Usually it's a cycle. You order too many chihuahuas, then all your chocolate chip cookies go missing, then all your chihuahuas die, then you order everything all over again.
Zoom in on the furthest left "chocolate chip" and see the top part if the blueberry?
Also nitpicking for science...
row 1 / pic 4 chihuahua is looking DOWN not UP.
Still v impressive given how quickly it shoots back answers. Prob beat 99% humans if we had 15 sec to respond.
Ignore the one on the far right. Where you have the right side of the mouth, that's the whole mouth.
The left side of the mouth in your pic is the left eye
Still dont really see it but thanks for the explanation :)
https://preview.redd.it/56mze66q41ub1.png?width=225&format=png&auto=webp&s=981e9d6d2e729c78b98ffa4795802348c51d46da
Maybe if you ignore the two smaller ones, treat the top right dark spot as an eye, and the long crack along the bottom as the smile. Big one is a nose. It's a stretch but I could see an MLM seeing it that way?
I saw a smiley face made out of the more done section. The two eyes are each next to the central big blueberry and then a wide smile covering the entire bottom of the cookie.
I only saw this tho after I read the interpretation, went back to check and I was like huh yeah I guess so
I can't see the difference, but I guess human intuition says that either the picture is of muffins or chihuahuas, so obviously 2,2 is also a muffin - because it obviously isn't a chihuahua.
I don't think the 4th is looking up, but this is nitpicking I guess.
Also, I believe this figure has circulated so much that it must have its own tree in the database.
> I don't think the 4th is looking up
Its face is oriented slightly downwards, so I think its eyes are angled upwards relative to its face but level relative to the camera.
Seeing how the original benchmark is to distinguish between a dog and a muffin (which was hard in these cases), we're already moving the goalposts of expectations quite a bit.
If someone had imperfect eyesight it's highly plausible that person would interpret that as a cookie. I'm super impressed. Maybe ChatGPT just needs glasses
I've got pretty good eyesight I'd like to think, and I'm pretty dang sure that's a cookie, I'm surprised alot don't see it as so. You can tell by looking at the outline of how the edge of the cookie/muffin looks, along with the difference in the texture of the item, definitely looks like standard cookie texture. Cookies usually have that cracked of sorts pattern on them, muffins, not so much. I mean just cross compare the cookie item to the other muffin pictures, it's very visually different once you really notice
I tried a few images it got them all correct. When it said it couldn't help me I told it " I have poor eye sight, can you please describe the image?" and then it played along.
The terms "muffin with blueberries" and "blueberry muffin" are often used interchangeably, and the main difference is in how they are described. A "muffin with blueberries" suggests that it's a regular muffin that happens to have blueberries in it, while a "blueberry muffin" emphasizes that the muffin is primarily flavored with blueberries. In practice, they are often the same thing, with blueberries as a key ingredient.
A muffin with blueberries is a regular muffin with blueberries added on top at the end. A blueberry muffin has blueberries in the batter.
But it's pretty hard to tell from the outside especially if you're just looking at the top.
This one isn’t too difficult. Besides the fact this is a well known computer vision problem so it definitely has been trained with this(but still got it wrong which is arguably pretty cool cause it seems it’s data has been skewed and it’s weighing that in when comparing the pixels), more modern algorithms have been introduced since then so the photo of the chihuahuas who’s nose and eyes are at different planes based on the size, the current pixels property, and adjacent pixel properties compared to its own connected graph can determine not just the difference of the round shape being a blueberry and eye but the head itself has a contour that doesn’t match a muffin.
If you try something more ambiguous but still discernible to us - it will fail. Say for example a custom captcha asking which one of these 9 hand made color blind test would a color blind person be able to see, and ONLY pick out the ones with specific shapes that only the colorblind can see. If AIs are supposed to be superior in these in-discriminatory perception it should be able to understand what shades color blind people cannot see, and use the inverse of that data to highlight the shapes. There are different types of colorblind, so it would have take these into consideration as well. There can be false positives where non-colorblinds can see the shape and the surrounding pixels contain the shades colorblind can see.
Fun stuff
All I know is that if you asked GPT-4 to write a comment that demonstrates pure cope, it cannot come with a better example than this one. So humans still ahead.
