echinopsis posted:

hmm thanks

my first result turned out absolute dogshit and it’s kinda burned me lol

fack you posted:

so like you know in star trek all the doors on the enterprise slide open, but it was just some person pulling on wires or something at the right time in the script, not a real automatic door, so it appears to work not on motion, but like a person's intent because sometimes there'd be a whole conversation right next to a door and it'll magically open when riker is done chatting up troi or whatever ugh. could you feed in all the ridiculous footage into all this machine learning poo poo and end up with software that'd actually open a door based on intent just like how it appears on the show I don't know

fack you posted:

so like you know in star trek all the doors on the enterprise slide open, but it was just some person pulling on wires or something at the right time in the script, not a real automatic door, so it appears to work not on motion, but like a person's intent because sometimes there'd be a whole conversation right next to a door and it'll magically open when riker is done chatting up troi or whatever ugh. could you feed in all the ridiculous footage into all this machine learning poo poo and end up with software that'd actually open a door based on intent just like how it appears on the show I don't know

Feisty-Cadaver posted:

somebody post that gif of the seagull tricking the convenience store door sensor and running back out with a bag of chips

or maybe it was a duck I forget

quote:

In such markets where both stations appeared to adopt algorithmic software, as estimated by sudden changes in the size and rapidity of price changes, margins increased by an average of almost 30%. Without pricing software at both stations, margins were unchanged.

beer pal posted:

u know how when you have a car you're all like yeah i get it... the gas blows up and that sends the pistons moving and then the wheels turn or whatever.. and then you take it to the mechanic and they say your screwjank is all rusted and your double boiler has got an oil leak int he drivecrank.. well thats what i got from the op of this thread. everybody knows what machine learning is its when the machines learn. even with the probably laymans explanation and sardonic tone all the computer words got me messed up. i read one computer word and its lights off up there. but anyway after that its people making small joke posts much like a yobbo would do on the subject of machine learning.

the tone from what i gather is mostly cynicism about the uses of machine learning (shady data collection & surveillance etc). theres a bunch of jokes about deep faking porn videos. another issue that comes up is the conception that algorithms, by the fact that they're run by computers and not done directly by humans, are inherently neutral / free of bias which is wrong & bad since if you teach computer to be racist, computer will be racist.

heres a couple posts in a row that i could understand and that were interesting to me:

The Management posted:

for those of you who haven’t worked with machine learning, here’s how it’s works:

* you take a bunch of pictures of shoes or horses or whatever the gently caress you want to recognize.
* then reduce those images to some ridiculous low resolution thing
* then you cram those images through some matrices until you get some matrix that happens to tell you horse or not horse.
* nobody knows why this matrix is horse, but it seems to work so you’re like, cool, I made a horse model.

now you take your horse model and set out to detect some horses. you take some pics and run them through your model and it’s all here a horse, there a horse, no horse there. but then there’s one picture of a horse and your model says no, not horse. and you have no idea why it’s not horse. the matrix is just a bunch of 8-bit values, it doesn’t even look like a horse. the answer, which you will never discover, is that the picture has a reflection of the sun in the water under the horse, which is not where the sun goes and your model couldn’t deal with that.

and then you realize that your model doesn’t understand poo poo, it hasn’t learned anything. it is incapable of learning, it’s a loving filter.

Sagebrush posted:

To me the most damning example is those papers with adversarial techniques where they apply a really subtle filter to the image and it tricks the algorithm. Like you start with an image of a turtle, and the machine recognizes it as a turtle, and then you apply a tiny convolution that affects 10% of the pixels in an almost undetectable way, and the algorithm is now certain that it's a picture of a gun. But it still looks like a turtle to you.

So the takeaway is that whatever the algorithm is triggering on, it's absolutely not what humans think of as turtle-like features. It doesn't see things the way that humans do, doesn't have the same "mental" model of the world. That means you can't make any assumptions about its behavior that are based on how humans would treat a given situation. yet that's exactly what people do when they start pressing these systems into service in things like self-driving cars.

this all seems to agree with my conception prior to clicking on the thread that this kind of thing is 1) fake 2) nefarious or 3) both

Cybernetic Vermin posted:

how much is jeffrey paying them for that dreary review work?

big scary monsters posted:

beer pal seems to have a solid understanding of machine learning, missing only this key image that i guess i probably got from this thread but i'm too lazy to find the post to quote

Trabisnikof posted:

Nature Communications charges a $5,700 publishing fee too lol

fart simpson posted:

why? do some of the humans survive?

animist posted:

oh also, this short story got posted in the c-spam doomsday econ thread (i think??) and its really good. pretty solid examination of "but what if the machines turn on us???": https://rifters.com/real/shorts/PeterWatts_Malak.pdf

ultrafilter posted:

Midjack posted:

https://twitter.com/DeepCapybara/status/1344840846177427457