variables: 954428
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 |
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954428 | Total estimated investment - Field: Speech recognition | constant 2021 US$ | 2024-07-25 13:04:18 | 2024-07-30 06:18:28 | 2023-2023 | 6633 | $ | { "unit": "constant 2021 US$", "shortUnit": "$", "numDecimalPlaces": 0 } |
0 | estimated_investment_summary__field_speech_recognition | grapher/artificial_intelligence/2024-07-16/cset/cset#estimated_investment_summary__field_speech_recognition | { "filters": [ { "name": "field", "value": "Speech recognition" } ], "originalName": "Total estimated investment", "originalShortName": "estimated_investment_summary" } |
2 | Total estimated investment between 2013-2023. Only includes private-market investment flows, such as venture capital; excludes all investment in publicly traded companies, such as the "Big Tech" firms. This data is expressed in US dollars, adjusted for inflation. | [ "World aggregate does not include data for Micronesia, Tonga, Samoa, Kiribati, Fiji, Papua New Guinea, Palau, Tuvalu, Gibraltar, Jersey, Kosovo, Moldova, Isle of Man, Andorra, Montenegro, San Marino, Liechtenstein, Monaco, Vatican City, Afghanistan, Kyrgyzstan, Laos, Hong Kong, Bhutan, Brunei Darussalam, Maldives, Syria, North Korea, Myanmar, Timor-Leste, Nepal, Turkmenistan, Palestine, Yemen, Kuwait, Cape Verde, Equatorial Guinea, Swaziland, Namibia, Central African Republic (the), Angola, Ethiopia, Niger, Benin, Gabon, Gambia, Rwanda, Burkina Faso, S\u00e3o Tom\u00e9 and Pr\u00edncipe, Burundi, Guinea, Guinea-Bissau, Cameroon, Sierra Leone, Lesotho, Somalia, Chad, Liberia, Libya, South Sudan, Congo, Sudan, Malawi, Togo, Mali, Djibouti, Mauritania, Eritrea, Mozambique, Comoros, Antigua and Barbuda, Bolivia, Suriname, Nicaragua, Bahamas, Saint Vincent and the Grenadines, Grenada, Guyana, Haiti, Honduras, Cuba, Turks and Caicos Islands, Saint Lucia, and Dominica." ] |
- Reporting a time series of AI investments in nominal prices (i.e., without adjusting for inflation) means it makes little sense to compare observations across time; it is therefore not very useful. To make comparisons across time possible, one has to take into account that prices change (e.g., there is inflation). - It is not obvious how to adjust this time series for inflation, and we debated it at some length within our team. - It would be straightforward to adjust the time series for price changes if we knew the prices of the specific goods and services that these investments purchased. This would make it possible to calculate a volume measure of AI investments, and it would tell us how much these investments bought. But such a metric is not available. While a comprehensive price index is not available, we know that the cost for some crucial AI technology has fallen rapidly in price. - In the absence of a comprehensive price index that captures the price of AI-specific goods and services, one has to rely on one of the available metrics for the price of a bundle of goods and services. In the end we decided to use the US Consumer Price Index (CPI). - The US CPI does not provide us with a volume measure of AI goods and services, but it does capture the opportunity costs of these investments. The inflation adjustment of this time series of AI investments therefore lets us understand the size of these investments relative to whatever else these sums of money could have purchased. | { "note": "Data is expressed in constant 2021 US$. Inflation adjustment is based on the US Consumer Price Index (CPI). Data for 2022-2023 is incomplete." } |
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11d2f545a4e330c341321620f7c7edf4 | e14facbd6995dcc568d03c924f8133e3 |