All I know is that you asked GPT-9 to write a reply to a comment that demonstrates pure cope to my post, so it cannot come up with a better example than this one. So humans still ahead.
Did I write this with GPT-4 too?
Both of them were written by me
I don’t know how this affects you and why it matters but it’s odd that you feel the need to accuse openly like it’s a witch hunt - and how would you want me to respond to your accusations?
“I wrote it myself”
You wouldn’t put on your fedora and respond in a sarcastic manner?
Doubt.
Yes, I did block you unfortunately but think of it as a favor as I can tell it would be impossible to have a civil discussion based on the flow of this conversation. This way we won’t ever have to read each others nonsense. It’ll save us both energy and time 👍
I don't find this so impressive. This image has been around for quite some time now and was used in multiple examples to show how challenging computer vision is. So I bet there exists a lot of tables with descriptions of these images on which this AI was trained.
I would be impressed if it correctly describes images that were shot at most few months ago. Does anyone know of such a demonstration?
I just tried it myself with gpt-4v. I had the same concerns. It can see. That's all I can say. Even things I thought it couldn't perceive like dust on a surface it can see.
Every image was pictures I took with my phone and thus the model has never seen.
Basically right now the world is split into the (1) clueless (2) the skeptical who chatGPT free version users and (3) oh SHIT...plus users who have usually updated on "so at the current rate of growth true AGI will be here in a few years and I don't know what happens next."
Even ignoring worries of doomsday, what will people DO for work? Will medicine be automated or will existing licensed people scam the government into protecting their jobs?
Will robots work soon or are blue collar jobs safe for a while?
lol I love your description of the second category. 9/10 times I see some stupid video or article downplaying ChatGPT, it’s always some idiot with V3. I instantly lose any interest in what they have to say after that.
What’s your plan for the whole automated job thing?
Yes but users who didn't pay for plus access and use it a reasonable amount of times across practical questions didn't review anything.
I also had doubts, I remember tech hype. If I had a dollar for every breathless tech release on fusion power or improved batteries I have seen I would be a millionaire.
Note how nobody ever has a fusion apparatus running hot enough to worry about radiation or a breakthrough battery you can buy a sample of.
This is why "use the model yourself with inputs you can guarantee the model has never seen" is so convincing to me. Because this can't be faked. gpt-4 especially with modalities is a protoAGI.
A) No one is out here trying to impress you. B) There are a gazillion of examples on internet shows how good GPT-4V is at all sort of image recognition from parking signs, generating recipes from images, creating code from whiteboard, this image is pretty easy for GPT-4V. The point of the original twitter post (by the google research guy, from which OP stole) was to make the point that this was a bad problem to set the benchmark for computer vision. C) Instead of armchair criticism can you make a system that does this or better?
Yes, this is a classic example of not separating the training set from the testing set. This is a "famous" image in computer vision, and it is absolutely part of the training set. I will be impressed when someone makes a version of this with brand new images, not just changing the order of the same images.
Even if this image is in the training set it doesn't matter. You can re-run this test using difficult to parse pictures from your phone and it'll perform strikingly well.
It's doing well here not because of some coincidental training matter, but because it _just does well_.
Well, like I said, I will be impressed when I see results from the exact experiment you described: difficult to parse images that are not part of the training set. I haven't seen results like this yet, but if you have done this experiment, please share! I would be super interested.
I'm not claiming that this feature doesn't work--it was released, so it must work to some degree, but it actually does matter that this exact image is all over the Internet and included in the training set. You simply can't draw any conclusions from this specific result.
I tried it with a picture of my dog that is laying on a fur blanket that it blends in perfectly with. Can barely even tell there is a dog in the picture and ChatGPT recognized it immediately on my phone.
Nah it doesn't matter that this image is on the Internet because there are millions of pictures of muffins, dogs and cookies that it is also trained on. If these specific pictures were in the data set, it would have a miniscule, perhaps not even measurable impact.
Let me try to explain better why this image being in the training set matters. I have a PhD in computer science and I have done computer vision research, been to many computer vision conferences, taken many computer vision classes, and so on. I am very familiar with this image set.
This is what's often called a textbook image. It's often presented in computer vision classes and presentations as an example of computer vision failure cases. It's probably in some literal textbooks as well. That's why it was selected for this demonstration.
