe right after cold fusion hits mass adoption.
They’ve become a lot more reliable. It would be strange if that progress stopped now. It’s possible. My main point is that they won’t get worse, as the other commenter suggested.
This isn’t a theoretical or technical problem; in fact, it’s not about the models at all: it’s about the available services getting worse. When they preview a new model and people are benchmarking it, they afford them a shitload of compute and they work great. Then, they get worse. That extra compute is surely in the billions of dollars OpenAI allotted to marketing, and especially in higher-volume periods, people talk about Anthropic‘s responses being lower quality all the time. The finances don’t indicate these companies’ current MOs are sustainable. Since self-hosted models don’t stand a chance of competing with frontier model capabilities, there is a very real chance that the available services will get much worse, and where the rubber hits the road, that’s really all that matters in the foreseeable future.
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