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A return to less centralized web publishing would also be bad for the many creators who lack the technical expertise or interest to jump through all the hoops required for building and hosting your own website. Maybe this seems like a pretty small friction to the median HN user, but I don't think it's true for creators in general, as evidenced by the enormous increase in both the number and sophistication of online creators over the past couple of decades.

Is that increase worth traumatizing moderators? I have no idea. But I frequently see this sentiment on HN about the old internet being better, framed as criticism of big internet companies, when it really seems to be at least in part criticism of how the median internet user has changed -- and the solution, coincidentally, would at least partially reverse that change.


Content hosting for creators can be commoditized.

Content discovery may even be able to remain centralized.

No idea if there's a way for it to work out economically without ads, but ads are also unhealthy so maybe that's ok.


I mean, the technical expertise thing is solvable, it’s just no-one wants to solve it because SaaS is extremely lucrative."

Where are you getting 10X? If I look at, say, Merck, their "sales, general, and administrative expenses" [1] trends at even or slightly higher than their R&D expenses [2]. Abbvie's ratio is around 2x [3, 4].

AFAIK, SG&A is the number that groups criticizing pharmaceutical companies look at, even though it includes a lot of money spent on things like paying lawyers, which any pharmaceutical company that actually wants to make back the billions spent on developing drugs will have to do.

[1] https://www.statista.com/statistics/269499/merck-and-co-sgan...

[2] https://www.statista.com/statistics/282738/expenditure-on-re...

[3] https://www.macrotrends.net/stocks/charts/ABBV/abbvie/sellin...

[4] https://www.statista.com/statistics/417068/r-and-d-expenditu...


That's how it was described to me by several R&D staff at JnJ two decades ago.

Do you have evidence for "most new treatment research is government funded (and by governments of other countries)"? My understanding is that the opposite is true: big pharmaceutical companies foot most of the bill for developing new drugs, then US-based insurers pay high costs, and most "other countries" enjoy much lower prices because US healthcare is effectively subsidizing their drug prices.

It’s both working together- the basic research, including identifying targets and new chemistry and in some cases even the drugs themselves are mostly academia. However, clinical trials, and drug development that iterates the chemical structure itself and delivery approaches is very expensive, and almost entirely done by industry. Often the academics are working collaboratively with pharmaceutical- and can have either government or pharmaceutical funding for these projects. I’m an academic PI that has discovered and patented new drugs and licensed them to industry.

Thanks. Do you have some sense of the breakdown in actual expenses incurred by the basic research and subsequent industrial development? It may qualitatively be true that many governments sponsor basic research that is later productized, but if the second bit costs 1000x more than the first bit, it's not exactly a fairly shared cost.

I don’t know the numbers off the top of my head, but most likely substantially more of the money is from industry. However, just answering that requires really carefully defining the question- because much academic research that happens to lead to new drugs or drug targets is basic medical and biology research- do you also include all biological research that does not turn out this way? On the industry side do you include all biotech startups hoping to sell to big pharmaceutical companies including the majority that do not?

Clinical trials are incredibly expensive but also comparatively straightforward and require a very different set of facilities and skills from basic research. Pharma mostly could not recruit away the people with these skills from academia- they can’t offer the same freedom and job security, but the academics often found startups they work for on the side and ultimately sell to pharma if it works out. So comparing money spent isn’t the entire picture of relative contribution- as they are each doing parts the other is not equipped for.


You are correct.

> For some reason people on HN imagine that

It's an easy simplifying heuristic to suppose that countries are all self-interested and nobody actually cares about "norms" or "war crimes" or "not filling low-orbit space with satellite fragments", because you get to forget about a lot of context and motivations and just put on your game theory hat and go, but like most simplifying heuristics that make things cleaner to think about, the conclusions this leads you to should be taken with a grain of salt


> you get to forget about a lot of context and motivations and just put on your game theory hat and go

Great insight.


This is the thing that actually worries me the most about AI. Right now there are meaningful practical obstacles to, say, manufacturing ricin or 3-D printing a working gun or figuring out how to kill somebody with a drone, and apparently these practical obstacles are enough to deter a nutso but insufficiently committed/intelligent/methodical would-be assassin, but if you have a chatbot that will happily talk you through the whole process, maybe that equilibrium changes.