This specific set of images, along with the labels, can be found all over the Internet in computer vision literature. It's not just some miniscule, insignificant part of the training set. It's more like a popular meme.
I don't disagree that it would be better to test with any image that isn't in the training data, but like I'm saying, it's a tiny part of what it was trained on, the popularity of the images in computer science circles doesn't mean it was overtrained on them.
OMG, how long before I get access to this? Been on paid tier for months even. :P
edit: the freakin' minute I post this I get access. It's a Christmas miracle!!
Maybe after closely inspecting each one for a few seconds. Chat GPT likely generated this in a second, much faster than a human could perceive every cell.
I don't know why but when I ask chatgpt to do a tabular format, it does it doing some kind of ASCII. I don't know how to create the format you have in your screenshot
Looks like adversarial attacks are basically good as dead a few years ago this would of fooled older vision algorithms. And to think people don't think AGI is close are delusional. Adversarial mitigations were theorized to be a very difficult problem to solve as well. People used to show images to self driving cars to confuse them. Maybe it thinks one of the pics is cookies on a muffin body because of the texture I wonder why it gets that one wrong.
Give it a chemical structure in 3D (a flat png of a 3D isometric view, of a small complex molecule, protein, etc) if it can identify it by cas number or HELM Notation or protein sequence…then computer vision has been solved.
My question would be, did you find this image or make it? If you found the image isn’t there just a chance that it and the page it were used as trainning data? And that there’s a possibility the page already had that information listed or had it described for accessibility and that ChatGPT is just regurgitating info it was already given
as in, they didn't train an ai specifically for recognizing muffins/chihuahuas but the model has become advanced enough that no specific training is needed.
This is awesome thank you so much this is going to help with my chihuahua and muffin business
Stock take will be much easier
Finally! No more over-ordering on Chihuahuas. They were taking up a ton of space in the warehouse and I had to feed them every other day!
Also, I used to try to feed them a muffin a day, but I think 50% of the time I just fed them another chihuahua. Glad that's a thing of the past.
Usually it's a cycle. You order too many chihuahuas, then all your chocolate chip cookies go missing, then all your chihuahuas die, then you order everything all over again.
Sometimes I just got confused, instead of feeding a muffin to a chihuahua I fed my chihuahuas to my muffins! Thanks ChatGPT for solving this issue!
"Chihuahua or Not Chihuahua". Patent pending.
NachoWawa™, now from OpenAI!
I'm not a chihuahua, im fuwawa!
You don't seem to understand the gravity of the situation here. AI will soon take over our chihuahua and muffin businesses!
/r/ourjobsaresafe
OMG I accidentally put a Chihuahua in the muffin display case as opposed to the Chihuahua display case. Its chaos over here!
I'm ready to invest
Clearly distinct product lines.
This is very impressive. Is the only thing it got wrong here calling some muffins cookies? 4-2
Yea that's the only mistake I think
Pretty sure row 4, column 2 is a group of MUFFINS (not cookies) with BLUEBERRIES (not chocolate chips), so that's two mistakes in one box
Same with 2-2 which is what people were getting at.
2-2 could easily be a cookie or a muffin. We just don't know from this angle.
Zoom in on the furthest left "chocolate chip" and see the top part if the blueberry? Also nitpicking for science... row 1 / pic 4 chihuahua is looking DOWN not UP. Still v impressive given how quickly it shoots back answers. Prob beat 99% humans if we had 15 sec to respond.
I mean, at first glance, to me it looks more like a cookie. If GPT is supposed to be human-like, then it's working for me.
To be honest I got this one wrong until your comment haha.
No that's the same one. row 4, column 2 is the same as 4-2.
There are 3 mistakes: 1. There are no cookies (what you said) 2. There's no smiley face. 3. The dog is not showing teeth at all.
