There's a critical difference between "we don't think we will add it" (what you quoted) and "we won't add it because we think you don't need it" (what OP claims)
> And why exactly are we "hoping for a global currency revolution"
So that Visa and MasterCard can't censor things they don't like. So that PayPal can't block creators from withdrawing money because they made a Japanese style game
Blanket dismissal of regulations is about as silly as a blanket dismissal of laws. Some laws are "bad", some are "good", but the point is who do they hurt, and who do they serve? Regulations are tools, like laws, and can be written to serve the needs of the people, for good things.
I'm not even saying this should be dismissed with a blanket dismissal.
First example is a reminder that regulation can be bad.
Second is an actual concern about this specific regulation. This is a concrete concern about the incentives it creates. There wasn't a single response to this comment about exactly WHY questioning effectiveness of it is irrational.
> Second is an actual concern about this specific regulation. This is a concrete concern about the incentives it creates.
Like I said in my OP comment, the problem with saying "this regulation will push devs to subscription-based game models" is that it does not explain why that would happen. It just assumes it would.
This argument to me is like saying "forcing people to wear seatbelts will push them to take the bus instead". Why would this be such a problem that people ditch their whole mode of transit? I see it that way because I can't think of a single case where designing your game server architecture with decommissioning and redistributing to your users in mind would be difficult or costly at all, and I have seen no convincing explanations
At least historically, Google prioritized not hiring bad candidates over hiring good candidates. So it was neither a priority for interviews to be consistent (for good candidates) or for employees to be able to consistently pass interviews.
That certainly makes sense as a goal, given the cost of hiring someone bad and then not being able to get rid of them.
The problem is that companies like Google that have evaluated their own hiring process, by comparing candidates "hiring score" with subsequent on-the-job performance, have found that there is little correlation. So, while the goal (be more concerned about false positives than false negatives) makes sense, their process of trying to achieve this is broken.
I feel like this kind of tool has been completely obsoleted by LLMs (even local models). I've used similar tools such as tiny for Emacs, which is a DSL for generating text based on numeric ranges. Now, it's simply more efficient to ask AI.
Quite plausible. I built most of it in May 2025 (1 year ago) before I even looked at LLMs for coding, and announced it in Oct 2025[1]. I started it principally as a mechanism to dog-food Jiff[2]. Jiff has not been obsoleted by LLMs and is exactly the sort of thing an LLM would add as a dependency to a Rust project. This ended up being an extremely useful exercise because it did lead to some Jiff improvements.
Fun fact: ripgrep started as something to dog-food the regex crate (with a focus on performance). I didn't originally build it to release to end users funnily enough. To be clear, I'm not implying bttf will follow the same path. I honestly probably agree with you at this point. I wouldn't have 1 year ago though.
I believe AI-for-everything will become unsustainable financially for many and I’m genuinely curious to see how people deal with it. When to use it? When is it wasteful?
My big hypothesis is that tokens are going to get much more expensive. Either that or OpenAI/anthropic are going bankrupt. I’m almost excited to find out, I have to admit.
Your remark just reminded me of this, I went a bit off topic, I admit.
Have you tried DeepSeek V4 Flash? It's very competent and extremely cheap.
I think Gemma 4 is also a good example of a capable small model.
I mention these not only because they're cheap but because they can run on consumer devices. The "every year bigger and more capable SOTA model" trend is mirrored by "the every year smaller and more capable open source model" trend.
256GB is what deepseek v4 flash with Q4 requires I believe. It is really still very far from “running locally on your device”. And it’s getting further away every day, looking at how the electronic market prices are surging.
I need to find stats on average RAM of personal devices, but I expect it will be so low, we are light years away from running a frontier model (from today) locally on a smartphone, let’s stop dreaming (and I really would love having it).
I do agree local models are progressing and I am to this day in awe at what a 50GB file can do – it still feels like black magic to me.
Also granted, something like Gemma 2 2B seems to have similar performance to ChatGP 3.5 and only require 2GB of RAM. But I think the RAM/performance ratio curve over time is logarithmic and not linear, it’s moving slower and slower.
