Bro lol is this like your first day on the job? The faux "brutal honesty" as a personality trait is what smelly antisocial computer nerds have always been known for. Just ignore them.
> I love the insinuation that I must be an evil prick.
the insinuation is that there is deep, rich, delicious, irony in someone writing this
> The program doesn't work for everyone, but it does have a purpose, and it is frustrating when selfish academics bastardize that purpose to give this kind of false impression of the degree.
after giving everyone reading a false impression of what a PhD is worth. ie you sound extremely selfish yourself when you use phrases like
"Maybe you did get that but you aren't using it in your job; if so, then maybe you didn't need that PhD, but that's hardly the fault of the degree."
and
"PhD is not about learning content. It's about picking up research independence, confidence, and a strong capacity for critique."
and
"No, this is precisely what the PhD is supposed to be for. It should be the most challenging topic of your entire early career, or your supervisor wasted your time. You have a handful of years to impress people, so they have to count."
ie ludicrous absolutist terms.
> Otherwise, you are in the ivory tower telling others that they shouldn't come in.
...are you a native english speaker? the ivory tower is academia. i am emphatically (as i've been emphasizing for 2 hours now) not in the ivory tower and i advocate for everyone to avoid the god forsaken place no matter what.
> Yes, people get FAANG jobs without doing higher education
the vast vast majority of my coworkers have BS/MS. the two best engineers i know (extremely successful ICs) have only a BS. the other PhDs i meet in industry are generally worthless "architects" who can't hack their way out of a paper bag.
EDIT:
it's amazing to me that the conflict of interest here isn't front and center: you're still in academia recruiting students! of course it's critical for you that the dream of academia lives on! if you had any integrity you would have disclaimed your conflict of interest at the outset.
do whichever one of these online MS which permit you to leave off the "online" part (i.e., are awarded through the conventional faculty). i'm not sure johns hopkins does but OMSCS from gatech does.
1) my advisor is literally in the top 500 most cited researchers in the world
2) every single other student in systems had the exact same experience
in summary: your "no true scotsman" doesn't work here because by all measures all of these people are the scotsmen.
> Immense challenge is suffering
this is facile - torture is suffering, deprivation is suffering, prison is suffering. immense challenge is ... challenge. stop with the exaggerated language please. stop writing these paeans for research. it's not some ethereal pursuit. for a select few it's a calling. for most it's just a shitty job.
> find another PhD supervisor please, before it is too late.
bro you are so out of touch it's laughable. there are departments full of your so-called "not true advisors". what do you recommend to the students in these departments who are post-quals and are just now discovering the truth? you recommend to them they what? transfer schools? drop out after 2-3 years of reduced earnings? will you compensate them?
> No, this is precisely what the PhD is supposed to be for. It should be the most challenging topic of your entire early career, or your supervisor wasted your time.
again my guy: take a look at literally any top conference and tell me how many papers do truly novel work? as i commented below: i grew up in math where novel work meant a truly original theorem. that kind of quality is 1/1000 in neurips.
> you were used as part of a paper mill
did you catch the part where i attend a US T10? how do you square your assessment with that?
> The program doesn't work for everyone, but it does have a purpose
there is literally no program. you're completely full of shit. there is no "standardized phd". every single department around the world completely makes it up to be whatever they want.
> it is frustrating when selfish academics bastardize that purpose to give this kind of false impression of the degree.
have you looked at the mirror recently? the frustration comes not from the craven/mercenary individuals who admit their cravenness - it comes from gaslighters like you who claim there's some idealized version of it that exists that everyone supposedly falls short of (hint hint: have you ever heard of this convenient concept of original sin?).
EDIT:
> it seems you did not experience what you should have
i got exactly the experience i needed to disabuse me of the illusion that academia was a priesthood in pursuit of truth/knowledge/beauty/whatever. so that was perfect (i will never step foot on another academic campus again and i will warn everyone else off from it too). in addition i got a job in FAANG so that was a nice consolation prize :)
> Granted, my PhD was in math, not CS, so I'm sure the experience was different
my BS and MS were in (pure) math (my MS thesis is on convergence of the ito integral...) and my PhD is in CS systems. CS outside of theory is worse than an empirical discipline - it's a "throw spaghetti, lasagna, burgers, caesar salad at the wall and see what sticks" discipline. it bears literally no resemblance to math (pure or applied).
> Maybe the problems in CS are easier... Of course, the pace of publication is far slower in math, so I'm sure this is a factor in the choice of problems.
yes and that should tell you everything you need to know - there are kids in my department graduating with 5 first author conference papers (i had "only" 3). how much of those papers do you think is original work really?
do you have a phd? did you get it in the last 10 years? because i have one as well and 100% agree with op - it was worthless. and i got mine from a "world class" school too (US T10).
> It's about picking up research independence, confidence, and a strong capacity for critique.
lolol maybe in the days of yore. today it's about pumping out questionable papers that your advisor tells you to pump out and targeting the right conference.
> It is supposed to be suffering of a special kind
are you also one of those people who takes cold plunges every morning? this myth is what perpetuates the same horrible relationships with shit advisors. it's not supposed to be suffering. it's supposed to be challenging. there's an enormous difference.
> an experience in grinding and radical unproductivity when the problem really is that hard
there are no problems like this in academia (at least not CS) because it's absolutely impractical (re graduation, tenure, etc.) to set out tackling problems which are intractable.
in summary: this entire comment is "phd virtue signaling"
> PAW reframes the foundation model from a per-input problem solver into a tool builder: invoked once per function definition, it produces a small reusable artifact whose subsequent calls per function application are cheap and offline.
Umm you can just get the LLM to spit out real functions instead of fuzzy functions and just run those real functions through real interpreters, which is also "cheap" and "offline".
> negate that you have a stack of transforms that relate a point in world space to one on screen space and you want to be able to project from one to the other.
no it doesn't "negate", it's all completely orthogonal (pun) or irrelevant. like for real just please take a look at
> PCA is an orthogonal transformation of the covariance matrix
Yes you're now the second person the literally repeat the same thing I've already stated extremely clearly and succinctly: PCA is not just rotation (hint: you also need to understand covariance).
> I’m not sure why you’re both negative and dismissive. Transformation matrices in graphics are a good and approachable way to get used to linear transformations, which turn out to be useful pretty much everywhere.
I've already literally drawn the analogy/metaphor that I've drawn: if you think 2d/3d rotation matrices as they are used in graphics is any kind of introduction to the matrices in ML (modeling linear transformations or otherwise) then you're probably the type of person that believes that cash registers any kind of introduction to finance.
My point is not that hard to understand. Graphics in no way, way, shape, or form prepares you for ML. I don't understand why this is so controversial.
i don't understand who is having trouble reading the dialogue here you or i;
> there is absolutely no sense in which the SVD/PCA decomposition is just a rotation matrix... (hint: scaling is extremely important)
...
> SVD is the decomposition of a matrix into two rotation matrices and a scaling matrix, by definition:
yes that's exactly what i was implying when i said SVD more than just rotation, scaling is also important.
my point, which is my same original point, is that if you think learning about rotation/euler matrices is going to prepare you in any way, shape, or form for ML (vis-a-vis SVD/PCA or RoPE or anything else) you're in for a very rude awakening.
https://machinelearning.apple.com/research/introducing-third...
they just suck