charts: 7665

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
7665 ai-performance-knowledge-tests-vs-parameters ScatterPlot 
{
    "id": 7665,
    "map": {
        "columnSlug": "737492"
    },
    "note": "The values for the number of parameters are estimates and come with some uncertainty, especially for models for which only minimal information has been disclosed.",
    "slug": "ai-performance-knowledge-tests-vs-parameters",
    "type": "ScatterPlot",
    "title": "Artificial intelligence: Performance on knowledge tests vs. number of parameters",
    "xAxis": {
        "max": 25000000000,
        "scaleType": "log",
        "canChangeScaleType": true
    },
    "yAxis": {
        "max": 100,
        "min": 0
    },
    "$schema": "https://files.ourworldindata.org/schemas/grapher-schema.004.json",
    "version": 63,
    "subtitle": "Performance on knowledge tests is measured with the [MMLU benchmark](#dod:ai-MMLU), here with 5-shot learning, which gauges a model\u2019s accuracy after receiving only five examples for each task. Parameters are variables in an AI system whose values are adjusted during training to establish how input data gets transformed into the desired output; for example, the connection weights in an artificial neural network.",
    "originUrl": "https://ourworldindata.org/artificial-intelligence",
    "colorScale": {
        "legendDescription": "Developer of AI system"
    },
    "dimensions": [
        {
            "property": "y",
            "variableId": 820642
        },
        {
            "property": "x",
            "variableId": 820640
        },
        {
            "property": "color",
            "variableId": 820643
        }
    ],
    "entityType": "system",
    "isPublished": true,
    "hideTimeline": true,
    "comparisonLines": [
        {
            "label": "Expert human performance",
            "yEquals": "90"
        },
        {}
    ],
    "entityTypePlural": "systems",
    "hideAnnotationFieldsInTitle": {
        "time": true
    }
}
 2024-03-01 16:33:59 2024-04-08 12:13:54 2024-03-15 14:00:27 2024-03-01 16:36:10 72 72 1 Artificial intelligence: Performance on knowledge tests vs. number of parameters Performance on knowledge tests is measured with the [MMLU benchmark](#dod:ai-MMLU), here with 5-shot learning, which gauges a model’s accuracy after receiving only five examples for each task. Parameters are variables in an AI system whose values are adjusted during training to establish how input data gets transformed into the desired output; for example, the connection weights in an artificial neural network. The values for the number of parameters are estimates and come with some uncertainty, especially for models for which only minimal information has been disclosed. Artificial intelligence: Performance on knowledge tests vs. number of parameters () 
{
    "$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": true,
    "colorScale": {
        "baseColorScheme": "default",
        "equalSizeBins": true,
        "binningStrategy": "ckmeans",
        "customNumericColorsActive": false,
        "colorSchemeInvert": false,
        "binningStrategyBinCount": 5
    },
    "scatterPointLabelStrategy": "year",
    "selectedFacetStrategy": "none",
    "isPublished": true,
    "invertColorScheme": false,
    "version": 63,
    "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": 7665,
    "note": "The values for the number of parameters are estimates and come with some uncertainty, especially for models for which only minimal information has been disclosed.",
    "slug": "ai-performance-knowledge-tests-vs-parameters",
    "title": "Artificial intelligence: Performance on knowledge tests vs. number of parameters",
    "subtitle": "Performance on knowledge tests is measured with the [MMLU benchmark](#dod:ai-MMLU), here with 5-shot learning, which gauges a model\u2019s accuracy after receiving only five examples for each task. Parameters are variables in an AI system whose values are adjusted during training to establish how input data gets transformed into the desired output; for example, the connection weights in an artificial neural network.",
    "originUrl": "https://ourworldindata.org/artificial-intelligence",
    "dimensions": [
        {
            "property": "y",
            "variableId": 820642
        },
        {
            "property": "x",
            "variableId": 820640
        },
        {
            "property": "color",
            "variableId": 820643
        }
    ],
    "comparisonLines": [
        {
            "label": "Expert human performance",
            "yEquals": "90"
        },
        {}
    ]
}

Links from other tables