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.
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.
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/
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.
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.
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.
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.