Share of notable AI systems by domain
What you should know about this indicator
- The authors of the Epoch dataset have established a set of criteria to identify key AI systems, which they refer to as notable. These systems must demonstrate the ability to learn, show tangible experimental results, and contribute advancements that push the boundaries of existing AI technology. In terms of notability, the AI must have garnered extensive academic attention, evidenced by a high citation count, hold historical significance in the field, mark a substantial advancement in technology, or be implemented in a significant real-world context. Recognizing the difficulty in evaluating the impact of newer AI systems since 2020 due to less available data, the authors also employ subjective judgment in their selection process for recent developments.
- 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.
- Drawing systems can create illustrations or sketches, either by mimicking human techniques or by generating unique art. Examples range from AI-generated artwork to design tools that can sketch based on user input or descriptions.
- The 'Other' category represents a diverse set of tasks, including 3D reconstruction, autonomous driving, video processing, text-to-video synthesis, search algorithms, audio processing, and robotics.
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Sources and processing
This data is based on the following sources
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All data and visualizations on Our World in Data rely on data sourced from one or several original data providers. Preparing this original data involves several processing steps. Depending on the data, this can include standardizing country names and world region definitions, converting units, calculating derived indicators such as per capita measures, as well as adding or adapting metadata such as the name or the description given to an indicator.
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Notes on our processing step for this indicator
For each year starting from 1950, the total number of AI systems in each domain was calculated by adding that year's count to the previous years' counts. This provides a running total or cumulative count of AI systems for each year and domain.
To streamline the categorization of domains, domain categories with less than a total of five notable AI systems since 1950 were grouped under the "Other" label. The aforementioned changes were implemented to make visualizations more coherent and concise.
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Citations
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To cite this page overall, including any descriptions, FAQs or explanations of the data authored by Our World in Data, please use the following citation:
“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 http://staging-site-fix-deleted-assets-in-cache/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 minor processing by Our World in DataFull citation
Epoch (2024) – with minor 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 June 14, 2024 from http://staging-site-fix-deleted-assets-in-cache/grapher/share-of-ai-systems-by-domain