UseofWeapons1

Fascinating. Is this mostly remote software engineers? Hardware folks with manufacturing out there?

The time zone would make it tough for non global teams I imagine. Interested to hear what types of companies make it work.

It would be nice to see an estimate for the order of magnitude of the effect.

As is, I’m skeptical the clocks would be able to measure it. Just a bachelors degree in physics though, so I’m not an expert.

Yes, that was my thought as well. Breakeven might be like 1 (give or take 2x)?

The post is quite clear? They call on the sponsors to stop funding ruby central, and the employment status bit is a clear concern extending from ruby central’s supposed takeover.

Read the post more clearly before accusing someone of LLM usage. And even if it is, they are still valid points to be discussed, as opposed to trying to bury it with an LLM accusation.

I had to look this up. In California in particular, this is true, which surprised me.

Per a random law firm: California’s yellow light law permits drivers to enter an intersection during a yellow light. No violation exists unless any part of the car is over the stopping line when the light turns red. However, the law encourages drivers to slow down before reaching the intersection.

Whereas in, for example, Massachusetts, this would be considered running a red light.

https://www.wccbc.com/red-and-yellow-light-accidents/#:~:tex....

It’s unlikely they are able to gouge McDonald’s and the large companies. Even the article mentioned that the big competition is for those massive contracts. It’s much more likely that McDonald’s and co can shop around, negotiate a great price, and maintain margins.

It’s the mom and pops, the regional suppliers that can’t do anything, and likely pay much higher prices than the megacorps.

Important to note that despite being started by humans, those fires are still made larger and exacerbated by climate change.

Not to say you’re implying against that, just clarifying.

As you consider the decision to let them go, consider the impact on other people in your work place too. Other developers notice someone like that underperforming and getting overpaid, and it can hurt the good climate you aim for. It may feel bad to fire them, but it may be worse to keep them.

This article is just an exercise in back of the envelope math. There’s no coherent point to it. “If we just assume that Pablo Alto was as desirable as Manhattan and could justify building the same infrastructure…”

It’s not. You can’t.

Great summary. Always hard to tell whether proposed experiments are doable within a reasonable timeframe. Sounds like this one is not, but perhaps by defining a new category it may lead to one that is.

Cool project - I’ve had this problem. I’d like the GitHub reader to also lay out how to set up figma. E.g. import figma library. Anything else needed?

This looks pretty compelling! The best of controlling your own data and a global, network-effects-compatible content approach. Seems like a win for users if it gets adopted.

Curious, do you have a source for this?

Are PFAS primarily concentrated in the bloodstream?

Fascinating. This material alone would be revolutionary if legitimate, although I’m sure there’d be further improvements.

Question for any experts - what’s the relative difficulty of keeping something under sustained high pressure in a piece of hardware vs keeping it very cold?

Our ultra cold usages work decently well. Would it be any easier to keep a hardware component under pressure like what this new material requires?

Fascinating. The summary:

“On the one hand, according to the (generalized) standard canonical interpretation, the arrival distribution is considered as a generalized observable, which is described by a positive-operator-valued measure (POVM), satisfying some required symmetries [10, 11, 30, 31]. On the other hand, in the realistic- trajectory-based formulations of quantum theory, such as the Bohmian mechanics [32], Nelson stochastic mechanics [33], and many interacting worlds interpretation [34], the arrival time distribution could be obtained from particles trajectories [7, 18, 35, 36].”

I’d be interested to hear a definition of each of those interpretations.

Fun product, I can see myself using it.

A feature request - I’d like to be able to adjust the time frame. Things like basketball shoes move a lot year to year, and it can be hard to find ones from 18 months ago.

TikTok seems particularly vulnerable to MLM schemes, given its focus on highlighting content beyond a user's social circle. Combined with their younger user base mentioned in the article, it seems clear that TikTok has a lot of good reasons to tackle MLMs.

Claiming that the internet is turning on MLMs seems like hyperbole though - Facebook has been around for a long time and is still a decent platform for MLMs.

