This section is about games initially designed for humans, but which ended up being used in AI development as well, e.g.:
- board games such as chess and Go
- video games such as Minecraft or old Video game console games
Allow us to determine with good approximation in a multi-electron atom which electron configuration have more energy. It is a bit like the Aufbau principle, but at a finer resolution.
Note that this is not trivial since there is no explicit solution to the Schrödinger equation for multi-electron atoms like there is for hydrogen.
For example, consider carbon which has electron configuration 1s2 2s2 2p2.
The by far dominating DNA sequencing company of the late 2000's and 2010's due to having the smallest cost per base pair.
To understand how Illumina's technology works basically, watch this video: Video 1. "Illumina Sequencing by Synthesis by Illumina (2016)".
Illumina Sequencing by Synthesis by Illumina (2016)
Source. The key innovation of this method is the Bridge amplification step, which produces a large amount of identical DNA strands.
The official page: www.image-net.org/challenges/LSVRC/index.php points to a download link on Kaggle: www.kaggle.com/competitions/imagenet-object-localization-challenge/data Kaggle says that the size is 167.62 GB!
To download from Kaggle, create an API token on kaggle.com, which downloads a The download speed is wildly server/limited and take A LOT of hours. Also, the tool does not seem able to pick up where you stopped last time.
kaggle.json file then:mkdir -p ~/.kaggle
mv ~/down/kaggle.json ~/.kaggle
python3 -m pip install kaggle
kaggle competitions download -c imagenet-object-localization-challengeAnother download location appears to be: huggingface.co/datasets/imagenet-1k on Hugging Face, but you have to login due to their license terms. Once you login you have a very basic data explorer available: huggingface.co/datasets/imagenet-1k/viewer/default/train.
ImageNet Large Scale Visual Recognition Challenge dataset Updated 2025-07-11 +Created 1970-01-01
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.There is a bug on that page however towards the middle:and there is one missing label if we ignore that dummy
n02119789: kit fox, Vulpes macrotis
n02100735: English setter
n02096294: Australian terriern03255030: dumbbell
href="ht:
n02102040: English springer, English springer spanielhref= 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 carchariasgist.github.com/aaronpolhamus/964a4411c0906315deb9f4a3723aac57 has lines of type:therefore numbered on the exact same order as image-net.org/challenges/LSVRC/2012/browse-synsets.php
n02119789 1 kit_fox
n02100735 2 English_setter
n02110185 3 Siberian_huskygist.github.com/yrevar/942d3a0ac09ec9e5eb3a lists all 1k labels as a plaintext file with their benchmark IDs.therefore numbered on sorted order of image-net.org/challenges/LSVRC/2012/browse-synsets.php
{0: 'tench, Tinca tinca',
1: 'goldfish, Carassius auratus',
2: 'great white shark, white shark, man-eater, man-eating shark, Carcharodon carcharias',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.txtn01440764 tench, Tinca tinca
n01443537 goldfish, Carassius auratus
n01484850 great white shark, white shark, man-eater, man-eating shark, Carcharodon carchariasImplosion-type fission weapons are more complicated than gun-type fission weapon because you have to precisely coordinate the detonation of a bunch of explosives.
Good film, it feels quite realistic.
It is a shame that they tried to include some particularly interesting stories but didn't have the time to develop them, e.g. Feynman explaining to the high school interns what they were actually doing. These are referred to only in passing, and likely won't mean anything to someone who hasn't read the book.
The film settings are particularly good, and give what feels like an authentic view of the times. Particularly memorable are the Indian caves shown the film. TODO name? Possibly Puye Cliff Dwellings. Puye apparently appears prominently up on another film about Los Alamos: The Atomic city (1952). It is relatively close to Los Alamos, about 30 km away.
The title is presumably a reference to infinities in quantum field theory? Or just to the infinity of love etc.? But anyways, the infinities in quantum field theory theory come to mind if you are into this kind of stuff and is sad because that work started after the war.
This is the order in which a binary search tree should be traversed for ordered output, i.e.:
- everything to the left is smaller than parent
- everything to the right is larger than parent
This ordering makes sense for binary trees and not k-ary trees in general because if there are more than two nodes it is not clear what the top node should go in the middle of.
This is unlike pre-order depth-first search and post-order depth-first search which generalize obviously to general trees.
The main interface between the central processing unit and software.
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