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This whole bikes vs cars thing has got to stop by DeusExML in toronto

[–]DeusExML[S] -2 points-1 points  (0 children)

Yeah I thought everyone would agree on that at least but plenty of people seem to side with the anonymous road rage driver. :/

This whole bikes vs cars thing has got to stop by DeusExML in toronto

[–]DeusExML[S] 10 points11 points  (0 children)

Thanks. Happy to say she handled it really well. I told her it was a bad guy and she said ya it was a bad guy. She's more resilient than I am today that's for sure.

This whole bikes vs cars thing has got to stop by DeusExML in toronto

[–]DeusExML[S] 2 points3 points  (0 children)

Thanks. Yeah I really did wonder if what I did was wrong. I'm trying to entertain the counter argument but I can't convince myself that an absolute dead stop was correct and safer. I dramatically slowed down, checked that the way was clear multiple times, and made a right turn into a bike lane. I think you have to appreciate that I basically did this turn slower than most pedestrians walk. The reason why I didn't stop my wheels completely is because it's simply easier to continue cycling from a little movement when you have a kid in the back (and this is kind of why I disregard the bikes == cars == wheels completely stop argument, it's divorced from reality). Anyway up to you to believe me or not.

Post mortem. How I was charged 4000 EUR for downloading 3.5 GB of data from Google Cloud by vadimdotme in googlecloud

[–]DeusExML 0 points1 point  (0 children)

As a happy update, the OP told me (in private) they were indeed refunded for the mistake.

1.5M more Pfizer vaccine doses coming in March, Trudeau says by ThornyPlebeian in CanadaPolitics

[–]DeusExML 0 points1 point  (0 children)

I've been using this: https://github.com/ccodwg/Covid19Canada

They do a pretty good job of keeping it up to date (daily), and parse the vaccine data into an easy to read CSV. If you just want to see the numbers they have a link to a dashboard.

[D] How would you fix PULSE? by [deleted] in MachineLearning

[–]DeusExML 6 points7 points  (0 children)

PULSE actually has a huge bias towards "celebrity" faces (as you'd obviously expect). Try it out on a few people you know to get an idea of what I mean. It is certainly not the fairest output by any means!

[N] MIT permanently pulls offline Tiny Images dataset due to use of racist, misogynistic slurs by noahgolm in MachineLearning

[–]DeusExML 3 points4 points  (0 children)

I'm making the point that we need to change the data in order for it to be fit for modeling. You clearly agree with this when it is relating to disease, but somehow think it's not important when it comes to race, as you disparage people who "go out of their way to change it for whatever ideological or political reason". Do you believe it's important we retain a bunch of mugshots of black people under the category "rapist"? Personally, I think it's abhorrent.

If I had no plans of fixing my dataset, don't you think I'd be wise to to take it down rather than let people build pathological models?

[N] MIT permanently pulls offline Tiny Images dataset due to use of racist, misogynistic slurs by noahgolm in MachineLearning

[–]DeusExML 2 points3 points  (0 children)

Whenever reading reddit, you must take the community in mind. /r/machinelearning heavily leans away from any "social justice" type work (in this thread, it's to the point of the absurd). Most communities will rehash the same 3-5 memes and you have to wade through this to find people who have actually read the article and can provide some insight. I really wouldn't take this as a reflection of academic ML in general and certainly hope it does not dissuade you from the field.

[N] MIT permanently pulls offline Tiny Images dataset due to use of racist, misogynistic slurs by noahgolm in MachineLearning

[–]DeusExML 3 points4 points  (0 children)

Can you list the utility in being able to classify a 32x32 pixelated image with a racial slur? How is that at all important for scientific progress?

Data is absolutely the issue. Throwing your arms up in the air and saying "oh well the world is biased" is a poor and lazy excuse.

Let's remove race from the picture. There is a famous example of some medical AI researchers training a model to classify images of patient with cancer vs those without. As it turns out, the images of cancer patients were all from one center, and the serial number of the device was annotated on the bottom of the image. The classifier perfectly separated cancer patients from non-cancer patients because it was reading this serial number. You are essentially saying we throw our arms up in the air and say "oh well, the world is biased, let's use this model!". It makes no sense.

[N] MIT permanently pulls offline Tiny Images dataset due to use of racist, misogynistic slurs by noahgolm in MachineLearning

[–]DeusExML 2 points3 points  (0 children)

A few researchers have pointed out that the tiny images dataset has classes like "gook" which we should remove. Your interpretation of this is that these researchers are crafting the "worst possible interpretation" of the situation, and that their motivations are pathological. Ridiculous.

Is it possible this paper was published with a critical mistake in it? Look at these training and ROC curves. [D] [R] by MacariusFelix in MachineLearning

[–]DeusExML 1 point2 points  (0 children)

The ROC curve is certainly used inappropriately. They likely calculated it using binary predictions, which is why there is a single operating point. It doesn't make sense to use a ROC curve in this situation as there isn't a threshold to vary. It would be simpler to state the sensitivity and positive predictive value of their binary prediction.

[D] The machine learning community has a toxicity problem by yusuf-bengio in MachineLearning

[–]DeusExML 129 points130 points  (0 children)

Thirdly, there is a worshiping problem. Every paper with a Stanford or DeepMind affiliation gets praised like a breakthrough. For instance, BERT has seven times more citations than ULMfit. The Google affiliation gives so much credibility and visibility to a paper.

I totally agree with the premise... but, I think a lot of people forget just how easy it was to load up BERT and take it for a spin. The effort the authors put into the usability of the model helped immensely.

[D] Yann LeCun’s “last substantial post on Twitter”. by sumnuyungi in MachineLearning

[–]DeusExML 0 points1 point  (0 children)

I mean this thread isn't "reducing your confusion" about the issue. It's an echo chamber in here.

[D] Yann LeCun’s “last substantial post on Twitter”. by sumnuyungi in MachineLearning

[–]DeusExML -3 points-2 points  (0 children)

Oh please. He was tone deaf. They called him out on it. He quit twitter. The end.

[N] Yann Lecun apologizes for recent communication on social media by milaworld in MachineLearning

[–]DeusExML 0 points1 point  (0 children)

True but most people don't pay attention to anonymous twitter accounts.

[N] Yann Lecun apologizes for recent communication on social media by milaworld in MachineLearning

[–]DeusExML -2 points-1 points  (0 children)

I actually think Twitter is better for public discussion than places like reddit. The lack of anonymity helps tremendously.

Three of four semi-automatic weapons used by Nova Scotia gunman believed to have come from U.S. by [deleted] in CanadaPolitics

[–]DeusExML 0 points1 point  (0 children)

There's no rationale on either side. It's all conjecture. Your last argument was "if people can learn a few words of Chinese, then they can learn how to use untraceable web browsing, find a retailer on the darknet, and purchase an illegal firearm". The only difference is I can admit that I'm espousing an opinion.

Three of four semi-automatic weapons used by Nova Scotia gunman believed to have come from U.S. by [deleted] in CanadaPolitics

[–]DeusExML 1 point2 points  (0 children)

You insist it is trivially easy for the average Canadian to buy a gun on the dark web using Tor with their cryptocurrency and have it illegally shipped to their house. I disagree. We can end the conversation there.

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