That's fine with me. I'd even appreciate that even more. I get one life on this miserable planet. I am going to do what I enjoy for as long as I can. Call me a blacksmith or a Luddite, I couldn't care less. One thing you can never call me is unhappy.
> In a few years we'll look at this the same way as people who unicycle or blacksmith.
It's equally likely that in a few years we see everyone who doesn't have skill the same way we view people who follow the Kardashians and other influencers: vacuous and incapable of non-augmented thought.
In a few years they will be the only competent people left who can save us from the deluge of AI slop. You should be nice to them, because you'll need them someday.
Do you think information is going to be destroyed or something? If this AI stuff is so sub par, why would anyone read/use/interact with it? Why wouldn't the "better" human created stuff float to the top?
The difference is that the textile machine workers could immediately verify the work product. This is impossible when the work product is a configuration of knowledge you don't actually have. It's why, for example, amateurs "solving" these open math problems refuse to discuss the results with actual mathematicians, because they can't. So we have a bunch of Lean-verified slop that may or may not actually prove what is claimed, without experts poring over everything line-by-line and reverse engineering.
ChatGPT was the fastest growing software of all time not that long ago. Citing a bad AI product as evidence for lack of demand is saying the failure of the Homer car was due to the fact that people don't like automobiles.
> ChatGPT was the fastest growing software of all time not that long ago.
Google+ was the fastest-growing social network of all time not that long ago.
When you're one of a pair of VC darlings that have effectively-infinite money because of -in part- handwavy promises to cure cancer and eliminate 90% of payroll everywhere, or if you're an established company that has total control over very widely used consumer products, you can do all sorts of things to manufacture amazing growth numbers.
In the case of those VC darlings, we're seeing their shift towards providing their products that are most expensive to create exclusively to B2B customers and also the shift towards justifying the elimination of most of their R&D expenditure. Every company performs belt-tightening in advance of their IPO, [0] and those two are no exception.
[0] ...which is when their finances will be scrutinized by the public and regulators...
You could have said this about Google's Search product...
How much would the average normie pay if Google suddenly charged? Sure the user-base would drop.
And what? Did Google suddenly become a bad business?
I find it funny how people have these strange and hypocritical viewpoints when it comes to OpenAI and Anthropic when the hyperscalars like Google, Amazon etc, followed these exact same kinds of playbooks for years and years.
I think you, and many LLM fans, have a grossly distorted view of per unit SaaS costs vs per unit current LLM costs.
Google Searches, once the infra setup was finished, were ridiculously cheap. Not the case for OpenAI & co.
Inflation adjusted, launching most of Google's core services (Search, Gmail, Maps, etc) cost less than launching ChatGPT 5. Running them at similar scales is also much cheaper per user.
There is a point at which it's just too much.
Oh, Google and Amazon never had these kinds of humongous losses and they reached profitability much sooner.
Well, Nvidia started out as a manufacturer first & foremost.
Maybe I'm in the middle of the road :)
Seems like economy, scale, velocity, and even "critical mass" are related in some way, but not the same at all.
I would say it's quite possible that economies of scale can go from positive to negative without much warning.
I think it's most sustainable financially when the underlying "economy" is what drives the resulting scale-up, which usually does occur in phases or stages where each successful milestone informs the next campaign more realistically than you can get any other way.
As market demand grows beyond baseline sustainability it becomes less costly to serve each additional customer this way.
The opposite effect could occur if meeting lofty scaling goals requires an ever increasing cost of customer acquisition beyond the point of unmet initial pending demand.
When the scaling process itself is what drives the activity without being limited by the actual buying power of the ultimate consumers at any one point, things can really get ahead of themselves. Accounting practices can be so diverse that the only way to be sure whether scaling ahead of the curve was actually "economical" is after liquidation ends up occurring.
Unfortunately, liquidation of one kind or another is more likely when the scale is based on hyperbolic dreams rather than more reasonably optimistic estimates. But who's to say which is which, and the continuum between them is blurry enough without any highly interested parties trying to muddy the waters even further. Who even knows if they've given it as much thought as it deserves, or if more clear-headed thinking could be the primary factor given what there is to work with :\
I've used the $200 dollar Anthropic plan @ Opus4/4.1, 4.5 and 4.8, and the $200 OAI plan from GPT5-6, and at every point in time my anecdotal experience is that the OAI limits are FAR more generous. I could consistently burn my weekly limits in ~36h on Opus, but it's hard to do it in less than ~72h with GPT.
It's really not a question, in every dimension I've confirmed it including socially across a lot of the heaviest users. There was a short period of time this was true it's not been true for months now.
If it was true, it would only be a very recent phenomenon, and it still doesn't match anecdotal reports from people I trust. If you have data to back up your assertions you should share it, otherwise you come across as very sus.
Lol @ sus though, I mean I am curious how this can be because I do see people saying Codex is more generous and wonder how it can be. I have too much usage for too long to have any doubts, but for all I know OpenAI black boxed me or Anthropic put me in some nice bucket, I wouldn't be surprised if they do that. I did see some mention that they can limit your tokens if they suspect you of things, though I forget the source of that.
That's not how it works. Look at AlphaEvolve. The model generates hypotheses and designs experiments, and the results of those experiments are fed into the next round, with notable results percolated up to humans for refinement.
The western labs are very AGI pilled, and their public models are distilled down from larger research-only models that are uneconomical to serve directly. They could (and probably will) start distilling models for more niche use cases eventually, but we're not there yet.
Any bench that puts GLM 5.3 ahead of 5.6 Sol is highly sus. They've been my two daily drivers since release, and I like GLM 5.3, but it's definitely not better than Sol, it's more ~Terra, while being significantly slower.
I had exactly the same thoughts. I often have similar thoughts on other benchmark sites, where supposed performance is way off base from my experience.
I’m not sure what the methodology of these are, but they certainly don’t match what I experience. Maybe I need to look deeper for relevant benchmarks.
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