steev

But isn't the real issue how these small changes add up over time? Seems kind of like saying "a single car will not put out enough CO2 to impact the atmosphere" but here we are with millions (billions?) of cars that are definitely having an impact on their environment. Granted, we will not have millions of data centers but maybe we have enough that it makes a negative impact. Certainly seems plausible.

I don't know anything about ecology, but my intuition is that all of these things from wind turbines to data centers under water, have an impact on their ecosystems. It wouldn't surprise me if we found out these had a negative (or neutral) impact on their environments.

I guess my point is that it seems naive to simply hand-wave off the possibility that these supposed environmentally friendly technologies actually negatively impact their environment. Whether or not that negative impact is less than the alternative is an interesting question.

Work harder.

Never give up.

Nothing to it but to do it (Ronnie Coleman)

The journey is the reward (I think this is Steve Jobs)

What can I do to move myself towards my goals right now?

These are things I usually say to myself throughout the day.

You really want all their staff to lose their jobs just so your image search results experience is better? Seems a bit selfish don't you think? What about all the users that enjoy it?

I don't like pinterest and I get the frustration but come on, there are better solutions than "this thing bothers me so let's get rid of it completely."

At least for beginners, they absolutely are. I have found undergrads generally get the idea behind something like HashMap<Integer, String> but getting them to reason about OCaml modules takes quite a bit of effort.

I can't understand why OCaml doesn't have mass adoption.

Probably for the exact same reason each year you think about learning OCaml you decide not to (I mean this sincerely, not trying to be snide).

I think the main reasons it doesn't see mass adoption in industry:

* There are only two major companies that do a substantial amount of OCaml that I can think of off the top of my head, Jane Street and Ahrefs. Facebook does some OCaml too but I don't think it's a core part of their stack.

* The tooling is lacking.

* People have an easier time learning Python or Java so you'll have a larger pool of candidates if you use one of those languages.

I am not sure I follow. It seems plausible that the sky-high taxes are a major motivator for people wanting to leave CA but a recent change in SF made it possible for people to move to a different state (e.g., Twitter and FB allowing permanent remote work and Google working remotely into 2021).

This [1] is a a much more detailed course that gives a great introduction to OCaml.

[1] https://www.cs.cornell.edu/courses/cs3110/2019sp/textbook/in...

The Girl Scouts are a non-profit yet they don't give their cookies away for free.

I don't see how this is a nuanced perspective - it seems to restate the same complaints/arguments just about every comment makes in these discussions.

A nuanced perspective would look at the arguments as to why OpenAI is doing the things they are doing. For example:

* OpenAI publishes in closed journals (actually conference proceedings) because that is where all the cutting edge research is published and reviewed. I cannot recall an OpenAI paper that wasn't available either via arXiv or their website, despite being published in a closed journal. What is the alternative here? Where should they go for quality peer-review? Yes you can argue the peer review at top conferences is not quality, but is worse quality than no peer-review or peer review from open-access no-name journals?

* How does OpenAI make money? How much are they bringing in? How much does it cost to support things like the OpenAI Gym, etc.? How much does it cost OpenAI in terms of bandwidth to host pre-trained versions of GPT-3? At some point a company needs to make money and prioritize resources - they can't give everything away for free in perpetuity.

I don't think these questions have obvious answers - there is give and take.

How on earth is any of the advertising antagonizing? I had to read through the course page twice to look for anything remotely resembling a criticism and came up blank.

If it is the quote you added to the bottom of your comment, my question still stands. That isn't an insult to anyone (certainly not mathematicians) but rather a comment that many people freeze up when it comes to mathematics (at least that was my interpretation).

I am completely baffled by this response. At a minimum, that is not what narcissistic means in any sense of the word. I cannot understand how trying to improve yourself, whether as a research, programmer, or just general human being, makes one "narcissistic." I would love to understand this if you care to explain.

Imagine having to work with someone that judges based on your education rather than you as an individual! Probably something only a PhD would do, right? :)

God forbid anyone pursues higher education because they want to become a better researcher.

I would suggest you spend some time thinking about your EQ rather than spending time on the internet posting nonsense generalizations about entire classes of people.

I work from home as a software engineer at a major tech company.

Infrastructure: my company provides money to setup your workspace. Buying a desk is the most expensive part here but really you can get a solid setup for < $500.

Internet costs: I was already paying ~$120/mo and I get some of that reimbursed. This seems like a standard living cost though, not something unique to working remotely.

Productivity creep: I define my schedule based on my deliverables. At least with my team, no one expects me to be available 24/7. I work a full day but if I need to run an errand or take care of something during work hours it is no big deal. As long as I am getting my work done, everyone is happy.

Rewards/promotions: who knows - anecdotal evidence doesn't mean much here.

