webel0

This was my exact initial reaction.

However, suppose that Bill Clinton, George Bush, or Barack Obama had declined to attend the inauguration of there predecessors. That would surely trigger a crisis worthy of de-platforming. We’ve become somewhat numb to this sort of thing.

I guess my second draft would have said, “We’ve allowed DJT a platform because he is the President of the United States. In light of all that he has said on Twitter over the last 10+ years, though, he is guilty of inciting hate and violence among his followers. [Cite myriad tweets and cases.] We were going to wait until he left office to suspend his account. In light of his most recent tweets indicating that he would not attend the inauguration, we think it prudent to move up this timeline...”

My issue with the “obscure” comment is what it suggests to the non-dev reader. It is easy to think that “Obscure” companies can be pushed around more easily by state actors. That their product has never been critically evaluated for security issues.

There may well have been an issue emanating from jetbrains. I don’t know.

But when you combine these insinuations with the fact that the company is run by Russian nationals (quite different from the Russian government!) you simply get stronger insinuations, not facts.

I think you’re mixing up a few different items.

The streetcar is, indeed, a disaster. I think that is largely because they built it essentially as an amusement park ride for the weekends rather than a serious commute option. A subway that had the ability to actually move people across town (like the planned 16 mile loop) would have been great. The subway suffered not so much from local incompetence as inflation.

The Brent-Spence bridge does need repair but that’s not a city issue. It’s a mix of state and federal. It doesn’t help that Ohio thinks that Kentucky should pay for it and vice versa.

I believe the paper discussed is here [0]. I've skimmed it and am somewhat underwhelmed by both the methods and theory:

* All of their regressions are in levels.

    * Look at Table 1, Column 1. 

        * Robotics investment is positively correlated with overall employment. 

        * What this tells me is that, "Large companies, by dint of their being large, make large investments. Some of those investments are in robotics. Likewise for small companies." 

        * To me, it has nothing to do with the claim "More robots => more employment."

    * Running regressions in first differences would be better (but not enough). 

     * Then you could begin to work towards an interpretation like, "companies that _increased_ their investment in robotics in year X tended to increase/decrease employment/management/turnover by X." You can account for lags and the like via your specification.

     * Fixed effects _are not_ equivelant to first differences in this setup!

* Separate out the long-, medium- and short-term consequences: * Investment in new technology may require hiring new "talent" that is knowledgeable of the tech.

* In cases where there is a tech shock and firms are all buying the same machine, demand for a certain skillset will grow quickly. So you'd likely see:

  * An uptick in turnover among affected workers

  * A move to a "flatter" organizational structure (various reasons). So maybe fewer people who are managers per se.

  * Possibly short-term productvity decreases arising from implementation issues. (e.g. have to hire people to check the work of machine in staging manually while still running previous process.)

 * Over time, though:

  * Implementation issues/bugs are smoothed out

  * Rare skills are commidified. The need to hire "superstars" ends.

* It is important to ask, "what might have caused investment by a given firm over a given time frame?"

* Common industry technological shocks might spur investment.

* (And the simplest way to account for technological shocks in this sort of regression you'd want `[industry] x [year]` fixed effects.)

* "We went on a manager hiring spree in year 1. Those managers, in turn, bought a lot of robots in year 2. In year 2 we hired fewer managers because we'd just hired a bunch in year 1."

* Reverse causation issues are pervasive.

* Finally, I think it is important to notice their notion of "robot adoption":

* They are talking about physical hardware _only_.

* Their measure of investment is coming only from import data. The set of firms that are going to go through the rigammarole of importing physical hardware is probably raher special: Probably:

  * Larger

  * Have a high expected ROI from investment

At the very least, this paper needs first-difference regressions and a good instrument that can help to disentangle what might be going on. For the instrument, it might make sense to look into changes in tariff duties over time [1].

---

[0] https://content.tcmediasaffaires.com/LAF/lacom2019/robots.pd...

[1] https://cbsa-asfc.gc.ca/trade-commerce/tariff-tarif/2020/htm...

It is interesting that the only way to draw attention to this issue was via Twitter DM. For many big companies this seems to be the one place where you can hope to get a response.

For example, a year ago I was in a pinch and ended up booking a flight on Delta via Twitter DM.

The problem with this is that the escalation chain and documentation to go along with it is unclear. The author could only hope that he was being connected with the right people. Likewise, I was just crossing my fingers that there was, indeed, a ticket waiting for me.

The tone of this article (plus my experience on indeed) suggests that a lot of these roles are for larger companies, not for little companies who are suddenly online and need a FT/PT web dev.

I wouldn’t be surprised if there was a shift in job listing behavior that caused a sudden influx of php job listings on indeed. So it isn’t as if the jobs didn’t exist before, they just weren’t posted on Indeed.

The salaries discussed (77k) doesn’t suggest that a surge in demand is pushing up pay.

Trump had a hilariously bad password.

But it appears that twitter has even worse password protection policies.

The account was “hacked” by manually entering several different password ideas into Twitter’s login. The guy got it on the fifth try. Why not lock it down sooner?

Wow, I wasn’t aware of the Skype IP battle [1]. In that case EBay licensed the underlying IP from the founders.

It is especially interesting in the context of quibi because it appears that most of their content deals allowed the content creators to own the underlying content but require a 2 year exclusive license to the service.

