thats one option. But other companies sometimes choose to keep the scarcity and secrecy for years, even decades, and if they play their cards right it keeps working

Labubus fall is more about its makers decision to increase sales numbers instead of keeping them flat and generating more and more and more hype

Hermes can sell a $15,000 Birkin to everyone, im sure they can figure out the supply chain aspects if they really wanted to. and within a month everyone that wanted one would have one and sales would drop. Hermes will have a spike in sales, followed by a drop

Instead they force you to play years long games with their sales staff to get an opportunity to spend $15,000. And decades later people still opt in to spending thousands of dollars on plates and scarves hoping one day they will be offered one

This is just as true about a $40 Supreme, or Aime Leon Dore T-shirt, than it is for a $15,000 handbag. If you keep the scarcity going just right, it lasts much longer

It does delight me no end to see a whole thread on handbags on HN. I agree with one of the parent posters though, handbags are an unusual category with long-lived brand status (like cars and watches) and not really comparable to lububus.

I checked this out and was amused to see that wikipedia notes:

> Birkin used the bag initially but later changed her mind because she was carrying too many things in it: "What's the use of having a second one?" she said laughingly. "You only need one and that busts your arm; they're bloody heavy. I'm going to have an operation for tendonitis in the shoulder".

In my experience it's pretty common to carry stuff in backpacks. They put a lot of weight on your spine, which can take it. Jane Birkin's comment reminded me of the idea in Dave Barry's Only Travel Guide You'll Ever Need that frequent travelers are always on the lookout for luggage that can hold more than it can actually hold.

This seems to occur in high fashion a lot, an upscale rendition of something popular among the working class.

Many rock bands with working class roots "bring up" styles (like the newsboy cap), but also lower classes try and "look" upwards which can give us the nouveau riche clichés. Celebrities trying to hid their identity in public started to wear large sunglasses and suddenly everybody would start to wear them.

It's the primary reason why brands have become so important - fabric quality can vary, but jeans are otherwise just jeans; slap Gucci or Prada on it and suddenly you're signalling conspicuous consumption.

According to a more fashion and design orientated friend of mine, you can buy knockoffs of Birkin or any other high-end bag. And, guess what? Some of those knockoffs and their manufacturers have developed a certain cachet, and actually sell for quite high prices. So of course, those have spawned knockoffs too.

It's like the bit in Pattern Recognition, isn't it?

There are whole subreddits devoted to this, the most well-known being repladies, which went private after it got too famous due to an NYT article. People will spend $1000 or more for a really good Birkin knockoff with high quality leather and hardware. The bags are almost all made in workshops in China. Getting one is apparently (I haven’t done it myself) an interesting exercise in trust and reputation: how do you know the seller isn’t going to send you a cheap knockoff from China rather than a “real” $1000 knockoff? In practice there is a whole world of trusted Chinese middlemen with reviews etc. who have a strong stake in keeping their reputation high in the “reps” community (but you’d better make sure the reviews are real…).

I'd bet you a coffee that there are knockoffs, or "reps" if you prefer, that are actually at least in some respects better quality than the original.

It's sad and petty I know, but if I were a billionaire edgelord like Elon Musk, rather than Twitter, I'd buy Hermes and sell their products in supermarkets. All the past limited editions too. Just to fuck with the kind of people who buy them.

Then again Hermes is worth 200 billion and upsetting an oligarch's sidechick might just get me killed so maybe not.

Wait hold on, what?

Like, I get that you were referring to the fact that they keep things scarce even for rich people, but you literally said “everyone”, so I just gotta check: Are you saying that everyday people would be willing and able to spend $15000 on a luxury handbag?

>thing >:(

>thing, Japan :O

It's an economic fact that a factory worker in Japan will have a higher salary and more overhead than a similar worker in Vietnam or China.

