Hats off to whoever took time to create this (and the beautiful whippet!).
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Hats off to whoever took time to create this (and the beautiful whippet!).
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Hats off to whoever took time to create this (and the beautiful whippet!).
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@un_bourguignon
Merci pour le ping, je crois que j'en avais vu passer un similaire. J'adore ! -
@un_bourguignon
Merci pour le ping, je crois que j'en avais vu passer un similaire. J'adore !@emeline
J'ai trouvé ça très drôle et bien vu en plus
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@Natasha_Jay @Milena_Hime -
M mindtunes@troet.cafe shared this topic
A andresimous@oslo.town shared this topic
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@srtcd424 @Natasha_Jay@tech.lent wait a minute, where are people getting pain au chocolate with THREE pieces of chocolate in it???
@pork_soda @srtcd424 We say "Chocolatine" and not "Pain au chocolat" #ExportFrenchDebate 🤪
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Hats off to whoever took time to create this (and the beautiful whippet!).
@Natasha_Jay
For me it's like : -
Oh so Gemini has issues differentiating dogs and bicycle seats? Good to know.
@agowa338 these used to be used as adversarial training sets for computer vision algorithms (not this one, probably, but Chihuahua or blueberry muffin, Sharpei or towel, Labradoodle or fried chicken, etc). There are whole image sets of them.
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Hats off to whoever took time to create this (and the beautiful whippet!).
@Natasha_Jay I love these adversarial image sets
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@agowa338 these used to be used as adversarial training sets for computer vision algorithms (not this one, probably, but Chihuahua or blueberry muffin, Sharpei or towel, Labradoodle or fried chicken, etc). There are whole image sets of them.
And captures are often used to label such datasets.
E.g. You know the result to 80% of the shown images and let the user click all of them. The user doesn't know which ones you expect them to click. Then for the few unlabeled ones you record if they did/didn't click them and then you serve the same unknown ones to multiple people and bam you've a very good way to enlarge your datasets.
That's how google originally started with recaptures and what they're doing now...
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And captures are often used to label such datasets.
E.g. You know the result to 80% of the shown images and let the user click all of them. The user doesn't know which ones you expect them to click. Then for the few unlabeled ones you record if they did/didn't click them and then you serve the same unknown ones to multiple people and bam you've a very good way to enlarge your datasets.
That's how google originally started with recaptures and what they're doing now...
@agowa338 yup, crowd-sourced ML training.
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@Natasha_Jay I love these adversarial image sets
@alice Sloth au chocolat
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Glad you posted this before I had to. Well done.
@cainmark Yeah, we all came here to post this. Whippet indeed good. Good whippet.
@phil_stevens @Natasha_Jay -
Hats off to whoever took time to create this (and the beautiful whippet!).
@Natasha_Jay gut kombiniert
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@srtcd424 @Natasha_Jay@tech.lent wait a minute, where are people getting pain au chocolate with THREE pieces of chocolate in it???
@pork_soda @srtcd424 me, sometimes
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@Natasha_Jay Whippet good.
@phil_stevens @Natasha_Jay Yep, now I'm thinking of a DEVO parody playing on "Whippet" vs "whip it".
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A alsternerd@akkoma.alster.space shared this topic