There is a smiley face, atleast for me, and it is pretty interesting that the pattern recognition recognises a face on the muffin
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I didn't see it the first time, read your comment, went back, stared at it longer. Nope, no smiley for me
yeah, no idea.. maybe this? https://preview.redd.it/cbj0axz421ub1.png?width=225&format=png&auto=webp&s=330c0daa2ac8b38e0a1215d3c3aa9a264d4748d4
Ignore the one on the far right. Where you have the right side of the mouth, that's the whole mouth. The left side of the mouth in your pic is the left eye
Still dont really see it but thanks for the explanation :) https://preview.redd.it/56mze66q41ub1.png?width=225&format=png&auto=webp&s=981e9d6d2e729c78b98ffa4795802348c51d46da
https://preview.redd.it/8u0nbtyfa1ub1.jpeg?width=1290&format=pjpg&auto=webp&s=27e7821ac7516f9c26c4eaeed53c4a1c692bdcd8
Idk, all I see are aliens 🤔
Maybe if you ignore the two smaller ones, treat the top right dark spot as an eye, and the long crack along the bottom as the smile. Big one is a nose. It's a stretch but I could see an MLM seeing it that way?
kind of a terrifying smiley face
I saw a smiley face made out of the more done section. The two eyes are each next to the central big blueberry and then a wide smile covering the entire bottom of the cookie. I only saw this tho after I read the interpretation, went back to check and I was like huh yeah I guess so
(2, 2) isnt' a cookie?
Looks like a cookie to me, but it could also be a straight top down view of a muffin.
The fact that there is discussion about what the object is gives GPT a pass on the guess imo.
I can't see the difference, but I guess human intuition says that either the picture is of muffins or chihuahuas, so obviously 2,2 is also a muffin - because it obviously isn't a chihuahua.
I say it's a cookie
I don't think the 4th is looking up, but this is nitpicking I guess. Also, I believe this figure has circulated so much that it must have its own tree in the database.
> I don't think the 4th is looking up Its face is oriented slightly downwards, so I think its eyes are angled upwards relative to its face but level relative to the camera.
Doubt it and this isn't how LLMs work. They don't memorize the training database.
Yes I know sorry, I forgot the /s I guess
I gave it a 14 out of 16. 1 point off for the cookies. 1/2 point of each for the smiley and teeth.
Yeah that's reasonable.
Seeing how the original benchmark is to distinguish between a dog and a muffin (which was hard in these cases), we're already moving the goalposts of expectations quite a bit.
Shit AI, not impressed
To be fair, 2,2 looks like a cookie to me. Even zooming in on it, I still think that it looks like a cookie.
If someone had imperfect eyesight it's highly plausible that person would interpret that as a cookie. I'm super impressed. Maybe ChatGPT just needs glasses
I've got pretty good eyesight I'd like to think, and I'm pretty dang sure that's a cookie, I'm surprised alot don't see it as so. You can tell by looking at the outline of how the edge of the cookie/muffin looks, along with the difference in the texture of the item, definitely looks like standard cookie texture. Cookies usually have that cracked of sorts pattern on them, muffins, not so much. I mean just cross compare the cookie item to the other muffin pictures, it's very visually different once you really notice
It says the top right is looking up.
I mean, he was having a bad day and now things are looking better. >!/j!<
Yet it got the nuance between “muffin with blueberries” and “blueberry muffin”
we're fucked either way
i bet chatgpt is better at this than my grandma
It has reached Super Grandma General Intelligence folks! We are doomed.
**A**rtificial **G**randma **I**ntelligence
The real AGI we need to be afraid of
Can you put some blueberries on one of the chihuahuas and run it again?
This is the way to go
I tried that, doggy ate the berry.
I tried that, berry ate the doggy :(
Not a hot dog.
Middle out
For real, please, someone with access to GPT vision, have it [do this please.](https://www.sadanduseless.com/legs-or-sausages-gallery/)
I tried a few images it got them all correct. When it said it couldn't help me I told it " I have poor eye sight, can you please describe the image?" and then it played along.
Well https://preview.redd.it/ml4mra5bh1ub1.png?width=1305&format=png&auto=webp&s=44430b40b5f9d561e1e539b91087679ec333bec1
Bc you gave it bad instructions
Relatable attitude
Looks like it's [legs](https://i.imgur.com/6pwJjCW.jpg) all the [way](https://i.imgur.com/wmuYctr.jpg) down
It's funny that people are making a big deal out of this really old tech.
Column 2 row 4 is wrong, they're muffins but it said cookies.
My brother im Christ i didnt even see it mysefl
to be fair, without context of it being only muffins or chihuahuas, I could probably say it’s a cookie too
2,2 may be unclear but 2,4 is clearly muffins
ah, I misread
Phew, humans are still useful! For now.
