I once heard a repair tech say that XPS stands for “eXpensive Piece of Sh*t” and now that always comes to mind, although it never totally made sense to me as I didn’t think they were particularly expensive. I have an XPS and I did replace the battery at one point, but other than that I think it performed fairly well for my simple needs. I think I paid $499 for it around 2018.
I've had a number of Dell's in the past and IMO their "consumer" and "professional" lines might as well be different brands that happen to share the "Dell" name.
Their consumer laptops are all garbage IMO, mainly cause I find they try to max out specs so it looks good on paper and skimp on really basic things like the hinges, batteries, etc.
Their professional laptops are much better, my parents just got rid of a Dell Latitude that I passed down to them after college, and when I bought it for college it was already 5-6 years old so all in all it had a service life of more than a decade. Specs might be down compared to the consumer line but everything else IMO is much better built (chassis, battery, hinges, etc)
The base model XPS laptop was ~$999 at the time (vs $1299 for a 2023 model). Which sadly doesn't feel all that expensive today even though I would absolutely still call a $1000 laptop expensive.
It’s kind of funny, now when I have a programming question I find myself going straight to the documentation which is a better habit than searching anyway. By the time I would have combed through search results, blogs, and stack overflow to find a relevant answer, I might as well have just read a few pages in the docs and gotten a more complete knowledge of the topic.
I think of it as my personal journey to “RTFM”. I now understand why people are so strict about that. To be fair though, I haven’t really dabbled into alternative search engines much yet.
Completely agree, and I have been feeling similarly. While I did manage to get a job, I have still been miserable. The work is not interesting or meaningful and working remotely is very isolating. It’s been discussed to death, but I think the lack of “third places” makes it very difficult to date or even spend time with friends.
Like you mentioned, without a spouse or kids it’s hard to find purpose. I don’t have an intrinsic drive to grind or make more money just for the sake of it.
I hope that things will get better with time, but I can’t think of any concrete reasons why they would. Of course some people will get married and have kids, but many won’t. It can be hard to find reasons to get up out of bed every day.
I wonder if some just realize that they don’t like STEM. Maybe they only studied it for family or social pressures, or they heard that engineers can get paid a lot.
Anecdotally, I feel like some of my classmates had no interest in engineering. They seemed to stick around for the money or the benefits or the clout. But if landing a job in the industry became more trouble than it’s worth, I don’t see why they wouldn’t turn elsewhere.
When I read that I thought about the ability to replicate someone’s voice using AI. How would you know it’s me on the other end reading you my key over the phone? Then again, you would need a substantial amount of audio from me to accurately train a model of my voice.
Is it able to run Xcode? I’ve been trying to do some iOS development on Linux and so far my solution has been to use DockerOSX… but this sounds much more convenient.
That's actually useful. I need the asset bundlers so I can build for MacOS without having a Mac. I already build Rust programs for Linux and Windows on Linux.
I'm genuinely curious, what is your expectation of candidates looking to get into ML at the entry level?
You seem to look down on those who have
1) learned from online courses
or
2) used AI on tasks that don't require it
Isn't this a bit contradictory? Or you expect candidates to have found a completely novel usecase for AI on their own?
I understand that most ML roles prefer a master's degree or PhD, but from my experience most of the master's degrees in ML being offered right now were spawned from all the "AI hype". That is to say, they may not include a lot of core ML courses and probably are not a significantly better signal of a candidate's qualifications than some of the good online courses out there.
So what does that leave, only those with a PhD? I think it's unreasonable that someone should need that many years of formal education to get an entry level position.
Maybe I'm missing something, but I'm really wondering, what do you expect from candidates? I think a few years of professional software engineering experience with some demonstrated interest in AI via online courses and personal projects should be enough.
It sounds like Aurornis was not, in fact, trying to hire people at the entry level.
Most companies doing regular, non-ML development hire a mix of junior and experienced engineers, with the latter providing code reviews, mentorship and architectural advice alongside normal programming duties.
It's understandable that someone kicking off a new ML project would hope to get the experienced hires on board first.
But there are a lot more junior people on the market than senior people right now - as is the nature of a fast growing market.
I agree, it's problematic that there are so many more juniors than seniors in the industry right now. I feel like many juniors are being left without mentorship, and then it becomes much harder for them to grow and eventually become qualified for senior roles. So that could help explain why many candidates seem so weak, alongside with all the recent hype.
I guess eventually the market will cool off and the hype will die down since this stuff seems to be cyclical, and the junior engineers who are determined enough to stick it out and seek out mentorship will be able to grow and become seniors.
But it definitely seems like the number of seniors is a bottleneck for talent across the industry.
I thought we knew better than to use volume of code as a metric.
Relevant xkcd: https://xkcd.com/2899/