On the face of it, even relatively "point-target" goals of this kind could take many decades if at all; GaN for blue diodes come in mind as an example of a field that was stuck for a generation -- until it wasn't.

This seems to be supported by this quote:

> Putting arbitrary deadlines on state, local, and Tribal governments to start and finish complicated permit reviews...

I'm not an American but I am alarmed at the recent tendency for bad-faith rule making. However - the above sounds in reasonably good faith - is that indeed the case or am I missing some angle?

A lot of folks I know regard mechanical watches as a type of jewelry, a high value item that's not intended for the everyday.

I concur that that popularity of mechanical watches is on the rise, but having a cool mechanical piece on in the evening does not preclude having a digital watch at all other times.

I wish it was more commonly accepted that choosing not to act is effectively a stand against one's own value system in favor of the value systems of those who do act.

Yeah, some of its design decisions required immense cost and time to overcome to make for viable production solutions. However as it turns out, however suboptimal it is a language, this is quite made up by the presence of a huge workforce that's decently qualified to wield it.

Alas, YAML is just about everywhere, so the chances for a replacement that'll be both better behaved and as ubiquitous are unfortunately slim.

From people at Facebook circa 2018, I know that end user privacy was addressed at multiple checkpoints -- onboarding, the UI of all systems that could theoretically access PII, war stories about senior people being fired due to them marginally misunderstanding the policy, etc.

Note that these friends did not belong to WhatsApp, which was at that time a rather separate suborg.

I can see how a tech-centric person would see the described business as viable, but putting on my founder hat, I realize that it faces enormous risks:

- Any competitor could build the same product with less janky UX; users tend to hate even unavoidable usability issues.

- There's no compliance strategy even remotely possible in the described scenario.

- If a capital investment becomes necessary for business scaling, I cannot imagine this organization passing even a perfunctory level of due diligence.

Would be happy to hear out if that makes sense.

1. A senior Google leader telling the shareholders "we've asked 1% of our engineers, that's 270 people, costing $80M/year, to work on services that produce no revenue whatsoever." I don't think it would pass that well.

2. A Google middle manager trying to figure out if an engineer working exclusively on non-revenue projects is actually being useful or otherwise; this is made more complex by about 30% of the workforce trying to go for the rest and vest option provided by these projects.

Furthermore, I concur with the piece that a proper investment in the said fields would further the common good.

However, take objection with equating investment with investment in the way specifically done up until now.

The article opens with longevity; the Alzheimer amyloid hypothesis, which served as a bandwagon for low impact, perhaps even bad faith research, whole syphoning out billions of public spending and blocking out alternate research pathways.

Many of the other domains mentioned exhibit similar dynamics. To my ears, it makes little sense to champion further spending without exploring the reform that needs to be carried out to align that spending with the various notions of public good.

To reiterate, I abhor the populist choice of dismantling everything and putting cronies to feed off the rest. I'd be looking forward for a way forward to make change, because some change is due.

Decent threading is awesome news, but it only affects a small minority of use cases. Threads are only strictly necessary when it's prohibitive to message pass. The Python ecosystem these days includes a playbook solution for literally any such case. Considering the multiple major pitfalls of threads (i.e., locking), they are likely to become a thing useful only in specific libraries/domains and not as a general.

Additionally, with all my love to vanilla Python, anyone who needs to squeeze the juice out of their CPU (which is actually memory bandwidth) has a plenty of other tools -- off the shelf libraries written in native code. (Honorable mention to Pypy, numba and such).

Finally, the one dramatic performance innovation in Python has been async programming - I warmly encourage everyone not familiar with it to consider taking a look.

A lot of your reaction is towards the notion of dramatic impact. Note that I tend to distinguish between an "intellectually capable" researcher and a "right stuff" researcher, which involves the ability to manage risks in self-led multi-year high-risk high-impact programs.

My icons are Katalin Karikó and James P. Allison, who are not necessarily the brightest people of their fields, and subpar at politics, but are actually very good at making impact (duh).

Circling back to the original thesis, setting up a Bell Labs necessitates spotting out the Karikós and Allisons out of a very large flock of (at best) diligent followers of current academic fashions or (worse) popularity contest winners, and I reckon that's not practically possible today.

That's a valid critique. What I had in mind is the overwhelming prevalence of researchers who in my opinion have never even carried out a high risk high reward project, regardless of impact (not every high risk high reward project is going to make impact, and that's fine).

As example of what I have in mind by high risk high reward, I'd like to point at the work of Katalin Karikó and James P. Allison, both highly untypical science practitioners who have been rejected and indeed denigrated during much of their careers.

There are two root causes that for the most part, grad student do not develop into a Karikó or an Allison:

(a) Most grad students are never put in a position where choosing a high risk high reward project is legitimate.

(b) Many grad student in the first place do not have the character such projects (tolerance to sparse rewards and inclination to long term project risk management)

Regardless of the root cause, I observe that a grad student who was never trained to properly manage a big bet project is not likely to succeed doing that after graduating.

To be clear, I do not blame anyone in that situation. The graduate school system selects candidates for being good underlings to the thesis advisor, and down the road for aligning into field/department politics. There's little wonder to me how this system perpetuates a meek research mentality.

I have a graduate degree with a thesis in a STEM field from a university that's occasionally ranked worldwide top-100. I appreciate a lot of my former classmates on a personal level, but do think that a lot of them did not make it as high impact researchers.

Would that clarification qualify my opinion as held in good faith?

Today we have a huge oversupply of scientists, however there's too many of them to allow judging for potential, and many are not actually capable of dramatic impact.

More generally, a standard critique for "reproducing a golden age" narratives are that the golden age existed within a vastly different ecosystem and indeed - stopped working due to systemic reasons, many of which still apply.

In particular, just blaming 'MBA Management' does little to explain why MBAs appeared in the first place, why they were a preferable alternative to other types of large scale management, and indeed how to avoid relapsing to it over a few years and personnel shifts.

Overall I am afraid this post, while evocative , did not convince me what makes 1517 specifically so different.

Also, the banality of how the system treats sailor lives as expendable is almost incomprehensible from a 21st century perspective.

Did you consider that the judgement of precariousness of the people's situation is in your value system, and does not necessarily transfer to their value system? Especially this could be due to you having access to more information than them

Hence I expect the host LTV to be a couple of orders of magnitude greater to that of guests.