Ciro Santilli @cirosantilli 37

14 million images with more than 20k categories, typically denoting prominent objects in the image, either common daily objects, or a wild range of animals. About 1 million of them also have bounding boxes for the objects. The images have different sizes, they are not all standardized to a single size like MNIST ^[ref].

Each image appears to have a single label associated to it. Care must have been taken somehow with categories, since some images contain severl possible objects, e.g. a person and some object.

In practice, the ILSVRC subset of ImageNet is the most commonly used dataset.

Official project page: www.image-net.org/

The data license is restrictive and forbids commercial usage: www.image-net.org/download.php. Also as a result you have to login to download the dataset. Super annoying.

How to visualize: datascience.stackexchange.com/questions/111756/where-can-i-view-the-imagenet-classes-as-a-hierarchy-on-wordnet

The categories are all part of WordNet, which means that there are several parent/child categories such as dog vs type of dog available. ImageNet1k only appears to have leaf nodes however (i.e. no "dog" label, just specific types of dog).

A major model that performed well on ImageNet starting on 2012 and became notable is AlexNet.

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A Hundred Birds Pay Homage to the Phoenix Updated 2025-07-16

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Video 1.

A Hundred Birds Pay Homage to the Phoenix with suona solo performed by Li Guangcai

. Source.

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AI accelerator Updated 2025-07-16

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Video 1.

The Coming AI Chip Boom by Asianometry (2022)

Source.

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AIDS Updated 2025-07-16

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AI game with natural language Updated 2025-07-16

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We define this category as AI games in which agents are able to produce or consume natural language.

It dawned on Ciro Santilli that it would be very difficult to classify an agent as an AGI if tthat agent can't speak to take orders, read existing human generated documentation, explain what it is doing, or ask for clarification.

Video 1.

Human player test of DMLab-30 Select Described Object task by DeepMind (2018)

Source. This is one of the games from DeepMind Lab.

Video 2.

WorldGPT by Nhan Tran (2023)

. Source. Not the most amazing demo, but it is a start.

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AI game world geometry Updated 2025-07-16

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Dragon Ball Z Updated 2025-07-16

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Although this was one of the children cartoons Ciro Santilli liked to watch, watching Dragon Ball Z as an adult feels like watching paint dry, everything takes forever! Apparently padding to sync with the manga: www.quora.com/Why-does-DBZ-drag-on-for-so-long The original Dragon Ball was likely strictly better, as it was much more fun and took itself less seriously. Also in DBZ power level inflation is taken to ridiculous levels. This is why One-Punch Man is good. Out of all evil characters, Frieza is one that made a big impression on Ciro, his graphical design is so good.

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ImageNet Large Scale Visual Recognition Challenge dataset Updated 2025-07-16

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Subset of ImageNet. About 167.62 GB in size according to www.kaggle.com/competitions/imagenet-object-localization-challenge/data.

Contains 1,281,167 images and exactly 1k categories which is why this dataset is also known as ImageNet1k: datascience.stackexchange.com/questions/47458/what-is-the-difference-between-imagenet-and-imagenet1k-how-to-download-it

www.kaggle.com/competitions/imagenet-object-localization-challenge/overview clarifies a bit further how the categories are inter-related according to WordNet relationships:

The 1000 object categories contain both internal nodes and leaf nodes of ImageNet, but do not overlap with each other.

image-net.org/challenges/LSVRC/2012/browse-synsets.php lists all 1k labels with their WordNet IDs.

n02119789: kit fox, Vulpes macrotis
n02100735: English setter
n02096294: Australian terrier

There is a bug on that page however towards the middle:

n03255030: dumbbell
href="ht:
n02102040: English springer, English springer spaniel

and there is one missing label if we ignore that dummy href= line. A thinkg of beauty!

Also the lines are not sorted by synset, if we do then the first three lines are:

n01440764: tench, Tinca tinca
n01443537: goldfish, Carassius auratus
n01484850: great white shark, white shark, man-eater, man-eating shark, Carcharodon carcharias

gist.github.com/aaronpolhamus/964a4411c0906315deb9f4a3723aac57 has lines of type:

n02119789 1 kit_fox
n02100735 2 English_setter
n02110185 3 Siberian_husky

therefore numbered on the exact same order as image-net.org/challenges/LSVRC/2012/browse-synsets.php

gist.github.com/yrevar/942d3a0ac09ec9e5eb3a lists all 1k labels as a plaintext file with their benchmark IDs.

{0: 'tench, Tinca tinca',
 1: 'goldfish, Carassius auratus',
 2: 'great white shark, white shark, man-eater, man-eating shark, Carcharodon carcharias',

therefore numbered on sorted order of image-net.org/challenges/LSVRC/2012/browse-synsets.php

The official line numbering in-benchmark-data can be seen at LOC_synset_mapping.txt, e.g. www.kaggle.com/competitions/imagenet-object-localization-challenge/data?select=LOC_synset_mapping.txt

n01440764 tench, Tinca tinca
n01443537 goldfish, Carassius auratus
n01484850 great white shark, white shark, man-eater, man-eating shark, Carcharodon carcharias

huggingface.co/datasets/imagenet-1k also has some useful metrics on the split:

train: 1,281,167 images, 145.7 GB zipped
validation: 50,000 images, 6.67 GB zipped
test: 100,000 images, 13.5 GB zipped

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