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Making deep learning go brrrr from first principles (2022)

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Re: Making deep learning go brrrr from first principles (2022)

#21

Post by dageshi »

tysam_and wrote: post #19
JanneVee wrote: post #18

Earlier quoted context omitted.

> As an aside and a comment on the article, I feel dismayed by the author's decision to include the 'go brrr' meme. It's connected with toxic sentiment and communities from where it's generally used, and is oftentimes used to needlessly mock a group of people. There was good content in reading the article, but it turned me off at the beginning as it was rather childish -- in not-a-pleasant way -- and unfunny, and it…

I did address those earlier in terms of association, I'm not sure if I understand the aggressive tone of this response however, or of a few of the assumptions in it. A few other people have made similar points about this culture as well.

I think your comment comes off as "concern trolling" whether you intended it to be or not. And indeed we are now off the topic and discussing "going brr" instead of the subject.

Re: Making deep learning go brrrr from first principles (2022)

#22

Post by JanneVee »

tysam_and wrote: post #19
JanneVee wrote: post #18

Earlier quoted context omitted.

> As an aside and a comment on the article, I feel dismayed by the author's decision to include the 'go brrr' meme. It's connected with toxic sentiment and communities from where it's generally used, and is oftentimes used to needlessly mock a group of people. There was good content in reading the article, but it turned me off at the beginning as it was rather childish -- in not-a-pleasant way -- and unfunny, and it…

I did address those earlier in terms of association, I'm not sure if I understand the aggressive tone of this response however, or of a few of the assumptions in it. A few other people have made similar points about this culture as well.

I'm trying to get the point across that not all people come from the same place and don't keep the same connotations and associations with the memes they use. Making them responsible for your associations is in my view fairly aggressive.

If you feel validated by people that think the same thing go ahead, but I think is that the 'meme policing' was unnecessary on a technical response of the content.

Re: Making deep learning go brrrr from first principles (2022)

#23

Post by tysam_and »

dageshi wrote: post #21
tysam_and wrote: post #19

Earlier quoted context omitted.

I did address those earlier in terms of association, I'm not sure if I understand the aggressive tone of this response however, or of a few of the assumptions in it. A few other people have made similar points about this culture as well.

I think your comment comes off as "concern trolling" whether you intended it to be or not. And indeed we are now off the topic and discussing "going brr" instead of the subject.

That's a fair response. I'm generally okay (some modern connotations aside) with people using the going brr bit. The servers where H.He spends a lot of time in actively use the meme when mocking outside groups (w/ few neutral uses), and it's a bit frustrating as it actively causes rifts that make it harder for me to do professional work.

I bring it up because I'd like to bring light on it if it's sorta seeping into the mainstream, a lot of people adjacent to it sort of just ignore it and leave it be. Like, I've actively seen this meme used in the main AI servers where it's used to push down people who do question blind scaling, for example (which is not what Sutton was talking about). It silences conversation and halts diversity, and it's an actual problem unfortunately.

Thankfully there are other spaces where it's not as much a problem, but since it's pretty well-tied and trickling into HN, felt appropriate to share my 2c. And people may well say what they want (including brr) in response. :)

Re: Making deep learning go brrrr from first principles (2022)

#24

Post by tysam_and »

JanneVee wrote: post #22
tysam_and wrote: post #19

Earlier quoted context omitted.

I did address those earlier in terms of association, I'm not sure if I understand the aggressive tone of this response however, or of a few of the assumptions in it. A few other people have made similar points about this culture as well.

I'm trying to get the point across that not all people come from the same place and don't keep the same connotations and associations with the memes they use. Making them responsible for your associations is in my view fairly aggressive. If you feel validated by people that think the same thing go ahead, but I think is that the 'meme policing' was unnecessary on a technical response of the content.

This feels pretty aggressive, I think we're on a different wavelength here. That's not quite what I'm saying, but it seems best for us to leave it at that.

Re: Making deep learning go brrrr from first principles (2022)

#25

Post by JanneVee »

tysam_and wrote: post #24
JanneVee wrote: post #22

Earlier quoted context omitted.

I'm trying to get the point across that not all people come from the same place and don't keep the same connotations and associations with the memes they use. Making them responsible for your associations is in my view fairly aggressive. If you feel validated by people that think the same thing go ahead, but I think is that the 'meme policing' was unnecessary on a technical response of the content.

This feels pretty aggressive, I think we're on a different wavelength here. That's not quite what I'm saying, but it seems best for us to leave it at that.

Sorry but I'm actively trying to help you here. From the other reply

> it's a bit frustrating as it actively causes rifts that make it harder for me to do professional work.

My comments that you are taking that I'm being aggressive is that you have made your professional frustration about your feelings. These issues isn't who else uses the meme, but that the meme spreads a bad idea that makes your professional life harder.

Re: Making deep learning go brrrr from first principles (2022)

#26

Post by [deleted] »

tysam_and wrote: post #23
dageshi wrote: post #21

Earlier quoted context omitted.

I think your comment comes off as "concern trolling" whether you intended it to be or not. And indeed we are now off the topic and discussing "going brr" instead of the subject.

That's a fair response. I'm generally okay (some modern connotations aside) with people using the going brr bit. The servers where H.He spends a lot of time in actively use the meme when mocking outside groups (w/ few neutral uses), and it's a bit frustrating as it actively causes rifts that make it harder for me to do professional work. I bring it up because I'd like to bring light on it if it's sorta seeping into t…

[deleted]

Re: Making deep learning go brrrr from first principles (2022)

#27

Post by ssivark »

tysam_and wrote: post #20
ssivark wrote: post #12

Earlier quoted context omitted.

> Experiment noise has taught me so much over several thousands of manually-run (yes, I'm a masochist, it's a personal preference) experiments converging in a few seconds. Is there any resource that makes legible how to go about this? Or shares insights into the process of iterative learning through experiments, more broadly?

I'd like to create it in the future, but I can share a rough version of what I have. Basically, as long as you gain more information than noise by scaling your experiments down (i.e., the smaller models create similar directions in the needle), then it's easier to run lots of experiments, and much more cheaply oftentimes too. Remember that performance oftentimes runs on a log(1+p) curve in terms of cost/time/complexi…

Tysm; this is good stuff for me to ruminate on. One of the challenges for me has been switching to this very empirical orientation (I’m far more used to a conceptual understanding driven mode). If & when you do get around to fleshing out your perspective, I think it would be quite invaluable :-)
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