Not really. Similarly to humans, it's easier to write code than read it; LLMs aren't particularly less efficient at doing off the cuff tasks vs reading in all of the tokens of documentation for a specific tool (assuming you did the legwork of manually feeding that tool to the LLM, which makes it less efficient for you) and then coming up with a solution. And that argument would only apply if there were custom tools for each of the infinite possible tasks, which there aren't.
Indeed, Japanese houses are designed to be disposable. Likely a result of them being built historically out of wood and paper and the abundance of wood.
Japanese "disposable houses" was a policy implemented after WW2, to rapidly rebuild the country as well as keeping a lot of people employed. And indeed a house has traditionally dropped faster in value after purchase than even cars.
And this policy has also meant that houses haven't been insulated, and very often haven't been strong against earthquakes, the latter is kind of baffling in this earthquake-prone country (the Noto earthquake on Jan. 1 2024 flattened large areas of houses, with nothing left standing). It's only gradually, through certain code changes implemented a couple of times post-1980 that things are improving. But it was as late as just a few years ago that the Japanese government hesitated, and in the end didn't implement certain new building standards, because that would put a LOT of makers out of work as they didn't have the competance to build to those standards. But this has finally changed, with the latest update a year ago.
I have to take issue with the ".. out of wood and paper". Because that's not the cause. There are buildings here literally a thousand years old and built of wood, still standing, after centuries of sometimes unbelievably big earthquakes. And wooden homes built properly these days handle earthquakes as good as anything else. It's not the material, it's how it's done which matters.
Source: Researched a lot of house building companies the last couple of years. Some of them, building wooden houses, have been in business for a long time and haven't had a single house as a victim of earthquakes for half a century, with the occasional exception where the earth has literally flipped over. Nothing can handle that. But "ordinary" earthquakes? All still standing. There are photos around showing certain houses alone on a field of flattened buildings. These guys.
It's not just that. Houses are a consumer good instead of an investment, yes, but a large percentage of Japanese people live in apartments that are built to last and be renovated (because they ARE investments).
The difference is partly the attitude towards houses, but it also has to do with how difficult it is for foreign investors to speculate in the market, the ubiquity of public transit (which makes accessibility as a value-driving feature mostly moot), the way the building code precludes a "missing middle" (or "missing cheap place"), and other features of modern Japanese society that are alien to Americans (and Canadians, but weirdly not always to Britons).
The point is that there are lots of ways to chip away at the affordability issue. It's just that ALL of them necessarily attack RE investors' ability to exploit their property to the fullest extent possible.
One last anecdote: South Korea is similarly situated to Japan, but is also facing an extreme affordability crisis. So, there is the suggestion that NONE of the material aspects matter if the owner class is determined to wring every cent out of you. The changes disincentivize gouging, but in the end, you just have to have property owners willing to acknowledge housing as a an affordable necessity and not a profit center built on the backs of a captive audience...
You may need to retake economics 101 perhaps if you think raising a wage floor has a single predictable outcome in every scenario, which seems to be what you are implying.
It puts varying pressures on other elements in a dynamic system in different ratios and with second order effects that can’t be fully predicted until you “run the experiment.”
You don't know what the definitive predictable identical outcome would be. But you know the effect at the margin.
At the margin, a wage floor will prevent some percent of transactions that would have taken place if a wage floor was not in place. It's not complicated. Some people will benefit, sure, but some commerce just won't take place.
Consider a price floor on selling a used car. Suppose you had a car to sell. Would it make you feel better if there were a law that prevents you from selling your car for less than some amount? Sure maybe without the floor, your car would have sold for less than the floor amount. But would you want a price floor as a seller of a car? How about as a buyer of a car?
Chances are if your car is worth less than the floor, no one will buy your car now. The price floor doesn't magically make your car more valuable, just makes it harder to sell.
You don't actually know that. It's too simple a model. Real world data on minimum wages do not bear it out.
There are more variables than the graphs you get in the first two weeks of Econ 101. If you make it to the end of the semester, or even to the midterm, you'll know that the simple predictions you got on the first quiz were false.
