Great looking - everything but the cutesy front headlights.
I'd slightly prefer a blacked out Tesla truck to that. The main problem with the front/back of the Cybertruck is the it's very flat and plain where even a licence plate or name decal would make it look better. But I have a feeling it will look better in person than online.
While I did snicker at the thought of a Vantablack'ed Cybertruck, I think it'd be a dangerous vehicle to have on the roads - your visibility would be so low.
My thought process went something like, "Oh come on, how bad can they really be? I bet you could <clicks on link> just put... something... over... No. Nope, those are irredeemable."
There's an awful, awful lot of virtue signalling going on in all of these designs. Extra emphasis on the 'awful'.
And considering it's the electric drivetrain that adds all the main features (performance, tow capacity, torque, electrical outlets, etc), they could easily close the gap with Tesla. It remains to be seen on how much people care about the styling and hardened steel body though.
Forgot range. Which depends on weight. Which is saved by the battery enclosure being a structural member of the vehicle. I think to make a decent electric truck it will take more than strapping some batteries under the box and swapping ice for electric.
Robots usually consist of many complicated components. ROS provides a unique and consistent method for those components to communicate with each other via an API and a pub/sub method. That way each one of your components can handle it's own logic via whatever software it likes, just so long as you can connect to the ROS api and let the OS handle orchestrating each component. A bit like a conductor in an orchestra.
I published a research paper as an undergrad on improving an existing algorithm for a team of mobile robots to navigate space and create a map of their environment.
I also used it as an intern at a robotics company to use a microsoft kinect as a depth sensor for helping the robot perceive space in three dimensions.
I was disappointed that he didn't give any information around SPA's he though were good! Does anyone have recommendations for an example of a world class SPA?
I've found that behavior that isn't quite a ritual, but unique to that activity can be highly motivating and beneficial to focus as well. Whenever I want to get deeply focused on code writing, I'll start speaking to myself under my breath. A bit like the intention behind vocalizing your thoughts during a coding interview, it's been very helpful for keeping my mind on track.
is the compensation really like this for a mid level engineer at a FAANG? I'm still fairly new into my career and I can't believe that the enterprise money is sooo much better than the startup world. I'm currently earning around 120k a year with health insurance and no equity. Should I really be designing on trading up into a nice big enterprise job?
I just started a job as a data scientist at a FAANG company. PhD + 2 years of experience for $200k total compensation (plus another $50k in one time bonuses/relo). It’s almost double what my previous (non-tech) employer paid. Although I’m starting to wonder if I should have gone the software engineering route instead. SWEs get double the RSUs as data scientists for the same experience level (so ~250k for my level) and they also didn’t spend 4 years working on a PhD to get there. Oh well... I can’t complain. Very happy with my current situation.
I’m not sure. At average companies, I think SWEs and data scientists make about the same. But the top companies have a much larger software engineering population to choose from, so they can afford to be picky, and the pay correspondingly reflects that. There’s about 20x as many software engineers as there are data scientists in the world.
I think this is changing though, and I think “data scientist” will soon be split into sub-roles. Some companies like Lyft have already changed their title scheme. Business analysts are now data scientists, and those who were data scientists are now research scientists.
The company I work for has an internal job role that isn’t public and an external title that is. So a “data scientist” may have an internal role of “business analyst” or an internal role of “applied scientist”, and there’s a big difference in pay despite the same outward-facing title.
I think the pay scale goes:
Data scientist (business analyst) < data scientist (non-CS PhD) < software engineer = core data scientist (CS PhD) < AI researcher (ML PhD + great publications)
I have a non-CS PhD so I think that’s why I don’t make as much as a software engineer or a core data scientist.
Base salary and bonus is generally the same for all roles for a given experience level; the difference in comp. comes from the RSUs granted.
Facebook's median compensation across all employees is $240k. Median of engineer compensation would be significantly higher. Also note that Facebook's median age is 29.
If you are in FAANG, and in bay area, then your numbers look too low. I know mid-level engineers in bay area, can make ~300k. All this assuming a good engineer who has been performing consistently, and is among the top 10% in his/her team.
The friends I'm talking about are deeply experienced and knowledgeable (10 years minimum, mostly more), phenomenally talented, and incredibly effective at delivering results.
The pay spread between startup and big-co exists at all tiers, but it's particularly huge once you start hitting the top talent.
Starting off with Ubuntu is a good idea. That's the friendliest distro of linux yet it still provides a fair amount of extensibility so you can start playing around with the really cool things linux offers. There wasn't anything I found myself missing. I suppose the keyboard layout is a little different but that's about it? Again though, the beauty of linux is that you can change just about anything for your preferences. I guess the recommendation is simply to just switch and just start and be patient! Good luck!
How many people actually do this vs talk about doing it? I know Mr. Money Mustache is super popular and generally the tenets are a great idea, but I certainly don't know anyone my age (early 20s) who has become a proponent of these ideas. It seems a bit too extreme for my tastes. Why not just get a job you like, save enough that work is optional and enjoy your day to day?
it's that middle bit that seems to cause all the consternation: "Save enough that work is optional". It also could be (and I don't mean to sound like an old grump or condescend so apologies in advance) that people in their early 20s haven't been soured on employment sufficiently yet. I was much more idealistic and had a greater tolerance for work-related BS when I was in my early 20s.
I'm nearly 50 now and after being burned several times I made a vow to myself never to be dependent on anyone else again. Even if you work for an incredibly well-funded company, that doesn't mean some dweeb with an MBA in some office in another city / state / country won't wake up one day and decide to wipe our your entire division just because she needs to make a bigger bonus.
I've seen pensions disappear overnight, industries collapse quicker than anyone ever thought, and vibrant cities crumble when big employers shut their doors. Painful and stressful in the extreme.
I've also blown $10k on something stupid instead of buying another bunch of Apple stock, reasoning that I'd make it up later in life easily enough. That was 1997. The $10k would be well over $1 million now.
The biggest thing to learn is that money doesn't equal happiness. That, for me, is the repeated lesson of MMM and related authors. Freedom to make decisions without reference to finances is a massive, amazing thing.
One point that often comes up is that people shut their mouth about FIRE because if they bring it up, the reaction is often negative. There might be several people you know working towards FIRE but they don't evangelize it.