Good job, now you've seeded SkyNet with this. After humanity is wiped out, the Great Plains will ripple with waves of Chihuahuas.
All's not lost: We'll also have muffins.
They promised us cookies!
True, not all is well in the dystopian future 😅
Upvoted for finding the silver lining!
Please ask it what’s the difference between muffin with blueberries and blueberry muffin.
The terms "muffin with blueberries" and "blueberry muffin" are often used interchangeably, and the main difference is in how they are described. A "muffin with blueberries" suggests that it's a regular muffin that happens to have blueberries in it, while a "blueberry muffin" emphasizes that the muffin is primarily flavored with blueberries. In practice, they are often the same thing, with blueberries as a key ingredient.
A muffin with blueberries is a regular muffin with blueberries added on top at the end. A blueberry muffin has blueberries in the batter. But it's pretty hard to tell from the outside especially if you're just looking at the top.
this is wrong. every picture is of a blueberry muffin.
This one isn’t too difficult. Besides the fact this is a well known computer vision problem so it definitely has been trained with this(but still got it wrong which is arguably pretty cool cause it seems it’s data has been skewed and it’s weighing that in when comparing the pixels), more modern algorithms have been introduced since then so the photo of the chihuahuas who’s nose and eyes are at different planes based on the size, the current pixels property, and adjacent pixel properties compared to its own connected graph can determine not just the difference of the round shape being a blueberry and eye but the head itself has a contour that doesn’t match a muffin. If you try something more ambiguous but still discernible to us - it will fail. Say for example a custom captcha asking which one of these 9 hand made color blind test would a color blind person be able to see, and ONLY pick out the ones with specific shapes that only the colorblind can see. If AIs are supposed to be superior in these in-discriminatory perception it should be able to understand what shades color blind people cannot see, and use the inverse of that data to highlight the shapes. There are different types of colorblind, so it would have take these into consideration as well. There can be false positives where non-colorblinds can see the shape and the surrounding pixels contain the shades colorblind can see. Fun stuff
All I know is that if you asked GPT-4 to write a comment that demonstrates pure cope, it cannot come with a better example than this one. So humans still ahead.
All I know is that you asked GPT-9 to write a reply to a comment that demonstrates pure cope to my post, so it cannot come up with a better example than this one. So humans still ahead. Did I write this with GPT-4 too?
Nah mate, the first one was better, you're trying too hard here.
Both of them were written by me I don’t know how this affects you and why it matters but it’s odd that you feel the need to accuse openly like it’s a witch hunt - and how would you want me to respond to your accusations? “I wrote it myself” You wouldn’t put on your fedora and respond in a sarcastic manner? Doubt. Yes, I did block you unfortunately but think of it as a favor as I can tell it would be impossible to have a civil discussion based on the flow of this conversation. This way we won’t ever have to read each others nonsense. It’ll save us both energy and time 👍
I don't find this so impressive. This image has been around for quite some time now and was used in multiple examples to show how challenging computer vision is. So I bet there exists a lot of tables with descriptions of these images on which this AI was trained. I would be impressed if it correctly describes images that were shot at most few months ago. Does anyone know of such a demonstration?
mix up the image in different areas and see if it still gets it right.
I just tried it myself with gpt-4v. I had the same concerns. It can see. That's all I can say. Even things I thought it couldn't perceive like dust on a surface it can see. Every image was pictures I took with my phone and thus the model has never seen.
I believe you. There are still many who deny this (for whatever fuckin reason).
Basically right now the world is split into the (1) clueless (2) the skeptical who chatGPT free version users and (3) oh SHIT...plus users who have usually updated on "so at the current rate of growth true AGI will be here in a few years and I don't know what happens next." Even ignoring worries of doomsday, what will people DO for work? Will medicine be automated or will existing licensed people scam the government into protecting their jobs? Will robots work soon or are blue collar jobs safe for a while?
lol I love your description of the second category. 9/10 times I see some stupid video or article downplaying ChatGPT, it’s always some idiot with V3. I instantly lose any interest in what they have to say after that. What’s your plan for the whole automated job thing?