When sales are still growing YoY (like the post covid market), but prices are up 30% or 40%, you understand your customer is still willing to pay the higher price

Its similar to a McDonalds or Starbucks situation where you just keep increasing prices dramatically until you get a first quarter of lower than expected sales, then you start adapting downwards

Most corporations still haven't hit that limit, see streaming companies increasing prices every few months, they still haven't hit the point where profits decrease YoY. When they do the streaming prices start decreasing

You won't die if you stop watching Netflix. We aren't talking food or medicine here. In fact your life would probably improve. But addiction is a real animal.

Screen addicts almost never stoop that low and the ones that do are addicted to a cam girl (e.g., Grant Amato), porn or gambling, not Netflix (or social media).

This is the easiest money and best relationship JPM could imagine

Wow, that's slightly more than Yahoo has. Well, had.

We don't know how ripe OpenAI's industry or market position is, yet. Yahoo knew what they had lost pretty early onto its spiral.

In a way this is probably the future state - 1000 different clients for 1000 different people, each fully customized to their taste

Still miss Apollo

I haven't used it since it became paid, but back then Junie was slow and thoughtful, while Cursor was constantly re-writing files that worked fine, and Claude was somewhere in the middle

kiro from amazon does both tasks (in tasks.md) and specs.

Too many tools soon, choose what works for you

On the other side of this, Firebase probably doesn't have money at stake making the update

Is that true in this case or are you speculating? My company runs a cloud platform. Our strategy is to have outages happen as rarely as possible and to proactively offer rebates based on customer-measured downtime. I don't know why people would trust vendors that do otherwise.

We should probably avoid punishing them based on free-associating made by a random not-anonymous not-Googler not-Xoogler account on HN. (disclaimer: xoogler)

https://downdetector.com/

(n.b. as much as Google in aggregate is evil, they're smart evil. You can't avoid execs approving every outage because checks without some paper trail, and execs don't want to approve every outage, you'd have to rely on too many engineers and sales people, even as ex-employees, to keep it a secret. disclaimer: xoogler)

(EDIT: for posterity, we're discussing a "overall status" thing with a huge refresh button, right above a huge table chockful of orange triangles that indicate "One or more regions affected" - even when the "overall status" was green, the table was still full of orange and visible immediately underneath. My point being, you gotta suppose a wholeeee bunch of stuff to get to the point there was ever info suppressed, much less suppressed intentionally to avoid cutting checks)

One of the many definitions I have for AGI is being able to create the proofs for the 2030, 2050, 2100, etc Nobel Prizes, today

A sillier one I like is that AGI would output a correct proof that P ≠ NP on day 1

aren't you thinking about ASI/ Superintelligence way capable of outdoing humans?

The goalposts are regularly moved so that AI companies and their investors can claim/hype that AGI will be around in a few years. :-)

Now we're up to o4, AGI is still not even in near site (depending on your definition, I know). And OpenAI is up to about 5000 employees. I'd think even before AGI a new model would be able to cover for at least 4500 of those employees being fired, is that not the case?

OpenAI is at a much earlier stage in their adventures and probably doesn't have that much baggage. Given their age and revenue streams, their headcount is quite substantial.

Not directly from OpenAI - but people in the industry is advertising how these advanced models can replace employees, yet they keep on going on hiring tears (including OpenAI). Lets see the first company to stand behind their models, and replace 50% of their existing headcount with agents. That to me would be a sign these things are going to replace peoples jobs. Until I see that, if OpenAI can't figure out how to replace humans with models, then no one will

I mean could you imagine if todays announcement was - the chatgpt.com webdev team has been laid off, and all new features and fixes will be complete by Codex CLI + o4-mini. That means they believe in the product theyre advertising. Until they do something like that, theyll keep on trusting those human engineers and try selling other people on the dream

So far the only significant human replacement I'm seeing AI enable is in low-end, entry level work. For example, fulfilling "gig work" for Fiverr like spending an hour or two whipping up a relatively low-quality graphic logo or other basic design work for $20. This is largely done at home by entry-level graphic design students in second-world locales like the Philippines or rural India. A good graphical AI can (and is) taking some of this work from the humans doing it. Although it's not even a big impact yet, primarily because for non-technical customers, the Fiverr workflow can still be easier or more comfortable than figuring out which AI tool to use and how to get what they really want from it.