Same, and the story is really of all technology. A suitable amount of friction is the invisible force that holds together much of society. We have to be very careful about what activities and actions we make easy to do, because if destruction is simple, we will be governed by the laziest and most stupid among us who will harness it without thought or care. The same goes in the opposite direction; if everything is hard to do, our dynamism is oppressed.


You need a certain degree of practicality to do proper damage to infrastructure, the trades have it in spades but political types not so much. You have to have some mental model of which parts of the system are hard to replace. Sometimes this is not immediately obvious, e.g. signalling equipment vs track damage or transformers vs line damage.

TBH most people's threat models haven't really caught up with the reality of battery powered tools and carbide / bimetal blades. A small number of organised protesters could quickly disable a lot of infrastructure with a few k of milwaukee, some wrecking bars & utility keys. It's been interesting to watch the "blade runners" in London solo this, still haven't seen a coordinated group do it on a large scale.


You don't need AI for that, just look it up on Reddit


The chatbot can't even give me a code sample which doesn't hallucinate APIs - something that is easily machine-verifiable.

Asking it to do something complicated that's not machine verifiable and expecting it to be correct is science fiction.


I'm not sure what chatbots you're using, but the big free ones at this point can and, in my experience, typically do give valid code samples for a surprising range of tasks. I'm skeptical about LLMs as the ultimate future of AI, but they aren't useless.


Another great Kidder book is "House", which applies the same perceptive profiling to the people involved in building a single house -- the couple, the architect, and the construction workers. There's an argument that a lot of the best work is done not in pursuit of an external reward but because doing good work is itself rewarding, and one way of viewing these books is as immersive explorations of how that plays out.


Tangential, but

> 1: a CDC meta-review said that 26% of surveyed US trans students attempted suicide this year, N=20,103 surveyed, ~660 of which were trans. https://archive.ph/0H81G

This paper also finds that 5% of cisgender male and 11% of cisgender female students (out of ~8k surveyed for each) attempted suicide in the past year. It's kind of strange, because the age <=18 suicide rate (of "completed" attempts) is much smaller, approximately 1 in 5,000 to 1 in 10,000 [1].

[1] https://www.cdc.gov/nchs/data/vsrr/vsrr024.pdf, Figure 3


> It doesn't say anything about the inverse.

Interpreted as a literal propositional statement, it's saying "if you have a good attitude, then you will have success". Therefore if you do not have success, it must be because you did not have a good attitude, which is your fault. It's the contrapositive, right?


If you take "determines" to mean "is the sole determining factor ... at a given instant" then yes. But with a more conventional reading, unless you define a time-frame, deny randomness or otherwise specify an outcome - no. "Will have" is a stronger rephrasing, but even with this wording it wouldn't necessarily blame your attitude as long as you're alive (and if one believes in afterlife the promise may as well never expire).


> Aspects of society that conventional wisdom holds to be outside or above the influence of tech and media, things like government, we suddenly realize are downstream from a single, monolithic technological communications machine that spans every screen and has its own biases.

> Covid-19 revealed that the Media/Tech Complex is capable of acting as a single unified entity if necessary. That makes them more powerful than the Roman empire ever was.

This article is long on ominous assertions about the incredible power of the "Media/Tech Complex" and short on actual evidence of that power. The main piece of evidence seems to be: look how they all said similar things at the beginning of the pandemic! But this seems like a weak example -- you may as well say getting a tornado warning on your phone and on the local TV news is evidence of the same thing.

The claim that Media/Tech is "monolithic" is also pretty weird to me. There are popular articles from big media companies tut-tutting "Big Tech" every week. They don't seem to be good friends.


> we're not much different from a 3rd world failed state like Venezuela

In 2016, Venezuela's murder rate was well over 50 per 100,000, and the USA's murder rate was slightly over 5 per 100,000 [1]. This gap is pretty consistent.

[1] https://dataunodc.un.org/crime/intentional-homicide-victims


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