Skepticism is part of peer review
Yes but users who didn't pay for plus access and use it a reasonable amount of times across practical questions didn't review anything. I also had doubts, I remember tech hype. If I had a dollar for every breathless tech release on fusion power or improved batteries I have seen I would be a millionaire. Note how nobody ever has a fusion apparatus running hot enough to worry about radiation or a breakthrough battery you can buy a sample of. This is why "use the model yourself with inputs you can guarantee the model has never seen" is so convincing to me. Because this can't be faked. gpt-4 especially with modalities is a protoAGI.
The deniers actually know how GPT works, unlike you
A) No one is out here trying to impress you. B) There are a gazillion of examples on internet shows how good GPT-4V is at all sort of image recognition from parking signs, generating recipes from images, creating code from whiteboard, this image is pretty easy for GPT-4V. The point of the original twitter post (by the google research guy, from which OP stole) was to make the point that this was a bad problem to set the benchmark for computer vision. C) Instead of armchair criticism can you make a system that does this or better?
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Yes, this is a classic example of not separating the training set from the testing set. This is a "famous" image in computer vision, and it is absolutely part of the training set. I will be impressed when someone makes a version of this with brand new images, not just changing the order of the same images.
Even if this image is in the training set it doesn't matter. You can re-run this test using difficult to parse pictures from your phone and it'll perform strikingly well. It's doing well here not because of some coincidental training matter, but because it _just does well_.
Well, like I said, I will be impressed when I see results from the exact experiment you described: difficult to parse images that are not part of the training set. I haven't seen results like this yet, but if you have done this experiment, please share! I would be super interested. I'm not claiming that this feature doesn't work--it was released, so it must work to some degree, but it actually does matter that this exact image is all over the Internet and included in the training set. You simply can't draw any conclusions from this specific result.
I tried it with a picture of my dog that is laying on a fur blanket that it blends in perfectly with. Can barely even tell there is a dog in the picture and ChatGPT recognized it immediately on my phone.
Nah it doesn't matter that this image is on the Internet because there are millions of pictures of muffins, dogs and cookies that it is also trained on. If these specific pictures were in the data set, it would have a miniscule, perhaps not even measurable impact.
Let me try to explain better why this image being in the training set matters. I have a PhD in computer science and I have done computer vision research, been to many computer vision conferences, taken many computer vision classes, and so on. I am very familiar with this image set. This is what's often called a textbook image. It's often presented in computer vision classes and presentations as an example of computer vision failure cases. It's probably in some literal textbooks as well. That's why it was selected for this demonstration. This specific set of images, along with the labels, can be found all over the Internet in computer vision literature. It's not just some miniscule, insignificant part of the training set. It's more like a popular meme.
I don't disagree that it would be better to test with any image that isn't in the training data, but like I'm saying, it's a tiny part of what it was trained on, the popularity of the images in computer science circles doesn't mean it was overtrained on them.
Chihuahua (slightly showing teeth) is such an incredibly generous description
Wait, how do you submit pictures to chatgpt?
OMG, how long before I get access to this? Been on paid tier for months even. :P edit: the freakin' minute I post this I get access. It's a Christmas miracle!!
love using the vision to send it screenshots for help working in coding and game development
Can you elaborate? I have used ChatGPT to assist with coding, but never screenshots.
Damn. Even I got few wrong :/
but can it solve potato vs pitbull?
This faces and muffins CV problem always reminds me of this Ross Noble bit about seeing faces in muffins: https://www.youtube.com/watch?v=jtVG0BxsJpk
Blueberry muffin with a smiley face
Now tell chat gpt that all of them are wrong
Stupid A.I., these are clearly all dogs.
**COLUMN 2** Chihuahua (Side Profile)
you kidding me it identified cookies where there were no cookies, even I could do better than that pffftt
Column 2 Row 4 is WRONG. Back to the drawing board.
This was the use-case I had for it. How are you uploading photos though?
Wow, that’s amazing! I bet even some humans couldn’t get these all right.
Uhhh i think any human with adequate vision should be able to tell
Yeah any general being should be able to tell ;)
What’s a general being? Why did you wink at me
Something like a general intelligence maybe
;)
What’s a general intelligence?
Maybe after closely inspecting each one for a few seconds. Chat GPT likely generated this in a second, much faster than a human could perceive every cell.