The point is that this Fiverr piece-meal gig work is the lowest paying, least desirable work in graphic design. No one doing it wants to still be doing it a year or two from now. It's the Mcdonald's counter of their industry. They all aspire to higher skill, higher paying design jobs. They're only doing Fiverr gig work because they don't yet have a degree, enough resume credits or decent portfolio examples. Much like steam-powered bulldozers and pile drivers displaced pick axe swinging humans digging railroad tunnels in the 1800s, the new technology is displacing some of the least-desirable, lowest-paying jobs first. I don't yet see any clear reason this well-established 200+ year trend will be fundamentally different this time. And history is littered with those who predicted "but this time it'll be different."

I've read the scenarios which predict that AI will eventually be able to fundamentally and repeatedly self-improve autonomously, at scale and without limit. I do think AI will continue to improve but, like many others, I find the "self-improve" step to be a huge and unevidenced leap of faith. So, I don't think it's likely, for reasons I won't enumerate here because domain experts far smarter than I am have already written extensively about them.

wow the sales go hard in this product

Deep learning models will continue to improve as we feed them more data and use more compute, but they will still fail at even very simple tasks as long as the input data are outside their training distribution. The numerous examples of ChatGPT (even the latest, most powerful versions) failing at basic questions or tasks illustrate this well. Learning from data is not enough; there is a need for the kind of system-two thinking we humans develop as we grow. It is difficult to see how deep learning and backpropagation alone will help us model that. https://medium.com/thoughts-on-machine-learning/why-sam-altm...

So at least two years old?

Oh, not that I haven't been as knocked about in the interim, of course. I'm not really claiming I'm better, and these are frightening times; I hope I'm neither projecting nor judging too harshly. But even trying to discount for the possibility, there still seems something new left to explain.

We're living in extremely uncertain times, with multiple global crises taking place at the same time, each of which could develop into a turning point for humankind.

At the same time, predatory algorithms do whatever it takes to make people addicted to media, while mental health care remains inaccessible for many.

I feel like throwing a tantrum almost every single day.

I've been out in the streets, protesting and raising awareness of climate change. I no longer do. It's a pointless waste of time. Today, the climate change deniers are in charge.

I've lived in this neighborhood a long time, and there are a couple of old folks' homes a block or so from here. Both have excellent views, on one frontage each, of an extremely historic cemetery, which I have always found a wonderfully piquant example of my adopted hometown's occasionally wire-brush sense of humor. But I bring it up to mention that the old folks don't seem to have much concern for spoons other than to eat with, and they are protesting the present situation regularly and at considerable volume, and every time I pass about my errands I make a point of raising a fist and hollering "hell yeah!" just like most of the people who drive past honk in support.

Will you tell them it's pointless?

Users can do that if they want, but it’s more effective and more efficient to do that after every billion chats, and I’m sure OpenAI does it.

Yes, you can keep finetuning your model on every chat you have with it. You can definitely make it remember everything you have ever said. LLMs are excellent at remembering their training data.

But, we don’t need AGI/AHI to transform large parts of our civilization. And I’m not seeing this happen either.

This is the ai-2027.com argument. LLMs only really have to get good enough at coding (and then researching), and it's singularity time.

It's not only definition. Some googler was sure their model was conscious.

They’d happily lose a queen to take a pawn. They failed to understand how pieces are even allowed to move, hallucinated the existence of new pieces, repeatedly declared checkmate when it wasn’t, etc.

I tried it last night with Gemini 2.5 Pro and it made it 6 turns before it started making illegal moves, and 8 turns before it got so confused about the state of the board before it refused to play with me any longer.

