cle

Web Environment Integrity. Eventually your hardware will rat you out via attestation.

I had no trouble understanding, but perhaps it could be made slightly less ambiguous, like:

> But that night, there was only one helicopter, and its pilot and co-pilot worked together to navigate...

Is that really the right statistic? Seems like the relevant one would be the number of maintainers whose maintenance work is company-funded. (Ex, I'd imagine it would be quite bad if most contributions were from company-funded developers but had to be upstreamed by non-company-funded volunteers.)

Ironically part of the long-term problem was El Salvador's dollarization, also preventing them from printing in a crisis (that crisis being the COVID pandemic).

This seems like an inevitable outcome of indefinite growth in executive power.

> If there are no consequences, the law is immaterial.

That is exactly what I mean by "growth in executive power".

A contributor in this space that I always thought was under-appreciated is Amazon SWF + Flow Framework. It's an older technology and SWF itself is deprecated, but it is a weird middle ground here in that it makes language-level modifications to inject workflow state persistence and coordination into Java code (via AspectJ). The original concept was to build a "distributed CPU" (ex see https://docs.aws.amazon.com/amazonswf/latest/awsflowguide/aw...).

SWF was the predecessor for AWS Step Functions. IIUC the lesson learned from SWF was that it was just too flexible, and imposing a more limiting set of constraints was both easier for the programmer to use & reason about, and made for simpler and faster execution.

Maybe. It needs to be the right data, and interpreted correctly. More of the wrong data isn't particularly helpful.

I think what I'm arguing is that just having data isn't good enough, and it's dangerous to accept data at face value. It needs to be the right data, and interpreted correctly.

> Data is the ultimate Fact Check.

This is wrong IMO. Data can be missing, incomplete, biased, skewed, and even just plain wrong. Cherry-picked data can be worse than no data.

The ultimate fact check is a scientific process of collecting data, modeling it, scrutinizing it and its methodology and the entities involved, contextualizing it, cross-checking, replicating, etc.

What media likes to call "fact checking" to me feels more motivated by punchy headlines and chyrons.

It's not in any sort of format to do this kind of analysis unfortunately. I'm also missing some data b/c I throw away certain kinds of datasets that are not useful for me. I can probably write some scripts to diff my archives with the current data.gov and see what's missing, but it won't be "complete". But it might still be useful...

I did however just write a Python script to pull data.gov from archive.org and check the dataset count on the front page for all of 2024, here are the results:

https://postimg.cc/1V0WYtRt

As you can see, there were multiple drops on the order of ~10,000 during 2024. So it's not that unusual. There could be something bad going on right now, but just from the numbers I can't conclude that yet.

(Specifically it takes the first snapshot of every Wednesday of 2024).

If I get around to re-formatting my archives this week, I'll follow up on HN :).

My company is my company so it kinda does need me :).

I’ve been archiving data.gov for over a year now and it’s not unusual to see large fluctuations on the order of hundreds or thousands of datasets. I’ve never bothered trying to figure out what exactly is changing, maybe I should build a tool for that…

Kinda? We all have bills to pay sure, but I also don’t want to spend my time working on something that doesn’t really need me.

I’m quite curious what you consider innovation (and not)?

Differences in how people want to consume the article, and what information they’re looking for. Some want snippets, some want summaries, some want long form.

We have information compression machines now. Might as well raw dump the information and let the machine package it up in the format we prefer for consumption, instead of pre-packaging it. (Yeah, this is effectively what authors are doing…currently they can still do novel things that the compression machines can’t, but how long will that last?)

It is a statistical machine but it is not over bare words/tokens, it effectively operates over a “concept space” that it learns during training.

(Granted the definition of “statistical machine” is quite vague and different folks might define that differently…)

Why are they poor choices? What tradeoffs are they making?

I can't really evaluate/judge them without understanding that first.

Nobody cared that gold conducted electricity until very recently in human history.

I'd add the additional nuance that cognitive load is highly dependent on the brain of the subject. One person's cognitive load is another person's effortless routine--it largely depends on how often the person works with those concepts and how quickly they can switch into the "mode". Where one person sees a wall of indecipherable matrix variables in Python, another person sees that it's obviously just a Cholesky decomposition as part of a Monte Carlo simulation.

So where to push the complexity should be dependent on who will be interacting with it and what they consider "cognitive load".

As an additional example:

> Rendering your web application entirely on the frontend in React, or entirely on the backend with templates, where all the logic lives in one place, is much easier than doing server-sided rendering then hydrating on the frontend.

For an expert front-end React developer, rendering entirely in the backend with Jinja templates would be higher cognitive load than the other options, even if it is technically simpler.

It's nothing to do with verbosity, which is why I didn't mention it.

> instead of using them implicitly from the context, without documentation and static typing

This is exactly what context is trying to avoid, and makes a tradeoff to that end. There's often intermediate business logic that shouldn't need to know anything about logging or metrics collection or the authn session. So we stuff things into an opaque object, whether it's a map, a dict, a magic DI container, "thread local storage", or whatever. It's a technique as old as programming.

There's nothing preventing you from providing well-typed and documented accessors for the things you put into a context. The context docs themselves recommend it and provide examples.

If you disagree that this is even a tradeoff worth making, then there's not really a discussion to be had about how to make it.

This is pretty normal. Even George Washington declined to enforce the law at times. A widespread recent example of "discretion" is the lack of enforcement of federal drug laws WRT marijuana. There are 39 states flaunting federal law, and presidents haven't bothered enforcing it.

Making sure employees feel valued does have a cost though. Managers spend a lot of time on this, and they have a high salary. Career growth, 1:1's, conflict resolution, comp adjustments, etc.

When managers' own heads are also on the chopping block in a tough job market, they're going to prioritize looking out for their own ass. If "leadership" is saying "boil the frogs or you're gone", they're probably going to do it. Even if they don't want to.

The companies that take such a zero-sum outlook will be devoured in the long run.

I think that companies that view AI as empowering workers to produce more, will blow past the ones dominated by bean counters and MBAs looking to optimize their quarterly earnings reports.

No that's not the point.

I don't know what you want. Most of the article is spent elaborating on what that means and providing examples of it.

> Instead of going out into the world and quietly helping members of marginalized groups, the politically correct focused on getting people in trouble for using the wrong words to talk about them.

> The problem with political correctness was not that it focused on marginalized groups, but the shallow, aggressive way in which it did so.

The whole article is an opinion piece that is judging a group of people. I don't think most people would agree with your definition.

And besides, the definition of "woke" is a secondary issue anyway, the article's purpose isn't to propose a definition of woke, it's to judge and criticize people who behave a certain way, and he's done an adequate job IMO of describing the behaviors he's criticizing.

> Instead of going out into the world and quietly helping members of marginalized groups, the politically correct focused on getting people in trouble for using the wrong words to talk about them.

I also think there's a pretty big difference between keyboard jockeying / speech policing, and putting yourself in physical danger by physically confronting racists who'd lynch you if there weren't cameras around.

Well b/c of the "focus on social justice" clause. I'd definitely agree though that both parties are way too "aggressively performative".

Helpfully he spends most of the article elaborating on what he means by "aggressively performative".

TFA spends the first 7-8 paragraphs defining "woke", even a dedicated callout to a concise definition:

  > An aggressively performative focus on social justice.