The article is off by an order of magnitude in one of the more headline grabbing comparisons. It states 2.5 million goroutines in a gigabyte of RAM, when it should be 250k at 4KB per stack. Still impressive on its difference, but less so.

The easist method is by trend in employee count. If headcount is rising, that's a good indicator, if it's falling, that's generally bad. Stable can be perfectly fine, or bad, depending on the company. You may have concerns about the magnitude of growth, or claim lay-offs were justified or turnover is natural, but the trend generally holds.

You should also pay attention to other employees; ask yourself why folks who leave are leaving. This seems easy, but I know one start-up well where a small trickle of occasional high-level departures turned into an eventual flood and bankruptcy.

Beyond that, it's the usual. Anything you can tell about sales growth, competitive intensity, leadership, etc. are all helpful and good data points.

Per a Forbes article on the subject [0]

"Check Point estimated the firm was making millions from the ad clicks, in the region of $300,000 per month."

I imagine your price per click is over-estimated by a couple orders of magnitude, but that's just a guess.

[0] https://www.forbes.com/sites/thomasbrewster/2017/05/26/googl...

I respect TechCrunch's decision to not publish the plaintiff's name in the primary portion of their article. It's easy to look up for those who have a reason to search for it, but it's not necessary to the discussion, and could potentially alleviate some of the social backlash (or at least issues) associated with going to court. Employees with legitimate legal gripes against their employers don't need to face additional barriers (such as social stigma) to legal action.

At the pre-MBA level, interviews often just test for the right mindset and approach to problem-solving. Very little hard skills are expected prior, unless you're applying somewhere with strong expertise (life sciences comes to mind).

Post-MBA, they'll still hire from most industries and backgrounds, but take into account prior experience. The interviews will have case questions, where you'll walk through a small case with an interviewer (e.g. a multi-step case on a company, looking at their profit levels, expansion strategy, and similar). There really aren't that many hard skills required. However, the difficulty is in getting an interview. They generally recruit primarily from top 10 business schools, although the largest firms likely cast a wider net. I'm not entirely clear on the post-MBA recruitment process and what exactly they look for. I'd imagine coding skills would not be a negative, provided you could convince interviewers that you were actually interested in consulting, but I'm a little doubtful they would be seen as a strong positive either.

There's two major entry points to management consulting, straight out of college and post-MBA. I did an internship after my junior year, and took the full-time offer. Most firms also hire out of business school. There's certainly exceptions to this rule, especially when firms are seeking industry expertise, but those make up the majority of folks.

My level of enjoyment varies based on the cases I'm on. It's generally interesting, it's certainly fast-paced, and I very rarely count down the hours before I can leave work (there's no face-time policies). But after almost four years here, it can definitely get monotonous. Still, I've learned more than I would at almost any other job, and it's taught me a great work ethic, so I'm grateful for that.

Relatively normal, yes. I have friends at a number of other firms, and most have had similar work-life balances. It has a huge variance to it though; in January I worked until 6 PM most weeks, but for the past month or so it's been closer to 10 or 11 PM on average.

With seniority in the industry comes flexibility, so many of the VPs are able to take 6-9 PM off to be with their family, but even they'll come back online after that for a couple of hours.

For a different take: Management Consultant

Workday:

- 8 AM - Wake up, shower, shave, etc.

- 8:30-9 AM - Ride the subway in to the office

- 9-12 PM - Calls, meetings, data analysis, output creation (primarily in word, powerpoint, and excel)

- 12-12:30 PM - Lunch (but this can shift around widely based on meetings)

- 12:30-7 PM - Calls, meetings, data analysis, output creation (primarily in word, powerpoint, and excel), usually with a half hour break at some point

- 7 PM - dinner is delivered to the office

- 7-~9PM - finish up work for the day

- 9-9:30 - head home

- 9:30-12PM - unwind (internet, side projects, video games, etc.)

It's hard to define an average day, as my end time can be 6 PM, 9 PM, or 1 AM, but 9 PM is probably close to average. The work that I do on a given day can also vary widely. I've got a light day today, hence the comment.