I was in the chess club in 3rd grade. One of the top ranked LLMs in the world is vastly dumber than I was in 3rd grade. But we’re going to pour hundreds of billions into this in the hope that it can end my career? Good luck with that, guys.

An Alpha Star type model would wipe the floor at chess.

These models cannot even make legal chess moves. That’s incredibly basic logic, and it shows how LLMs are still completely incapable of reasoning or understanding. Many kinds of task are never going to be possible for LLMs unless that changes. Programming is one of those tasks.

Yeah they can. There's a link I shared to prove it which you've conveniently ignored.

LLMs learn by predicting, failing and getting a little better, rinse and repeat. Pre-training is not like reading a book. LLMs trained on chess games play chess just fine. They don't make the silly mistakes you're talking about and they very rarely make illegal moves.

There's gpt-3.5-turbo-instruct which i already shared and plays at around 1800 ELO. Then there's this grandmaster level chess transformer - https://arxiv.org/abs/2402.04494. They're also a couple of models that were trained in the Eleuther AI discord that reached about 1100-1300 Elo.

I don't know what the peak of LLM Chess playing looks like but this is clearly less of a 'LLMs can't do this' problem and more 'Open AI/Anthropic/Google etc don't care if their models can play Chess or not' problem.

So are they capable of reasoning now or would you like to shift the posts ?

You don't have to pretrain it for every little thing but it should come as no surprise that a complex non-trivial game would require it.

Even if you explained all the rules of chess clearly to someone brand new to it, it will be a while and lots of practice before they internalize it.

And like I said, LLM pre-training is less like a machine reading text and more like Evolution. If you gave a corpus of chess rules, you're only training a model that knows how to converse about chess rules.

Do humans require less 'pre-training' ? Sure, but then again, that's on the back of millions of years of evolution. Modern NNs initialize random weights and have relatively very little inductive bias.

What it can do is write and execute code to generate the correct output, but isn't that cheating?

(Unless you're arguing against the idea that LLMs are making programmers obsolete, in which case I fully agree with you.)

When I was trying to understand what is happening with hallucination GPT gave me this: > It's called hallucinating when LLMs get things wrong because the model generates content that sounds plausible but is factually incorrect or made-up—similar to how a person might "see" or "experience" things that aren't real during a hallucination.

From that we can see that they fundamentally don't know what is correct. While they can get better at predicting correct answers, no-one has explained how they are expected to cross the boundary from "sounding plausible" to "knowing they are factually correct". All the attempts so far seem to be about reducing the likelihood of hallucination, not fixing the problem that they fundamentally don't understand what they are saying.

Until/unless they are able to understand the output enough to verify the truth then there's a knowledge gap that seems dangerous given how much code we are allowing "AI" to write.

It also assumes they "understand" enough to be able to extract the correct output to test against.

Because the conversation is about AGI, and how far away we are from AGI.

What if it is a dumb AGI?

I remember being extremely surprised when I could ask GPT3 to rotate a 3d model of a car in it's head and ask it about what I would see when sitting inside, or which doors would refuse to open because they're in contact with the ground.

It really depends on how much you want to shift the goalposts on what constitutes "simple".

Compare to what a software engineer is able to do, it is very much a simple logic task. Or the average person having a non-trivial job. Or a beehive organizing its existence, from its amino acids up to hive organization. All those things are magnitudes harder than chess.

> I remember being extremely surprised when I could ask GPT3 to rotate a 3d model of a car in it's head and ask it about what I would see when sitting inside, or which doors would refuse to open because they're in contact with the ground.

It's not reasoning its way there. Somebody asked something similar some time in the corpus and that corpus also contained the answers. That's why it can answer. After a quite small number of moves, the chess board it unique and you can't fake it. You need to think ahead. A task which computers are traditionally very good at. Even trained chess players are. That LLMs are not goes to show that they are very far from AGI.

The best model you can play with is decent for a human - https://github.com/adamkarvonen/chess_gpt_eval

SOTA models can't play it because these companies don't really care about it.