I wondered the same. ff and fi are common ligature letter pairs, maybe the original is in an encoding where those are represented with separate characters, which then correspond to § and Ö in whatever encoding we find here?
3,922 karma · joined March 31, 2007
e: my username @berkeley.edu - put “HN” in the subject line
w: zamfi.net
But I think it's actually a much deeper indictment of the incumbents who couldn't present a vision more appealing than the "madness on television".
Hmm -- this seems a bit apples and oranges to me: collaborative editing is sync; git branches, PRs, etc. are all async. This is by design! You want someone's eyes on a merge, that's the whole rationale behind PRs. Collab editing tries to make merges invisible.
Totally different use case, no?
Shareholders are of course free to sue the board for acting outside of the interests of the shareholders overall, but this happens very rarely because typically the company would otherwise be shutting down and it’s very hard to make the argument that the deal undervalues common shareholders’ shares.
If you‘re just a regular employee with some options, and the acquirer doesn‘t want to keep you on, you should expect nothing.
In other words it sounds like you’re arguing that the root cause is “the transactional nature” but that’s the one thing that hasn’t changed. So why is it worse now?
What is it that makes students “better equipped to ignore you”?
If so, why would transactional-ism be the cause?
Read on:
> The average student has seen college as basically transactional for as long as I’ve been doing this. They go through the motions and maybe learn something along the way, but it is all in service to the only conception of the good life they can imagine: a job with middle-class wages. I’ve mostly made my peace with that, do my best to give them a taste of the life of the mind, and celebrate the successes.
And then, crucially:
> Things have changed. Ted Gioia describes modern students as checked-out, phone-addicted zombies.
One classic example is in transistor networks: each node in a network (think interconnected logic gates, but at the analog level) accepts a wider range of voltages as "high" and "low (i.e., 1- and 0-valued) than they are specified to output. In 5V logic, for example, transistors might output 5V and 0V to within 5%, but accept anything above 1.2V as "high" and below that as "low". (Sometimes called the "static discipline" and used as an example of the "robustness principle"—the other name for Postel's Law.)
This is critical in these networks, but not because transistor manufacturers don't read or fully implement the spec: it's because there is invariably unavoidable noise introduced into the system, and one way to handle that is for every node to "clean up" its input to the degree that it can.
It's one thing to rely on this type of clean-up to make your systems work in the face of external noise. But when you start rearchitecting your systems to operate close to this boundary—that is, you're no longer trying to meet spec, because you know some other node will clean up your mess for you—you're cooked. Because the invariable noise will now push you outside the range of what your spec's liberal input regime can tolerate, and you'll get errors.
The problem isn't Postel's law. It's adverse selection / moral hazard / whatever you want to call the incentive to exploit a system's tolerance for error to improve short-term outcomes for the exploiter but at long-term cost to system stability.
This is only true generally, not within a specific neighborhood, and it's because of correlations between demand and density.
If you look at a neighborhood with mixed SFH and condos, the condo $/sqft is lower than the SFH $/sqft. (To be clear: that's $/sqft of housing space not of land).
Having a diversity of density enables home pricing at different points. Looking only at SFH (as this article does) is missing the forest for the trees, IMO.
Sure, but this is only a lucrative business because despite the land getting more expensive, the housing units are less expensive—otherwise who in their right mind would pay as much for one unit in a duplex/triplex/etc. as they'd have paid for a single-family home in the same location?
Not with that attitude!
Kidding aside, most people looking for housing aren’t buying land, they’re buying housing — which absolutely does not have elastic supply by policy, not by natural law.
It only feeds through to the price of certain classes of goods: housing, healthcare, education.
Those are also "markets" that are artificially supply-constrained, through zoning, the AMA, and accreditation.
To be clear, I'm not saying that we should get rid of zoning, the AMA, and accreditation—but we should be much more careful to avoid use of those tools to curb supply.
Not quite just those who refuse to sell — because housing costs impact the cost of every other local service, maintenance in a gentrified area often becomes unaffordable for those who hold out, and then they can’t afford it. Roof replacement is the classic example. Another example (though not as relevant to the 90 year old on social security) is childcare costs.
Take a look at the EPA "exception" that California has needed in order to impose more stringent fuel efficiency standards for automobiles.
Many forms of commerce or communication that are relevant across state lines (net neutrality rules, etc.) are considered a federal prerogative and states have limited ability to control these.
Yes, states could do more to fund research--and hopefully they will--but no state has the same level of tax rate as the federal government, and while the NSF budget is "noise" in the federal budget ($10B/$1.7T discretionary) it would be quite a big outlay for most states, even for California it would represent 3%+ of the total state budget to reproduce.
Though, now that I look at that number, maybe it's actually an opportunity for CA...
In most sciences, to actually secure the funding, you need to argue for why the problem is important, why the team has a shot at solving it, and what possible approaches look promising. Then you need to actually advise the team in supporting the work.
Chat is a great UI pattern for ephemeral conversation. It's why we get on the phone or on DM to talk with people while collaborating on documents, and don't just sit there making isolated edits to some Google Doc.
