The thing about an editor is that if you're not careful, your voice is lost. That's fine if the publication you're writing for has a distinctive voice or you have a specific style in mind; this article [1] describes the "New Yorker" voice as an example:

>The New Yorker sort of voice—or rather, the New Yorker voice I was using—is one that sounds on top, or ahead, of the material under discussion. It is a voice of intelligent curiosity; it implies that the writer has synthesized a great deal of information; it confidently takes readers by the hand, introduces them to surprising characters, recounts dramatic scenes, and leads them through key ideas and issues. The voice narrates the material in the first-person and describes the researcher conducting the research, encountering people, reacting to situations, thinking thoughts. The voice is smart-sounding. It is an effective voice for a lot of long-form journalism...

The "default" LLM voice isn't one that I find particularly appealing. For lack of a better term, it has these "zingers" every third or fourth sentence that, if you were writing a spammy piece, would be bolded/italicized. It also reads like the LLM has no faith in the reader's intelligence, or that it's trying too hard to make you feel smart.

This article has that feel to it. I'm not saying it was written by an LLM; I trust that the author isn't lying about only using it for editing. But it has that same style and voice that spammy LinkedIn/Facebook posts have.

[1]: https://www.publicbooks.org/ditching-the-new-yorker-voice/

Other commenters have covered the major reasons Excel is so popular. But Excel really shines because it's designed for business. I use R and RStudio for a lot of my work, and while it's great, there are little things that it can't do that Excel can.

It could be insider knowledge that Intel/AMD/other has made a huge step forward and has reduced Nvidia's moat (unlikely considering his public support for Nvidia's hardware, but possible).

It could be that the AI bubble is popping.

It could be that he wants to "lock in" the gains that Nvidia has made; having that much capital in one company tied to a pretty volatile sector is risky.

Maybe he thinks that the beneficiaries of AI will be B2B companies like Microsoft with connections to most major businesses.

Maybe it's a changing view on how much compute will be needed to fuel AI developments moving forward.

And this is just the list I could thing of off the top of my head. There are plenty of other reasons this move could be happening. Absent an inside line on Thiel, anything else is speculation.

Howrver, I was also pretty far behind in math for reasons unrelated to ability (standardized testing and secondary educational success indicate that I'm actually pretty good at math). I also left with very underdeveloped time management and study skills.

Could these downsides have been mitigated? Definitely, and my parents largely made sure they were. But in talking to my peers at the time, my parents after the fact, and parents of to hers that went to Montessori schools, I think the general idea holds.

Point being that self driven education is fantastic for a lot of reasons. But it will also let a lot of kids stay far behind their ability if not carefully monitored.

I would amend this somewhat to say that most ideologies have aspects that are much less effective in practice than they are in theory. I think this matches your sentiment, but addresses the likely rebuttal of "But X method has this specific element designed to address the shortcoming."

if that is the case you didn't experience a good montessori program, because that should have taken care of that.

I'm actually a huge fan of Montessori schools, including the one I went to. It was a great experience.

But in my experience and the experience of a lot of others I've talked to, Montessori schools aren't perfect. The method does really well fostering natural curiosity and harnessing it for learning. Essentially, it develops internal motivation super successfully.

But, as I've seen and heard from plenty of parents and at least one teacher, the method struggles with students that can't find that internal motivation. The sort of freedom a Montessori classroom gives you is not ideal for everyone. I think it's okay to admit that.

it was my impression that this should not be a problem, but i have to admit that my knowledge and experience with montessori is not enough to understand why this would or would not be the case.

if this is really a problem, it needs to be addressed, and i would find it surprising if it hasn't already been solved in the meantime. i don't believe that this is a new problem.

I just think that any method of education is a series of tradeoffs. Time management and difficulty working on thing you don't like (and a lot of this is personal experience, both my own and in discussions with others) seems to be the largest tradeoff.

Bottom line is that almost no system gets implemented perfectly, so it's important to understand the common "failure" points. This seems to be the Montessori one.

Thats not to say this is a bad thing! Depending on your beliefs, decreased study skills and/or mediocre time management are way less important than maintaining a natural curiosity. But the skills some kids end up missing are very important in traditional schooling environments like universities and high schools.

it's not about the claim. we can't afford it not to. at least not for a system that we would like to apply nationwide (which is what i would like to do with montessori) because we don't always have the luxury of multiple schools in one region where kids can switch. maybe not even the luxury of multiple streams in one school, esp. in rural areas where there barely enough students for a single class. (at least by putting multiple years into one class, you need less students from each age group to fill a class, which makes smaller schools possible)

as a specialized school, not being able to handle very kind of student is fine. as a general school that would be a problem.