[1] https://www.theregister.com/2009/07/31/skype_joltid/

This is my greatest fear when it comes to terraform:

> terraform destroy

(And either a confirmation or a flag) and everything is deleted.

I know you can add some locks but still :/

This sounds rather similar to a lot of the work being done in macro/public finance right now.

If you look at a model from someone like Mendoza you’ll see that they have several parts of the economy characterized as recursive optimization problems + various constraints.

As others have pointed out, however, it is quite difficult to interpret these model results. The best you can do oftentimes is argue for why your setup makes sense then provide some intuition for what is going on. The problem is that slightly tweaked models are capable of delivering qualitatively divergent results.

I do think that reinforcement learning brings to the table some novel techniques for solving models with larger state spaces, though.

In this case, idleness appears alongside the requirement to maintain a plantation. So I think it more has to do with a requirement to be able to provide for oneself (particularly when it came to sustenance) rather than a prohibition on any particular set of activities.

I don’t have a reference handy but during this time and several centuries thereafter there were (enforced) laws that sought to prohibit what we’d now call tramps throughout the English countryside. It appears that that is one part of home that they’re trying to leave behind.

I also think that most of these “lots” are just for one item.

However, I think that the bids are probably mostly earnest.

As streetware a lot of this could probably be considered collector’s items among the hype beast crowd. The prices seem to be in a range similar to supreme and similar.

Good on you guys for listening and putting out what seems to be some pretty awesome auth!

Row level security is far more than I was expecting but exactly the sort of thing that is needed in a lot of my applications.

I look forward to diving into this more.

Interesting...my first few small entries were sort of neat.

Then I tried creating a longer story including quotations and references to “you.” The reply seemed to be hard-coded to deal with hard case. Something like, “You think I’ll tell a story.”

Could someone link to original article? Didn’t see in post. Notice that they don’t cite what the authors’ computed R^2 was but conjectured it was low (and I agree that it is likely low). Thus, doesn’t appear to be a case of blind p-hacking off the bat.

Could just be really bad. However could be that:

- The conclusion of the paper was that no relationship exists.

- Later specifications include covariates. For example, including travel flows here could help to disentangle cultural mores regarding drinking and probability that ANY virus was transmitted to place.

- some sort of weighting was done. Although in that case I would expect to see a steeper slope to account for New York. Usual practice here would be to display the univariate relationship with circles that are sized to match weights.

- Graphs like this can play tricks on your eyes. There might be a lot of dots clustered along the fit line that are overlapping etc.

Can someone explain how RStudio is a competitor to datacamp?

Have briefly used RStudio IDE in past but don’t follow them or datacamp very closely.

I think that this is a nice gesture. For those who are puzzled, I think that they’re just trying to help us to keep our work and programming in perspective by providing a reminder where we might not expect it. If you really need to read the docs you can do it on github. Think of it as a PSA, maybe.

Check out hypothesis [0]. No fun styling but the same functionality.

[0] https://github.com/hypothesis

This reminds me of how Jonathan Franzen writes on a giant old laptop with no internet. (Forgot where I read this.) Different dimension of keeping it simple.

Interesting to contrast with the likes of grammarly or google suggestions. I can’t stand having that stuff in my ear while writing. However, I did have a friend who was a non-native English speaker and he liked it because he felt less self-conscious about screwing up grammar elements when writing.

Ah, okay, whenever I think webrtc I assume p2p with no server but I am now actually reading into what SFU is, etc. Makes sense. Thanks for pointer to these resources.

Can someone explain how mediasoup differs from the RTCPeerConnection object (and related events) discussed in this Mozilla webrtc tutorial [0]? Given that it uses c++ I figure that mediasoup is more than just a wrapper around this? Any usability or reliability benefits of either?

[0] https://developer.mozilla.org/en-US/docs/Web/API/WebRTC_API/...

Wondering how much of this is convenience bias? If you want to make a podcast about great developers you’d probably start with the people you know, which is going to tend to be people with a substantial public presence.

Maybe you could say a bit more about why you’re asking. In some cases others would be right to suggest that you find material relevant to business for yourself.

The one case that I can think of off the top of my head that might apply to this situation is if there are disagreements re:product refinement/feature set/bug prevalence. (Basically, “why doesn’t this work as seamlessly as X?”) In that case you might do well to find the MVPs (and later iterations) of famous startups.

Do you think this could be sleep related? I still am guilty of sleeping a lot on the weekends (so Mondays feel great!) then running myself into the end of the ground by the end of week. Do not recommend for anyone.

If someone starts running this model couldn’t you just run the model yourself to predict the order?

I’m sure that there is market microstructure stuff/front running practicalities that would make this harder than it sounds but still you wouldn’t completely be in the dark.

Yes, it can help you to issue shares to a certain extent. (I am currently waiting for my signed forms to be processed so have only read, not done that part.) You May be interested in this guide [0]. It discusses some of the considerations that go into the default vesting plan.

[0] https://stripe.com/files/atlas/orrick-legal-guide.pdf

We got $100k but boy oh boy once you’re on it it’s hard to get off. Now we’re close to 50-50 gcloud/aws

> ate jelly beans off someone's desk.

Bush might have been President but this was Reagan-era stuff.

Good article but it seems to be copied near-verbatim from [1]. There is a tiny “H/T” at the bottom of the article.

Suggest that the link point to the original source.

[1] https://www.authorea.com/users/8850/articles/117724-nope-8-r...

Coming soon to a whiteboard near you!