Share of notable AI systems by domain
What you should know about this indicator
- 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.
- Recommendation systems offer suggestions based on user preferences, prominently seen in online shopping and media streaming. For instance, Netflix's movie suggestions or Amazon's product recommendations are powered by algorithms that analyze users' preferences and past behaviors.
- Audio systems process and generate sound, with applications in music composition, signal processing, and sound recognition.
- 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.
- Robotics systems combine AI with mechanical engineering to create autonomous robots for various industries.
- Video systems analyze and generate video content, aiding in editing, surveillance, and content creation.
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Sources and processing
This data is based on the following sources
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Notes on our processing step for this indicator
The count of notable 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. System domains with less than 10 systems are grouped under "Other."
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“Data Page: Share of notable AI systems by domain”, part of the following publication: Charlie Giattino, Edouard Mathieu, Veronika Samborska and Max Roser (2023) - “Artificial Intelligence”. Data adapted from Epoch. Retrieved from https://ourworldindata.org/grapher/share-of-ai-systems-by-domain [online resource]How to cite this data
In-line citationIf you have limited space (e.g. in data visualizations), you can use this abbreviated in-line citation:
Epoch (2024) – with major processing by Our World in DataFull citation
Epoch (2024) – with major processing by Our World in Data. “Share of notable AI systems by domain” [dataset]. Epoch, “Parameter, Compute and Data Trends in Machine Learning” [original data]. Retrieved December 11, 2024 from https://ourworldindata.org/grapher/share-of-ai-systems-by-domain