Time management and difficulty working on thing you don't like

what bothers me is that montessori is supposed to teach exactly that because you have more freedom to manage you time. so i can't accept that this is montessori's failure point. because it should not be. this is to vital a skill to miss out on. i don't know the answer for this. i am not nearly familiar enough with how he montessori method is supposed to work here.

what i am saying is more like: if you didn't learn math in school you didn't have a good teacher. because no good teacher would fail at teaching you math. that's the very definition of what a good teacher is, and it is the definition of what good montessori is. the no true scotsman fallacy does not apply here.

if the expected outcome is not achieved, they were not doing it right.

In kindergarten (casa), there's a lot of structure with individualised work and a child is unlikely to have gaps in a specific subject. On the other hand, I think that in elementary with the stronger focus on group projects, it's easier for certain subject to fall by the wayside if a student doesn't particularly care for them.

> the no true scotsman fallacy does not apply here.

I don't buy this at all.

but the situation here is more like: no true scotsman doesn't have scottisch ancestors or at least live in scotland.

i don't have scottish ancestors, and i have never even been there, so i can't ever be a true scotsman, as much as i'd like to be one.

it doesn't have to be a 100% success rate but being pretty far behind in math is a serious failure that makes me question the qualification of the teacher.

it can't be a failure of the montessori method because the very design and goal of the method is to not let that happen. or at least the chance is very small. and then it is still a failure of the teacher and not the method.

and since anyone can claim to do montessori without any certification, my bet is on that being the case.

it would be like a car without wheels. no true car is missing wheels. it could not fulfill its purpose.

High intensity interval training (HIIT) is an exercise method that involves very short (think under 5 minutes) intetvals of max effort exercise followed by breaks. This methodology validates very well in scientific literature, both conceptually and in exercise studies that show impressive fitness gains.

It also, by many accounts from researchers and participants, sucks super hard to do correctly. You need to be putting in truly grueling amounts of effort during the intervals to see the advertised benefits. Most people, even when they try to do this, aren't doing it correctly.

I think you could say two things about someone that's not seeing results from HIIT:

1. HIIT is super effective; if you're not getting good results, it's because you're doing it incorrectly. 2. HIIT is not actually a reasonable exercise regimen for most people; this means it's not a great exercise regimen.

Statement 1 is logically true. Statement 2 can be more or less true depending on the theory (walking 20 minutes a day is a lot more reasonable than requiring total exhaustion, whereas a theoretical routine that requires Tasering yourself is less reasonable and makes Statement 2 much more true).

What I've described as my experience in Montessori is definitely Statement 2. I'm sure the method has ways to combat my problems, and if I had gone to a "better" Montessori school it's entirely possible they would have dealt with them. But from what I've seen, these specific problems crop up enough that I think they're a fair criticism.

That being said, I can add some insight. Most state insurance regulators require a company to justify the rate they're charging based on actual claims data (i.e. you wouldn't be allowed to use a competitor's pricing as a justification). Insurance companies would basically never share their claims data with their competitors, so there's functionally a ban on using competitor's data.

Any rate changes have to be justified (based on claims frequency and experience) to the state regulator. I don't think it's a perfect system by any means; insurance commissions aren't completely unbiased, and there's some flexibility in what data the insurer uses. But in my experience it's pretty effective at regulating the data you can and can't use.

The ultimate outcome is that most insurers in these markets run combined loss ratios of greater than 90% (so on an underwriting basis, more than 90% of the premium they earn goes to paying claims and overhead associated with managing those claims).

I think the model of "here's a regulatory body, justify what you're charging based on this set of allowed data" is a decent framework, even if it doesn't work in every market.

If you're curious, the SERFF website [0] has rate filings for a lot of states. So you can see when a rating factor changes and what it changed to. Most of the detailed claims data isn't available for data privacy reasons, but depending on the state you choose, there will be summary figures available.

[0]: https://www.serff.com/serff_filing_access.htm

It's rare to have a CEO that can decide things 100% by themselves and still retain talented employees. It's also super rare to have investors with zero desire to determine a company's direction.

As allergies and (to an extent) COVID have shown, inflammation can also be dangerous. Too much acute inflammation can cause essential body functions to shut down or function incorrectly.

Point being that inflammation is "good" when the alternative is an infection running rampant in your body. But it's "worse" for your body than the baseline, so chronic inflammation is bad for you (and seems to increase cancer risk).