Mental costs: if you live alone, this could definitely be very lonely. I am lucky enough to have a wife, kid, and dog so loneliness isn't an issue. But this really depends on a case-by-case basis.

Personally I love working from home. It is more comfortable, I am paid incredibly well despite be scaled for a low COL area, and the work is super interesting. The most important part of this is now we can move wherever we need to for my wife's career. This flexibility is hard to put a price on.

A degree from a reputable university doesn't count in _any_ profession (ok, that's hyperbolic - it certainly counts for something in run-of-the-mill office jobs). Even doctors, lawyers, actuaries, accountants, etc. have to prove they are capable to a central authority before they can work.

That's not the case at Google. The call schedule for SREs is pretty nice.

They are working on things that interest them. What is wrong with that? That is also a little insulting to the researchers that are actually studying how to cure cancer.

Probably to try and prevent this from turning into a flamewar. A lot of people just read the title and don't read the article and then comment based on what they think the article is about.

I'm guessing they are referring to a work phone.

This doesn't seem any more ridiculous than companies setting a higher price and then always having the item on sale. I think JCPenny famously tried simply lowering their prices and sales went down. I guarantee if you ask the average person "would you rather companies cut the BS and just lower their prices rather than have items on sale in perpetuity" they would of course say lower the prices. But as the anecdote would demonstrate, that isn't how things actually play out.

The point is, when it comes to consumer behavior, I don't think anyone has a clue what to expect. It would not surprise one bit if vacuum companies make louder vacuums because the consumer thinks it works better.

It seems pretty reasonable to me, as an interviewer, to look up the question I am thinking about asking to see what is available online. Is there a reason you wouldn't do this?

My main objection is it dramatically decreases your productivity. If building and testing takes 5-10mins (which is the case in our codebase) trying to fix a bug can take forever when you aren't exactly sure what the cause is. You don't want to try multiple fixes simultaneously because if something doesn't work you aren't sure which of the fixes (if any) might be causing the issue.

Maybe a different way to look at it is: if you could shorten the BTD loop to a minute or two, why _wouldn't_ you want that?

That was my hunch.

People always say "use numpy", but that is only possible if your algorithm can be described in terms of vectorized operations. For many kinds of processing, the only alternative is C/C++ (through Cython

Agreed

I tried really hard to like Julia and just couldn't get behind it. We used it for a research paper in the area of optimization and by the end of the project I really regretted it. Performance and built in numerics libraries were great, but I feel the language ergonomics are pretty bad. I hate Python just as much as the next developer, but I do find it much easier to use than Julia for research type work.

My biggest qualm with Julia (and maybe this speaks to my inexperience with the language) is that it isn't always obvious when Julia is going to make a copy. We spent about an hour working through some code that was very slow (props to Julia's profiling tools) but couldn't figure out _why_ it was slow. It turned out that despite our best efforts, Julia was still copying a vector despite us using pre-allocated scratch space for the work.

From my point of view, if I am comparing algorithms then Python's performance doesn't really matter and it's ergonomics win. If performance matters I'd just use C++ or Rust.

Typically straightforward Numpy gets me from 40x slower than straightforward C to 5x slower.

I find this hard to believe. What kind of numerical work are you doing? Even something as simple as matrix-matrix multiplication should be hard to beat with C, unless your C code is using a cache efficient algorithm.

This sounds like an architecture problem, not a language problem. Can you elaborate?

I don't think he's saying he literally thinks slower than 80 WPM. I interpret this to mean the rate at which he writes his thoughts down matches the amount of time it takes him to think of what he wants to write next or how he wants to phrase the next sentence. When I am writing research papers there are long pauses between sentences as I think of what I want to say next or how I want to phrase the sentence. That doesn't mean there are long pauses between sentences in my thoughts throughout the day.

Just to be clear, the book series you are referring to is "Synthesis Lectures on Computer Architecture" published by Morgan-Claypool, right?

If you had to rank them in importance for the average engineer, how would you rank them?

The scale and complexity of the problems is appealing to some people. There are very few companies where you get to work on problems with the same scale problems as Google.

In my experience you can share your views in Google as long as everyone around you shares those views.

Not to get too much into the weeds, but in my experience in HPC for numerical work out-of-bounds read/writes are almost never an issue. I say almost because I'm sure someone somewhere as slipped up, but I've literally never had this problem. A priori you know your bounds and looping within them is trivial. I don't think I've ever encountered any data where you did not know the dimensions at program startup. I have experimented with Rust because I thoroughly enjoy the language (but am not an expert), and immediately got bit by bounds checks during vector indexing.

I also find if you write modern, idiomatic C++ code you rarely, if ever, have to worry about memory safety issues.