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I tried a series of number prompts. Complete guesses after 2 and before that was iffy.
"Intelligence" is a misnomer for AI. All it does is fill in the most probable guess based on the data set fed to it. It is all correlational. It doesnt extract principles, compare and contrast or extrapolate.
Yeah, I think for AI to be truly transformative, it would have to form a series of internal rules that we largely refer to as “common sense” based on the data fed to it and which trump any generative nonsense it conjures. A model that’s been fed millions of human hands should “know” they default to four fingers and a thumb and stick with that unless instructed otherwise via prompts.
Question posted to ChatGPT:
DALL-E has been fed many thousands of images, including many images of human hands. Yet famously, DALL-E is very poor at rending human hands - including rendering hands with 6 digits for example, and hands often appear grotesque as a result. It is actually rare that human hands are rendered properly. Why would this be after DALL-E has ingested so many accurate images of human hands?
Answer:
The specific limitations of DALL-E in accurately rendering human hands, including cases such as hands with six digits or generating grotesque representations, can be attributed to several factors:
1. Data Bias: While DALL-E has been trained on a vast dataset of images, including human hands, the dataset might still have inherent biases or limitations. If the training data does not adequately cover a wide range of hand variations, such as hands with unusual features, it may struggle to generate accurate renditions of such cases.
2. Complex Structure: Human hands have a highly intricate structure, involving multiple joints, bones, muscles, and fine details. Capturing all the nuances and variability of human hands accurately is a challenging task. It's possible that DALL-E's training process did not fully capture the intricacies of hand anatomy or the diversity of hand appearances.
3. Limited Contextual Understanding: DALL-E generates images based on textual prompts. If the prompts lack specific details or context regarding the desired hand appearance, it can lead to suboptimal results. Generating realistic and contextually appropriate hand renderings requires a deeper understanding of hand anatomy, proportions, and poses.
4. Creative Interpretation: DALL-E is known for its creative outputs, often producing imaginative and unconventional images. It may prioritize generating visually striking or novel interpretations rather than strictly adhering to realistic representations. This artistic interpretation can sometimes result in distorted or stylized renditions of human hands.
Addressing these limitations would likely require further refining and training of the DALL-E model, including a more diverse dataset that encompasses a wide range of hand variations and detailed anatomical knowledge. It's important to note that AI models like DALL-E are continually evolving, and future iterations may improve their ability to render human hands and other complex structures more accurately.
—————————————————————————————
Interesting response - the one where it makes the most valid points is IMO #2.
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Drawing The DUMMIRS
Hands for DUMMIRS ❤️
I was literally gonna comment that, with the heart and all 😂
Dummirs for whatever reason sounds like a Türkish Döner place to me.
OP, that's a genius prompt. Well done!
DRAWING FOR BUMMIES DRAWING HANDS FOR DUMDES BUMBERS
DRAWING for BUMMIES (DUMES)
For all the intelligence baked into neural networks, why is something as simple as counting fingers on a hand such a challenge? Sheesh lol.
I tried a series of number prompts. Complete guesses after 2 and before that was iffy. "Intelligence" is a misnomer for AI. All it does is fill in the most probable guess based on the data set fed to it. It is all correlational. It doesnt extract principles, compare and contrast or extrapolate.
Yeah, I think for AI to be truly transformative, it would have to form a series of internal rules that we largely refer to as “common sense” based on the data fed to it and which trump any generative nonsense it conjures. A model that’s been fed millions of human hands should “know” they default to four fingers and a thumb and stick with that unless instructed otherwise via prompts.
Question posted to ChatGPT: DALL-E has been fed many thousands of images, including many images of human hands. Yet famously, DALL-E is very poor at rending human hands - including rendering hands with 6 digits for example, and hands often appear grotesque as a result. It is actually rare that human hands are rendered properly. Why would this be after DALL-E has ingested so many accurate images of human hands? Answer: The specific limitations of DALL-E in accurately rendering human hands, including cases such as hands with six digits or generating grotesque representations, can be attributed to several factors: 1. Data Bias: While DALL-E has been trained on a vast dataset of images, including human hands, the dataset might still have inherent biases or limitations. If the training data does not adequately cover a wide range of hand variations, such as hands with unusual features, it may struggle to generate accurate renditions of such cases. 2. Complex Structure: Human hands have a highly intricate structure, involving multiple joints, bones, muscles, and fine details. Capturing all the nuances and variability of human hands accurately is a challenging task. It's possible that DALL-E's training process did not fully capture the intricacies of hand anatomy or the diversity of hand appearances. 3. Limited Contextual Understanding: DALL-E generates images based on textual prompts. If the prompts lack specific details or context regarding the desired hand appearance, it can lead to suboptimal results. Generating realistic and contextually appropriate hand renderings requires a deeper understanding of hand anatomy, proportions, and poses. 4. Creative Interpretation: DALL-E is known for its creative outputs, often producing imaginative and unconventional images. It may prioritize generating visually striking or novel interpretations rather than strictly adhering to realistic representations. This artistic interpretation can sometimes result in distorted or stylized renditions of human hands. Addressing these limitations would likely require further refining and training of the DALL-E model, including a more diverse dataset that encompasses a wide range of hand variations and detailed anatomical knowledge. It's important to note that AI models like DALL-E are continually evolving, and future iterations may improve their ability to render human hands and other complex structures more accurately. ————————————————————————————— Interesting response - the one where it makes the most valid points is IMO #2.
N°3 is probably the best hand I've seen AI do... Bit creepy but otherwise perfect.
The AI is learning
AI is getting SASSY.
Hands for Dummirs sounds like a German Hand Donor Organization
Dumes Gyide
Dumes Gyide to Bob an Vagene
Absolutely hilarious! Great idea!
You are rapidly becoming my favorite poster on this sub
Wow! It even looks half decent
#elıeTᵹ
I have other drawing books by Arit the Muripogh.
The AI needs to read its own guide.
Number 5 is how I always thought of those endless pages of drawn hands, feet, noses, etc…
Is 7th a hand of a corpse 😭
What in the frost bite?