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This isn’t true; LiDAR points provide an intensity value that provides information about surface material and ambient environment. Further, this information is influenced by angle and distance.

Lane lines and road signs in particular typically use reflective paints that are very easy to detect in LiDAR, but beyond that, you can approximate material composition of a LiDAR scene pretty easily.

Another big point you’re missing is that LiDAR can provide control points to photometric sensor fusion systems. While there are also purely photo based control point matching systems, they’re much more complex and require nontrivial offline preprocessing.

Many people also don’t do well in high stakes problem solving situations even when not being watched.

I’m not suggesting OP is dumb, but if someone is setting hiring criteria and thinks they need X skillset judged by Y, I think there’s a good chance they’re directionally correct.

I get it, I’ve bombed interviews I was excited about and rationalized it anywhere and everywhere. Once I started hiring folks, my opinions evolved significantly.

How else do you hire someone out of a pool of people that are all knowledgeable and likable? A bad hire, even if they’re super smart and just the wrong fit, is worse than not hiring anyone at all.

If you climb the management ladder, you’ll likely be graded on your org’s hiring outcomes. If 10 people all seemed qualified, I’m going to burn down the risk as much as possible. If I’m wrong 1 time for this, but it not obviously wrong 9 others, I’ll call it a win.

For context: this is coming from tiny startups to billion dollar companies and different things in between.

Who are you trying to convince?

I genuinely don’t believe you’re coming at this from a business stakeholder POV, which is fair for HN. But if you have to advocate for a devops org outside of some massive global scale or as a small % of revenue, you’re doing something wrong.

Unfortunately a proven playbook for struggling devops teams is to just fire all the devops and infra folks, which seems to help with platform stability, recruiting, and velocity year over year.

I think these arguments often miss the “for who” both in the producer and consumer sense.

If you have a team or teams of engineers, having one or two people deal with all the dev-ops stuff makes a lot of problems go away.

But if you have a large C++ project for example, you probably need more than a couple people focusing on build and target dev-ops work, or at least a lot more of their time.

It’s a lot easier to get a frontend person to help out with the backend dev-ops than it is to hire a new C++ guru and wait a bunch of time to catch up on the nuances of your build systems/org/whatever.

Anecdotally, I see the people who balk at Node are usually enterprise Java devs, backend Python devs, or junior Go/Rust enthusiasts.

At the end of the day, all these languages can interoperate with all the others in a bunch of different ways, and an organization’s ability to engineer and maintain systems is mostly orthogonal to its choices of “driver” technologies.

I think this has been going on for at least 2000 years…

It doesn’t matter if it’s crypto or gold, there will always be people manipulating financial systems, but that doesn’t mean any system is inherently good or bad.

https://en.m.wikipedia.org/wiki/Financial_crisis_of_33

https://en.m.wikipedia.org/wiki/Financial_crisis_of_2007%E2%...

https://en.m.wikipedia.org/wiki/WeWork

That’s a rather myopic view.

You could look at L2s as a sort of credit card system, and from a systems and technology POV there’s nothing inherently “scammy” about it. For web3 applications of any meaningful large scale, L2 solutions are necessary.

For better or worse, the L2 developer platforms that I assume you’re referring to are essentially low-code solutions to abstract away the actual systems software engineering aspect of web3 development. Are the low-code SaaS companies overvalued or “scammy”? I’m not suggesting they are or are not.

Well-staffed tech companies building web3 applications often build their own implicit L2 solutions because it’s just how you connect things in a distributed system with modern L1 blockchain constraints.

If it was a person, you shouldn’t have responded on a Sunday before a holiday. You’re at the bottom of their inbox now. Also, try to hold the questions for a live chat if you’re interested in the company.

It sounds like you really want to learn about roles at Chewy, why not just send another email or directly contact a recruiter on LinkedIn?

Interesting, looks like it’s using a combination of hardware, vehicle checks, LoRa (Helium?), ML, and good old fashioned Humans for verification.

If they can scale it globally and at high frequency for imagery, that’s a very novel justification of crypto IMO. Looks like the Costco version of https://www.mapillary.com/

WDYT about initializing a limit and having only one return? For/else in some languages is kind of interesting, too.

I’m indifferent in practice (whatever’s readable to others is usually best), but I like the limit approach in theory.

You’re a curious person and see that the back door to a closed restaurant was left unlocked. You should let them know, but make sure you find out how big of a screw up the closing manager caused so s/he can be dealt with or the process fixed.

You open the door a little and peak inside and see the office door is open. “This can’t be,” you think as you walk into it.

You bet there’s a safe left unlocked and customer reservation left unprotected on the computer, “how irresponsible can these people be…”

If their security is this bad, you wonder what their food safety processes are.

It’s a slippery slope, and maybe well-intentioned, but that doesn’t change the fact that you’re not allowed to wander into this restaurant’s back door or be there when it’s closed, and now that you have, how do you prove you didn’t do anything malicious if the only evidence there is is of you in the restaurant when you’re not supposed to be?

Maybe you can make an appealing public good argument against criminal accusations based on your stellar clean record, but how do you protect yourself from civil suits, which they have every right to spin up if they have damages and can link you to them?

Even in SF/Bay Area, 400 isn’t as common as level.fyi would have you believe. You can’t (easily) trade equity appreciation or pre-liquid options for cash.

Yes, in SF there are companies that give a lot of liquid RSUs, but most engineers don’t work at those companies, even if a lot of engineers do.

Also, if you’ve been swinging and missing in a silo for 20 years without full time employment, you’re most likely not going to easily find a job that pays you 400+ without working full time at large companies first.

I’ve been able to download the app over plane WiFi for free. It used to be a little-known hack for free internet once upon a time.

The “right way” also needs to be maintained and refactored over time. That gets increasingly expensive the more in-house or low-level things are.

