There is a whole culture around the tech bros that enables them to believe that what is good for them is ipso facto good for society. This allows them to think of themselves not as the ruthless capitalist barons they are, but as actual helpers and patrons of society.

This is also the basic manifesto of venture capital. Profits are inherently good and "consolidating fragmented markets" (i.e. monopolism) is also inherently good because they bring "innovation" to "everyone".

It's an exaggerated kind of neoliberalism from people who spend very little time outside of a rather narrow world.

The notion that AI can solve political problems is pure balderdash. Political problems get solved when people organize and interact with each other in ways that create stability and trust and enable societal or policy changes that address the problem. You can run AI a million ways to "solve" climate change, but until something gets people to negotiate and adopt different ways of operating, all AI has done is burn compute (ironically exacerbating climate change) while generating another set of outputs that nobody pays attention to.

But these are not people who like the slow boring of political work; they'd rather fantasize about some computer doing that.

This is well put. I'd also add that people are relentlessly marketed to to consume more to support that economic growth. People from the 19th or early 20th century might well consider the amount of psychological pressure we get to buy things to be a relentless propaganda campaign.

I think there are some other points worth considering here. The "chasing arrows" logo was originally intended more for labeling material content than recyclability. And there is evidence that plastic/petchems industry has used this state of affairs to promote plastics as being much recyclable than they actually are.

Everything I've learned suggests that only plastics # 1-3 are "practicably recyclable" in that the material recovered from these has decent purity and can be used for a meaningful range of purposes. That's because plastics vary hugely in terms of their actual chemical composition and how they react to common recycling methods. In fact AFAICT really only cardboard and some metals recycle "usefully" at present. So if you are going put energy into recycling, aluminum cans and cardboard give the most ROI.

So there is merit to the argument that those arrows are, as they currently exist, misleading to consumers.

There's also merit to what you are saying in that tying the state of recycling facilities for a particular set of materials is inherently complicated.

IMHO the key question is how to get more materials to be actually and meaningfully recyclable, and how to set up waste collection so that more materials can be usefully recovered from existing waste streams.

I haven't read enough about this bill to figure out whether it's likely to help or hinder, but that's the benchmark that I'd apply.

There are considerably more than two sides to this issue...

Spot on.

What happens when people take someone's "cute OOTD" pic and put them in another outfit without any consent? That kind of stuff will get the young people off of Insta and looking back at Snap or VSCO others.

What happens when someone swaps a paid influencer's merch for another brand?

And that's not even touching the whole issue of non-consensual sexual content.

And why exactly do regular people who post like or want that content to be manipulated? What's the value to the primary content-making user?

The Zuckodei and Pinchmans of the world seem to think that people will make public content no matter what they do. I'm not naive enough to think they'll all migrate to Proton or privacy-preserving OSS stacks, but I do think even regular people have limited patience for having their thoughts, communications, and likenesses changed and monetized without benefit to them.

Great point. It's also really unclear how many Mythos found that are not/would not be found by open weight models.

This is pure marketing FUD, which is one of Anthropic's most advanced forms of "intelligence".

While I agree that many in the industry want the cheapest and the fastest to build regardless of quality, my question is about the demand side.

Who wants these apps? What is is that they do that someone is willing to pay for? How does that address the cost of the other inputs that make apps worth enough money or other rewards that someone wants to maintain them?

We are 18 years out from the launch of iPhone App store, and even though humans are far slower than AI in building apps, after nearly two decades I don't think there are massive parts of human activity that are un-apped. In pharmaceutical development, the dearth of "undrugged diseases" has led pharma companies to focus on rare and orphan diseases - bringing VERY high cost drugs to market to serve small numbers of people.

Where are the "orphan applications" that these apps are there to serve?

Vibecoding a delivery app stack will not make DoorDash obsolete - somebody still has to recruit drivers and food sellers and offer something to each of those parties that makes them want to drop DoorDash. DoorDash may be able to automate away some labor (though I suspect it will be less than they think).

In the enterprise, the theoretical "un-automated work" seems to be in two main buckets:
1- making presentations, dashboards, documents automatically, and
2 - building software automatically

Both of these clearly have some value, but I think the AI boffins and investors are wildly overlooking all of the human stuff that goes along with those tasks.

Also, it's obvious that AI makes that kind of stuff a commodity, meaning that its value goes down as its volume increases. So yeah, AI can make a lot of slop, but it's not obvious how that makes there be more valuable stuff.

Yeah, agreed. I actually am really struggling to understand how they think there is demand for this kind of thing. Is there market research where someone says "sure, I don't care who's talking, just as long as the content is a topic that I am plausibly interested in and the _conversation_ is not too jarring".
It's true that people will watch AI slop on YouTube; my guess is that is the demand signal they are responding to.

I have once watched an AI generated YouTube video (really it was weird graphics over an audio that sounded like Richard Feynman reading) and I found the explainer vaguely interesting enough to continue watching in the background for 20 min while I worked. I guess that channel got a few ad impressions off my eyeballs for that.

So I can see notionally how this kind of slop might win over some other slop in a transactional zero-sum way, but I really can't see how any of the typical marketing stuff - audience building, brand development, downstream sales conversions, fits in with AI-generated, undifferentiated commodity content. Isn't the whole idea of an influencer that the audience wants a person to connect them to content?