It's great because it can go all over the place and the humans get to decide which part of that conversation is meaningful and which isn't, and then put that in the document.
It's also obviously not enough: you still need documents!
But this isn't an "either-or" case. It's a "both" case.
Right now we have a ton of AI/ML/LLM folks working on this first clear challenge: better models that generate better defaults, which is great—but also will never solve the problem 100%, which is the second, less-clear challenge: there will always be times you don't want the defaults, especially as your requests become more and more high-level. It's the MS Word challenge reconstituted in the age of LLMs: everyone wants 20% of what's in Word, but it's not the same 20%. The good defaults are good except for that 20% you want to be non-default.
So there need to be ways to say "I want <this non-default thing>". Sometimes chat is enough for that, like when you can ask for a different background color. But sometimes it's really not! This is especially true when the things you want are not always obvious from limited observations of the program's behavior—where even just finding out that the "good default" isn't what you want can be hard.
Too few people are working on this latter challenge, IMO. (Full disclosure: I am one of them.)
By human standards, sure.
Weird take I know, but since only one female bee in the hive passes along her genes (which are shared with the other bees), it's a very different incentive structure.
Yes, but this is reflected in China's vacancy rate: 22% by some estimates.
In the US, home vacancy rates are sub-1%.
Not saying people aren't treating homes as investments, but it seems clear we also have a supply issue.
"Real Estate is Investment" should naturally lead to overproduction as investment-only properties get built to satisfy that demand—as we see in China. In the US, we don't see that.
Graphologue used a version of this too: https://hci.ucsd.edu/papers/graphologue.pdf
Total anecdote, but I worked on this for a bit for a research-level-code code editor (system paper to come soon, fingers crossed!) and found that basic find-and-replace was pretty brittle. I also had to be confident the source appears only once (not always the case for my use case), and there was a tradeoff of fuzziness of match / likelihood of perfectly correct source.
But yeah, diffs are super hard because the format requires far context and accurate mathematical computation.
Ultimately, the version of this that worked the best for me was a total hack:
Prefix every line of the code with L#### -- the line number. Ask for diffs to be the original text and the complete replacement text including the line number prefix on both original and replacement. Then, to apply, fuzzy match on both line number and context.
I suspect this worked as well as it did because it transmutes the math and computation problems into pattern-matching and copying problems, which LLMs are (still) much better at these days.
mRNA producing COVID spike proteins that the body then recognizes as foreign is exactly the mechanism of action for this class of vaccine, this was not hidden from anyone. It's not just "factual and proven"—as though there was some cover-up with major questions about it—it's literally the reason companies like Moderna and BioNTech exist.
Describing this mechanism as "self-assembling nano-structures" is technically true but sounds like scaretalk, which could lead one to question what exactly you thought you were getting.
Any chance you’ll make the source available?
There are about 50 extensions I’d make to it if I could! (And I’m sure I’m not alone.)
What will be the outcome of that shift? Some kind of better research?
On what basis do you think that field should agree with your perception?
On what basis do you think your perception is correct?
Note that I’m using “qualitative” and “quantitative” as stand-ins for whatever you think there’s too much of and too little of, respectively—please feel free to clarify if these words don’t effectively capture what you are trying to say.
It’s not at all important to me to attribute to you a “total rejection” of these methods, your writing implies to me that you have a preference for quant methods and think they’re better. You’re not, for example, complaining about too much quant methodology in economics, and too little qualitative. Sure, you don’t think that qual methods are bad per se, but you do think that the social sciences could use fewer of them, and that they’re overused.
I imagine you would agree that these methods can tell us different things, and that they’re not interchangeable for any given research question. You’d probably also agree that some fields bias towards certain types of questions, and that maybe the ratio of methods of work in a given field reflects the bias towards questions that are best answered by those methods. So, are you suggesting that entire fields should focus more on different questions, specifically those that can be answered quantitatively?
If not, I’m not sure I understand what the implications of your argument are.
For what it’s worth, here’s my bias: I am both a quantitative and a qualitative researcher, and I actually think the underlying issues holding back the production of generalizable knowledge have little to do with choice of methodology, and to the extent that they do, it’s in part due to a fetishization of quantitative methods that tell us something generalizable—but not necessarily something useful or even something true.
Pragmatically speaking, I'm unsure why you would choose this language if you wished to convey the nuance that qualitative methods are actually great, that you're merely wishing that more "empirical" studies would also be undertaken, where "empirical" I guess means "quantitative" and "rigorous" though you don't make that explicit.
For what it's worth, you absolutely can generalize from an observational case study. RCTs are not the only way of drawing generalizable conclusions—it depends a lot on what your epistemic goals are.
It kind of sounds like you don't like that some social sciences rely more on non-quantitative methods because you don't think those are definitive. That's fine, you're welcome to hold that belief, but let's not pretend like you're a fan of all methods and just wish there were a few more quantitative studies in sociology (or whichever discipline).
It feels like epistemic weaksauce to claim that entire fields explicitly reject the goal of generalizable knowledge because they question or reject “the scientific method” on the basis of “I’ve read some case study / qualitative papers”.
I guess the question is whether this role is still employable.