Can you be a good musician if you always make mistakes while performing?

Maybe you’re a better composer or producer then, but it’s on whoever leads the group of musicians to organize that.

Jerks who randomly push buggy code straight to master might be the reason you have a job. Most of them probably aren’t, but some of them are the reason a bunch of other people have a job running around fixing stuff and being mad about it.

It’s really hard to see yourself as a regulating component in some messy system, but nothing is better for velocity than pissed of engineers heroically fixing all the stuff they hate from some other engineer that’s pumping out mostly working high impact stuff left and right.

Why? Assuming we’re talking about normal employee options, if you’re early and get a big % that gets diluted, someone with a smaller % later can end up with more shares.

But your username is not random.

Programming language/etc. is typically not a huge factor for high paying jobs. If I’m giving you a lot of money, you’ll learn whatever you need to ASAP.

News to me. Company value, dilution, risk, revenue, profit, outlook, etc. have significant weight.

20% of the job that applies 80% of the time.

so… your brother in law used opiates for 14 years until he overdosed on heroin, and you’re blaming weed? I’d say a family that didn’t help him successfully overcome his 14 year addiction is a more plausibly causal relationship, which is also absurd to suggest.

Not to be too snarky, but perhaps the onus is on you to do some homework if you want to understand a niche article for which you lack context?

Laying out matrices like that is pretty standard, especially for a post about vectorization.

You don’t have to always use the DOM. You can render in another thread, or even run compute in another thread and use the animation frame system to handle updates.

Having said that, maybe a little less than 10 years ago, we achieved the desired performance with touch-screen dragging of DOM elements. I don’t remember specifics, but we didn’t use any frameworks.

A company with a few people vs. a company with a lot of people are two different beasts. If things are not rigidly defined, it can be a lot more effective for people to be around each other, especially in the phase of spontaneous brainstorming or kitchen conversation or happy hour drinks. Most new companies aren’t hiring super experienced engineers to grind out a high risk venture, and maybe those are the people least affected by remote. Much harder to train or onboard someone who’s remote if you’re starting from 0.

Maturity is correlated with age, but age isn’t as strongly correlated with talent. Just because a team is just as capable working remotely doesn’t mean they’re as generally capable as a different team that’s more effective in person.

How do you reach the same level of effectiveness teaching or debugging math problems on a whiteboard without investing a lot of time asynchronously?

Why would it be worse? Why would you write p instead of phi?

I would, however, point out that to call this function, you need to separately compute lengths of sides. Where do those come from? How are coordinates stored? How are you wiring all this up? What happens when you change the data to support more dimensions, or to use memory pools, or to add new shapes?

To be clear, a lot of math needs a ton of complex code, and you also often have algorithms optimized for performance, approximation, numerical stability, etc. You can encode your understanding of what’s going on in the naming and break it into chunks so it’s readable, but that’s not necessarily a good thing.

Write some code to compute the intersecting earth-surface geometry of the projected frustum far planes from two satellites’ cameras at some point in time. Who’s using this code, is it a library? How do you abstract it? Who are the consumers of the code, will they ever change it or only use a part of it and want to refactor? Is it going to be a lot of work to refactor and are they just going to inject what they need into an evolving system of glue code? If I have to call it n times, how can I pass in and reuse memory to avoid memory penalties? What happens to names when we have to reuse symbols?

Edit: probably not obvious, but you can probably elegantly describe what you’d do with ideal inputs, but getting those inputs is the particularly hard part.

Effort to refactor is something to consider, and verbosity makes this harder as you get lower level.

Another thing to consider is the very verbose names can be something that people actively avoid for clean code, and you could end up with spaghetti code to make it both readable and verbose (imagine someone doing this for years and then handing the code off to someone when they leave because they were so pigeonholed in that system that no one else could easily collaborate).

Downstream, you can end up with tech debt instead of optimally refactored code as people struggle to do something of a smaller scope. And if every tiny thing is unit tested, it gets even harder to change without expanding the scope of work.

Math code is an extreme example of where verbosity can quickly become detrimental.

You invented huffing bleach?

The linked tweet isn’t about preventing contracting the virus.

When employees have high variance, or some other issue, I expect a good manager to debug it. It’s not that hard to figure out your 35% impact is because of your suboptimal juggling of two jobs. We just let someone go for this (proved of course).

I think you’re misunderstanding the transient nature.

There are always people coming in and out, and while that growth rate of new people has slowed down bit (it’s still positive) and the rate of people leaving temporarily went up, it will pick back up as companies return to the office.

I don’t think it’s for the reasons you suggest. A lot of the influx is young people, and there isn’t a compelling reason to move somewhere if you’re not going to make friends or establish social groups due to WFH, or are hesitant because of crime or safety or hygiene.

Our new grad offers, for example, have SF relocation in Q2 2022.

If the mortgages are perpetually ultra expensive, then it’s not a bad place to park your money.

I don’t know of any tech workers living in shacks in SF. I know people paying an extra 1-1.5k to live in 1bdrms vs. outside of SF/NY. If you keep a lower budget, you’ll probably end up in interesting situations in shared housing, which can get pretty shitty.

Lots of anecdotes, but when you look at the people who stay in SF you see people working at big companies and people doing the serial startup think. Survivor bias considered, these peoples’ resources have trended toward compounding over time and growing faster than other places.

SF is hot for startups, and even if those companies move out once they’re large, new companies are filling the gaps continuously. The high equity culture associated with that sees folks without a lot of cash, but that’s been changing the last several years, too as competition for hiring has gone way up.

2 million dollars for a shitty house is ridiculous. But it doesn’t really matter if you’re making 5 million every 10 years. Local banks will even get creative and lend against illiquid stock options now, sometimes non-recourse.