charts: 5881

This table contains the information used by our Grapher datavisualisation tool to render charts.

The most relevant field is the config field that contains json stored as text. A JSON Schema is available that describes the content of this json data. The SQLite JSON_EXTRACT function can be used in SQL queries to extract the content of this JSON data into columns in a result table.

Data license: CC-BY

This data as json

id slug type config createdAt updatedAt lastEditedAt publishedAt lastEditedByUserId publishedByUserId isIndexable title subtitle note title_plus_variant configWithDefaults
5881 artificial-intelligence-number-training-datapoints ScatterPlot 
{
    "id": 5881,
    "map": {},
    "slug": "artificial-intelligence-number-training-datapoints",
    "type": "ScatterPlot",
    "title": "Datapoints used to train notable artificial intelligence systems",
    "xAxis": {
        "label": "Publication date"
    },
    "yAxis": {
        "label": "Training datapoints",
        "scaleType": "log",
        "canChangeScaleType": true
    },
    "$schema": "https://files.ourworldindata.org/schemas/grapher-schema.004.json",
    "version": 182,
    "subtitle": "Each domain has a specific data point unit; for example, for vision it is images, for language it is words, and for games it is timesteps. This means systems can only be compared directly within the same domain.",
    "originUrl": "http://ourworldindata.org/artificial-intelligence",
    "colorScale": {
        "baseColorScheme": "owid-distinct",
        "binningStrategy": "manual",
        "legendDescription": "Task domain",
        "customCategoryLabels": {
            "games": "Games",
            "speech": "Speech",
            "vision": "Vision",
            "No data": "Other",
            "driving": "Driving",
            "general": "General",
            "language": "Language"
        }
    },
    "dimensions": [
        {
            "property": "y",
            "variableId": 953910
        },
        {
            "property": "color",
            "variableId": 953913
        }
    ],
    "entityType": "system",
    "isPublished": true,
    "entityTypePlural": "systems",
    "hideAnnotationFieldsInTitle": {
        "time": true,
        "entity": true,
        "changeInPrefix": true
    }
}
 2022-07-10 11:38:33 2024-07-17 16:46:47 2024-07-17 16:46:47 2022-12-01 13:42:53 74 48 1 Datapoints used to train notable artificial intelligence systems Each domain has a specific data point unit; for example, for vision it is images, for language it is words, and for games it is timesteps. This means systems can only be compared directly within the same domain.   Datapoints used to train notable artificial intelligence systems () 
{
    "$schema": "https://files.ourworldindata.org/schemas/grapher-schema.004.json",
    "map": {
        "projection": "World",
        "hideTimeline": false,
        "colorScale": {
            "baseColorScheme": "default",
            "equalSizeBins": true,
            "binningStrategy": "ckmeans",
            "customNumericColorsActive": false,
            "colorSchemeInvert": false,
            "binningStrategyBinCount": 5
        },
        "timeTolerance": 0,
        "toleranceStrategy": "closest",
        "tooltipUseCustomLabels": false,
        "time": "latest"
    },
    "maxTime": "latest",
    "baseColorScheme": "default",
    "yAxis": {
        "removePointsOutsideDomain": false,
        "scaleType": "linear",
        "canChangeScaleType": false,
        "facetDomain": "shared"
    },
    "tab": "chart",
    "matchingEntitiesOnly": false,
    "hasChartTab": true,
    "hideLegend": false,
    "hideLogo": false,
    "hideTimeline": false,
    "colorScale": {
        "baseColorScheme": "default",
        "equalSizeBins": true,
        "binningStrategy": "ckmeans",
        "customNumericColorsActive": false,
        "colorSchemeInvert": false,
        "binningStrategyBinCount": 5
    },
    "scatterPointLabelStrategy": "year",
    "selectedFacetStrategy": "none",
    "isPublished": true,
    "invertColorScheme": false,
    "version": 182,
    "logo": "owid",
    "entityType": "system",
    "facettingLabelByYVariables": "metric",
    "addCountryMode": "add-country",
    "compareEndPointsOnly": false,
    "type": "ScatterPlot",
    "hasMapTab": false,
    "stackMode": "absolute",
    "minTime": "earliest",
    "hideAnnotationFieldsInTitle": {
        "entity": false,
        "time": false,
        "changeInPrefix": false
    },
    "xAxis": {
        "removePointsOutsideDomain": false,
        "scaleType": "linear",
        "canChangeScaleType": false,
        "facetDomain": "shared"
    },
    "hideConnectedScatterLines": false,
    "showNoDataArea": true,
    "zoomToSelection": false,
    "showYearLabels": false,
    "hideLinesOutsideTolerance": false,
    "hideTotalValueLabel": false,
    "hideScatterLabels": false,
    "sortBy": "total",
    "sortOrder": "desc",
    "hideFacetControl": true,
    "entityTypePlural": "systems",
    "missingDataStrategy": "auto",
    "id": 5881,
    "slug": "artificial-intelligence-number-training-datapoints",
    "title": "Datapoints used to train notable artificial intelligence systems",
    "subtitle": "Each domain has a specific data point unit; for example, for vision it is images, for language it is words, and for games it is timesteps. This means systems can only be compared directly within the same domain.",
    "originUrl": "http://ourworldindata.org/artificial-intelligence",
    "dimensions": [
        {
            "property": "y",
            "variableId": 953910
        },
        {
            "property": "color",
            "variableId": 953913
        }
    ]
}

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