I think it does bear that out in general, although it is slightly more complicated. What seems to happen
1. Low-wage workers, as a collective group, experience an increase in earnings (Dube & Zipperer, 2024).
2. Total job losses do take place, but are minor and teens/part-time/new entrants workers lose more often (Belman & Wolfson, 2014; Redmond & McGuinness, 2024).
3. Lost hours & increased prices - businesses primarily absorb the cost by slightly reducing weekly hours worked & increasing prices for consumers (Redmond & McGuinness, 2024)
I would agree that modest minimum wage increases are far from the worst thing the government does, compared to other government interventions.
>You may need to retake economics 101 perhaps if you think raising a wage floor has a single predictable outcome in every scenario, which seems to be what you are implying.
>It puts varying pressures on other elements in a dynamic system in different ratios and with second order effects that can’t be fully predicted until you “run the experiment.”
Now replace "raising a wage floor" with "tariffs". Just over a year ago Trump administration cheerleaders were making similar arguments about "dynamic system" and "second order effects" to justify tariffs, predicting that prices might even drop due to [insert handwaving about fx rates].
Most predictions about the Trump tariffs from Trump and the people railing against them have proven to be hugely incorrect in both directions. If anything this proves my point that these are complex systems that are hard to predict.
>Most predictions about the Trump tariffs from Trump and the people railing against them have proven to be hugely incorrect in both directions
Really? Which ones? For the ones predicting economic calamity, they get a pass because they were didn't take into account TACO, which might be bad if you're grading it as a forecast, but hardly is a mark against them when it comes to economic analysis on the effects of a policy.
Do they? It's an interesting question whether resources can be spawned by fiat. I think the only entity capable of doing so is the government, i.e. when it prints money.
Well companies can issue stock, which is more or less spawning resources, but that's not what I meant. When people with more money than they need want more of it, things get done, including fucking over the customers, the partners and the workers. When wageslaves want more money they get dragged through the media for their greed (as is happening now).
Because then fewer people will use Uber. Customers don't have a whole-economy view. If you raised the price of an Uber to $200 a ride minimum, would that be a good thing? After all, workers paid more spend more, stimulating growth at all levels!
It's a bit like California raising fast food minimum wages causing thousands of jobs to be lost[0].
> TFPP Wire helps you stay ahead with breaking news, analysis, and bold <<conservative>> insights on the economy, politics, national security, culture, and more.
It quotes California Globe:
> About Us
> California Globe is an independent, professional news website obsessively chronicling everything political throughout the state of California. We are <<pro-growth and pro-business>>, non-partisan and objective; we report what we see and hear without fear or favor.
"pro-growth and pro-business" (dogwhistle for conservative), I'm sure their reporting is super unbiased, their sources are obviously not incentivized to distort facts.
Oh, wait:
> Explained Altaf Chaus, who owns and operates three Burger King franchise restaurants in San Jose
Ah, yes, the capitalist is complaining.
> By June 2024, <<Stanford University>> found that over 10,000 fast food jobs were already lost.
> The "Stanford University" study behind that 10,000-jobs figure is an article titled "California Loses Nearly 10,000 Fast-Food Jobs After $20 Minimum Wage Signed Last Fall," written by economist Lee Ohanian and published April 24, 2024 by the <<Hoover Institution>>. The Hoover Institution is a think tank located on Stanford's campus and affiliated with the university, which is almost certainly why outlets describe it as a "Stanford University" finding. (Hoover itself notes that opinions on its site don't necessarily reflect the views of the Hoover Institution or Stanford University.)
> <<Here's the catch: the article has been retracted.>> According to the notice now on the page, the author cited data reported by the Wall Street Journal and interpreted those data as being seasonally adjusted; following publication, those data were identified as not being seasonally adjusted, so the article was retracted to avoid misinformation. The seasonal-adjustment issue matters a lot here, because fast-food employment naturally fluctuates with the seasons, so unadjusted month-to-month numbers can show "losses" that are really just normal seasonal patterns.
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