Maybe it will work, but my guess is it will just result in a lot more content that one has to wade through. I'm sure someone will have an AI solution to that. Turn that Hamster wheel up to ludicrous speed!

You are dead right. Agnosticism is much closer to a "null hypothesis" than atheism, yet many atheists like to present their view as "more scientific".

A really rigorous scientific examination pretty quickly comes to the conclusion that the existence of deities (in the spiritual, moral, and experiential ways that most deities are defined) is essentially impossible to prove or disprove with scientific examination of the material world.

In my own opinion it's because faith and religion are mostly about questions of meaning and purpose rather than physical assertions. One's reaction to the tenets of a religion are also experiential - if those tenets provide meaning clarity and improvement in one's being they make sense.

The other aspect of agnosticism is that I find attractive is a kind of intellectual humility. As a single, limited human being, who I am to say what is absolutely true in the metaphysical planes of existence?

I think his age is a big factor even without dementia.

Many older people I've seen have a much stronger "wow, look at this reaction" to new technology- they still see advances as minor miracles when myself and others see them as incremental progress.

I also think a lot of people in that generation have spent less time with psychology and are less prone to being aware of their own emotional and cognitive reactions. This means they don't spend much time reflecting on whether that "wow" reaction is a factual assessment or just an emotional reaction.

And of course the LLM vendors love having people debate this stuff, it keeps the "AI is magic" aura alive even when so much of what "AI" is making seems to be slop.

...and the Cybertruck range and launch date, and the Model 2, and the 4680 battery process, and...

Based on Musk's track record, you can pretty much count on this being a lot less than what is promised and a lot later.

I also just don't see the opportunity. I wouldn't call myself all that knowledgeable about WeChat and its ilk, but I think these "super apps" emerged as China's mobile revolution was taking off, meaning that people started out doing banking and ride sharing etc within these apps. In the US, all those services came out separately.

Admittedly the app landscape is fairly cluttered, but I just can't see the path to US consumers suddenly wanting to hail a ride inside of Xwitter. It's not how most Americans learned to hail rides, and the consumer value in having it all inside of Xwitter seems pretty minimal.

I'm not sure I fully agree. If you know what you're doing, LLM-based code can be quite helpful. I just built a Python scraper using Antigravity in a few hours that would've taken me many days of work and required a lot of effort to learn async function syntax.

It's not a super complex code base, so there's nothing architecturally complex about it. Even then, if I hadn't had a decent understanding of how playwright works, I would've had a much harder time debugging things and fixing some of the dumb decisions the LLM made.

The "anyone can build anything" hype is clearly bogus, but "people who can clearly specify things" can build a lot more than otherwise.

That's actually quite tricky for Google. LLM-based searches unquestionably cannibalize traffic to the web properties that make them the lion's share of their revenue.
However, they surrender their position directing traffic to websites to competitors like OpenAI or Anthropic, then they are far less able to make ad revenue period.

I think their hope is probably to outlast some of the hype cycle and then come in with decent products that leverage their current dominance in ad sales.

The argument that AI will reduce costs is deeply flawed, because it assumes that the interactions between insurers and providers will remain unchanged other than AI "doing the paperwork". That is very unlikely to be true, because both providers and insurers are likely to deploy AI to manage the new flows of information.

You're already seeing it in billing. On the provider side, AI goes through and harvests diagnoses that can justify higher billing ("increased coding intensity") while insurers are deploying AI that downcodes. Both have to pay the AI vendors, and now there's just more "paperwork" to keep track of.

The same way that adding lanes to a highway does not successfully keep travel times fast over the medium and long term - the lanes just fill up.

I agree with the point you're making - there are vast variations by geography such that this range can represent a very financially constrained lifestyle or a pretty comfortable income.

I'd also add one other big confounder, and that's overall household wealth (including one's family). If you are 24 years old and you are living with a relatively low salary, there is a huge difference between knowing can always pull the plug and live with your parents or go to grad school on their dime versus having nothing to fall back on. Same income, totally different life.

Or you can be making over $300K and supporting both your own kids AND your parents (plus possibly helping fill gaps for extended family) and still be pretty uncertain about your finances. That's justifiable, too - the monthly cost for a single person in skilled nursing is easily over $12K for many facilities. That ends when your parent/loved one dies, or they run out of money and go on Medicaid.

All that said, I believe it's true that the upper middle class has expanded. Part of why Trump's form of class warfare works is that the educated upper middle classes (of who I am member) have overall seen growth in income and wealth, but they don't see themselves as "rich" or "taking all the money". Trump has succeeded in pointing a lot of the lower 60%'s rightful economic frustrations at these folks, because they're visibly well off but want to be believe they are "middle class".

While I think the really rich need to pay in a hell of a lot more to the system, I also think the "true" upper middle classes (the subset of AEI's cohort that has a comfortable set of resources) also need to pay in more.

I have been an on-and-off user of OpenOffice/LibreOffice for many years, and I have to say I've always found it extremely clunky. By all accounts the OOO codebase is pretty convoluted.
Given how many variations of browser-based office suites now exist, I just don't see the point in starting from the OOO design or code.