Anti-inflammatories like ibuprofen are good for knocking down inflammation, but they have a suite of side effects unrelated to this function that make them terrible for prolonged use. I don't know for sure, but I'd bet that these side effects are way worse than the benefits of reduced chronic inflammation.

More generally, reducing inflammation across the board leaves you open to infection. It's why we don't prescribe steroids long-term in most patients: the downside of reduced immune response vastly outweighs the benefit for generally healthy patients. It's only considered if the condition (like your body attacking an organ transplant) is more dangerous than the reduced immune response.

Immune system and inflammation is clearly very important process for humans for many things even beyond illnesses.

Like inflammation is body's way to repair and adapt to the environment.

The NHL Player's Association (so the PA in NHLPA) is the organization that collectively bargains on behalf of the players in the NHL. That's why all of the players were in the game, but the NHL logo, team logos, and team names weren't.

For example, CAT bonds are generally tied to the specific natural hazard ("this bond triggers if a hurricane of Category 3 or higher land falls in this segment of Florida") or to industry losses, as estimated by an agreed upon source.

This means that a CAT bond is correlated with, but not directly informed by an insurer's actual loss experience. Traditional reinsurance (so an insurer themselves getting insurance) will usually be tied to specific policies, so their experienced loss is what determines payout.

However, depending on the insurer's policies, traditional reinsurance may be unavailable or much too expensive (either due to the large limit needed, the risk level of the policies, or any number of other reasons). Depending on the trigger, a CAT bond can also pay out faster because you don't have to wait to see the claims from 100k home insurance policies.

From the technical side, most large reinsurers license CAT modeling software from one or both of the same two vendors: Moody's RMS or Verisk. The biggest reinsurers will develop their own models, and there are other modeling vendors that they may license for particular perils (EQEcat for earthquake and KatRisk for flood come to mind), but the big two are pretty widely accepted in reinsurance markets.

That means if your policies are "odd" in some way (uncommon construction type, power facility, etc.), depending on how a reinsurers chooses to model them (or how the model specifically handles them) can have a big impact on your reinsurance pricing. If you know something about your policies that can't be incorporated into a vendor model very well, you may get better pricing on a CAT bond.

These are just some of the considerations! There are so many more things that go into it. But I think it's super interesting to think about.

Source: I work in this side of the industry, specifically in natural catastrophe modeling.

I will clarify that CAT bonds can have industry loss triggers OR actual indemnity triggers. If an indemnity trigger then the insurer has to prove the actual loss. But you’re right on ILWs (Industry Loss Warranty) in that there is additional model/basis risk considerations.

Insurance companies try to minimize this basis risk. Because while sure it’s great to be in the situation where your CAT bond recovers when you didn’t have large losses, it’s NOT good to be in the position where you had big losses and you don’t recover. Certainty of recover can affect things like how much regulatory credit you get for your reinsurance.

So interested how things are today regarding brokers endlessly packaging up risks they sell on, rinse repeat. I'm aware of certain changes that came about to reinsurance brokers in both the Lloyds and London Markets on the back of the asbestos claim era, but not sure of the the CAT model risks/insurance regarding brokers endlessly packaging up to offset risk exposure vs regulations limiting how much they can do that - more so the USA market.

So curious - is there a risk from brokers diluting risks for commission profits in this market or is that saftly covered against and regulated?

A big part of the reason for this is that if payout is tied to actual loss, it starts to look a lot like actual insurance, which is specifically not what you want. Because while anyone* can buy a bond, only insurers or reinsurers can write insurance. This is something that needs to be considered whenever an insurer (or anyone, really) tries to transfer risk to a non-insurer.

The main ideas that I think should be adopted are:

1. A "lesson" doesn't need to take 45 minutes. Often, the next thing a kid will learn isn't some huge jump. It's applying what they already know to an expanded problem.

2. Some kids just don't need as much time with a concept. As long as you're consistently evaluating understanding, it doesn't really matter if everyone gets the same amount of teacher interaction.

3. Grade level should not be a speed limit; it also shouldn't be a minimum speed (at least as currently defined). I don't think it's necesarily a problem for a student to be doing "grade 5" math and "grade 2" reading as a 3rd grader. Growth isn't linear; having a multi-year view of what constitutes "on track" can allow students to stay with their peers while also learning at an appropriate pace for their skill level.

Some of this won't be feasible to implement at the public school level. I'm a realist in the sense that student to teacher ratios limit what's possible. But I think when every education solution has the same "everyone in a class goes the same speed" constraint, you end up with the same sets of problems.