variables: 935642

This table contains all the variables of all the datasets we have at Our World In Data. Note that this includes only the information about the variables like name and default display settings, not the data itself.

Data license: CC-BY

This data as json

id name unit description createdAt updatedAt code coverage timespan datasetId sourceId shortUnit display columnOrder originalMetadata grapherConfigAdmin shortName catalogPath dimensions schemaVersion processingLevel processingLog titlePublic titleVariant attributionShort attribution descriptionShort descriptionFromProducer descriptionKey descriptionProcessing licenses license grapherConfigETL type sort dataChecksum metadataChecksum
935642 Annual number of large-scale AI models by domain AI systems   2024-06-19 14:36:00 2024-07-08 16:32:09     2017-2024 6574     
{
    "unit": "AI systems"
}
 0     yearly_count grapher/artificial_intelligence/2024-06-19/epoch_compute_intensive_domain/epoch_compute_intensive_domain#yearly_count   2 major           Describes the specific area, application, or field in which a large-scale AI model is designed to operate. An AI system can operate in more than one domain, thus contributing to the count for multiple domains. The 2024 data is incomplete and was last updated 20 June 2024. A foreign key field categorizing the system’s domain of machine learning. This field links to the [ML Domains table](https://airtable.com/appDFXXgaG1xLtXGL/shrhzolGiQCVnwOY5/tbleYEsZORsiYRVTM), and domains are selected from the options in that table. 
[
    "Game systems are specifically designed for games and excel in understanding and strategizing gameplay. For instance, AlphaGo, developed by DeepMind, defeated the world champion in the game of Go. Such systems use complex algorithms to compete effectively, even against skilled human players.",
    "Language systems are tailored to process language, focusing on understanding, translating, and interacting with human languages. Examples include chatbots, machine translation tools like Google Translate, and sentiment analysis algorithms that can detect emotions in text.",
    "Multimodal systems are artificial intelligence frameworks that integrate and interpret more than one type of data input, such as text, images, and audio. ChatGPT-4 is an example of a multimodal system, as it has the capability to process and generate responses based on both textual and visual inputs.",
    "Vision systems focus on processing visual information, playing a pivotal role in image recognition and related areas. For example, Facebook's photo tagging system uses vision AI to identify faces.",
    "Speech systems are dedicated to handling spoken language, serving as the backbone of voice assistants and similar applications. They recognize, interpret, and generate spoken language to interact with users.",
    "Biology systems analyze biological data and simulate biological processes, aiding in drug discovery and genetic research.",
    "Image generation systems create visual content from text descriptions or other inputs, used in graphic design and content creation."
]
 The count of large-scale AI models AI systems per domain is derived by tallying the instances of machine learning models classified under each domain category. It's important to note that a single machine learning model can fall under multiple domains. The classification into domains is determined by the specific area, application, or field that the AI system is primarily designed to operate within.     
{
    "note": "Confirmed large-scale AI models are those where the training compute exceeds 10\u00b2\u00b3 floating-point operations (FLOP)."
}
 int 
[]
 a07f6379f050f1cc907e6c4d18672045 8228f7ba9faa49f912feaed25c47bac9

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