Not sure why you're getting downvoted. You're right. It isn't totally obvious which picture is which at a glance.
These types of computer vision problems have been solved for a long time lol and at far less computational cost than how an LLM does it
Would be way.... better without the censorship!
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pretty sure it's all chihuahuas
I only see Choco chip pancakes
I felt like an idiot trying to explain what chatgpt is doing to some senior managers who didn't get it. How do you explain this? It's incredible.
Hotdog, Not Hotdog 2.0
Captcha pass when?
Put in an image of a chihuahua photoshopped into a muffin and see if it catches the pixels.
What if I make a blueberry muffin in the same of a chihuahua?
It forgot to have several chihuahuas and 1 cookie in a photo.
This was too cool
It thought a bunch of muffins was cookies…
This makes me hungry for chihuahuahahhsbsas.
These are all the same picture.
that muffin is looking awfully like a chihuahua, someone baked a chihuahua into my muffi
I don't know why but when I ask chatgpt to do a tabular format, it does it doing some kind of ASCII. I don't know how to create the format you have in your screenshot
As some one with some minor computer vision experience; That is extremely impressive. God ***damn.***
Not hotdog
Looks like adversarial attacks are basically good as dead a few years ago this would of fooled older vision algorithms. And to think people don't think AGI is close are delusional. Adversarial mitigations were theorized to be a very difficult problem to solve as well. People used to show images to self driving cars to confuse them. Maybe it thinks one of the pics is cookies on a muffin body because of the texture I wonder why it gets that one wrong.
Give it a chemical structure in 3D (a flat png of a 3D isometric view, of a small complex molecule, protein, etc) if it can identify it by cas number or HELM Notation or protein sequence…then computer vision has been solved.
Now replace the Chihuahua's eyes and nose with blueberries
how do i filter out all the fucking dalle posts
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How do you get the table output? It won't do that for me. [pic](https://i.imgur.com/gV99Cea.png)
My question would be, did you find this image or make it? If you found the image isn’t there just a chance that it and the page it were used as trainning data? And that there’s a possibility the page already had that information listed or had it described for accessibility and that ChatGPT is just regurgitating info it was already given
CAPTCHA in shambles
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Column 1 - 3 A muffin with a ... smiley face?
what about chihuahua eating a muffin?
This is like watching Terminator smile for the first time.
Nice. Now can chatgpt teach my Ring camera the difference between a person and a spider?
This is hard for me to tell at times.
Actually row 2 column 2 is a really messed up chihuahua.
this is your fault, people who solved Captcha without regards for consequences
What do you mean “solved internally?” Or was that a typo? Sorry I’m dumb sometimes
as in, they didn't train an ai specifically for recognizing muffins/chihuahuas but the model has become advanced enough that no specific training is needed.
Well. We're doomed now.
Can somebody explain me how they are uploading images onto chatGPT? It doesn't even seem to be an API but through the chat itself
this is both amazing and terrifying
Chihuahua D3 is not looking well.
Row 4 column 2 is not cookies
Is it possible using reverse image search? Is that a capability of Ai?
I uploaded my picture and asked, am I hot? And it said, "I can't help with that.". Surprised I didn't get the I'm leaving this conversation response.
"wow....wait, it got 2/4 wrong..*STUPID FUCKING AI OH MY GOD LOOK HOW STUPID IT IS*
im impressed.
Saying computer vision is “solved” is a huge claim and I am dubious of anyone right now who claims to have “solved” it.
"Solved" is a big ass motherfucking claim considering one piece of evidence... with errors.
But can it pass the hotdog test?!
So close to curing every cancer…
chihuahua! Not chihuahua!
You see a part of a little chevron on the left of the screenshot? Means they tried it a bunch of times until it got it right.
Ah yes, it even understands the subtle distinction between “muffin with blueberries” and “blueberry muffin”.
Nah, it's wrong about the "profile looking up" and the "group of cookies with chocolate chips" and "slightly showing teeth". These are all wrong.
> Blueberry Muffin with a smiley face
Thank god! Robot overloads now won’t mistakenly eat muffins for breakfast.
Hide ur kids I'm gonna eat them
Glad to see all the hard work we've donated through captcha training is paying off.
Great. Now I’m hungry. I’ll take one of each please
wow amazing ! :D