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wiki:ai_timelines:ai_inputs:recent_trends_in_ai_investment [2023/04/04 17:36]
rickkorzekwa [Additional figures] |
wiki:ai_timelines:ai_inputs:recent_trends_in_ai_investment [2023/07/13 22:59] (current)
rickkorzekwa Fixed dollar signs |
| ====== Recent trends in funding for AI companies ====== | ====== March 2023 Recent trends in funding for AI companies ====== |
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| //Published 29 March, 2023; Last updated 3 April, 2023// | //Published 29 March, 2023; Last major updated 3 April, 2023// |
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| | //13 July, 2023 update: Since the last major update for this page, several AI companies have received large investments, including \$1.3B for Inflection AI, \$500M for SandboxAQ, \$450M for Anthropic, \$350M for Adept AI, \$300M for OpenAI, \$270M for Cohere, and \$150M for character.ai.// |
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| //For broader, but less up to date analysis, see [[ai_timelines:ai_inputs:funding_of_ai_research|Funding of AI Research]].// | //For broader, but less up to date analysis, see [[ai_timelines:ai_inputs:funding_of_ai_research|Funding of AI Research]].// |
| Funding for AI companies over the past five years has been a departure from the longer-term trend, which showed rapid, sustained growth, as shown in figures 3 and 4. | Funding for AI companies over the past five years has been a departure from the longer-term trend, which showed rapid, sustained growth, as shown in figures 3 and 4. |
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| [{{:wiki:ai_timelines:ai_inputs:annual_money_raised_since_1990.png?600|Figure 3: Annual funding for AI companies (blue bars) and all software companies (red line) since 1990. The vertical axis is on a logarithmic scale. Source: Crunchbase}}] | [{{:wiki:ai_timelines:ai_inputs:annual_money_raised_since_1990.png?600|Figure 3: Annual funding for AI companies (blue bars) and all software companies (red line) since 1990. The vertical axis is on a logarithmic scale. For 2023, the values are scaled based on the rate of funding so far, so they show what funding for the full year will be if it continues to accumulate at the same rate. Source: Crunchbase}}] |
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| [{{:wiki:ai_timelines:ai_inputs:total_money_raised_since_1990.png?600|Figure 4: Cumulative funding for AI companies (blue bars) and all software companies (red line) since 1990. The vertical axis is on a logarithmic scale. Source: Crunchbase}}] | [{{:wiki:ai_timelines:ai_inputs:total_money_raised_since_1990.png?600|Figure 4: Cumulative funding for AI companies (blue bars) and all software companies (red line) since 1990. The vertical axis is on a logarithmic scale. Source: Crunchbase}}] |
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| - For companies included in the [[https://gcrinstitute.org/papers/055_agi-2020.pdf|2020 Survey of Artificial General Intelligence Projects for Ethics, Risk, and Policy]] from GCRI((McKenna Fitzgerald, Aaron Boddy, and Seth D. Baum, 2020. 2020 Survey of Artificial General Intelligence Projects for Ethics, Risk, and Policy. Global Catastrophic Risk Institute Technical Report 20-1.)), we checked Crunchbase for recent funding rounds. Of the 72 projects included in the survey, 24 were associated with private companies and 11 of those had received funding since 2018. Three companies (Optimizing Mind, ORBAI, and FutureAI) had not been included in the original Crunchbase query, because they had not met the $3M cutoff. | - For companies included in the [[https://gcrinstitute.org/papers/055_agi-2020.pdf|2020 Survey of Artificial General Intelligence Projects for Ethics, Risk, and Policy]] from GCRI((McKenna Fitzgerald, Aaron Boddy, and Seth D. Baum, 2020. 2020 Survey of Artificial General Intelligence Projects for Ethics, Risk, and Policy. Global Catastrophic Risk Institute Technical Report 20-1.)), we checked Crunchbase for recent funding rounds. Of the 72 projects included in the survey, 24 were associated with private companies and 11 of those had received funding since 2018. Three companies (Optimizing Mind, ORBAI, and FutureAI) had not been included in the original Crunchbase query, because they had not met the $3M cutoff. |
| - To identify influential AI labs, we searched the [[https://paperswithcode.com/methods|Methods page]] on Papers with Code for machine learning methods that had been used in at least 400 publications. If one of the authors for the publication introducing the method had a private company as an institutional affiliation, that company was added to a list. This resulted in 15 companies or organizations within companies, which was then filtered to exclude any that had not received private funding since 2018, leaving only one (SenseTime). | - To identify influential AI labs, we searched the [[https://paperswithcode.com/methods|Methods page]] on Papers with Code for machine learning methods that had been used in at least 400 publications. If one of the authors for the publication introducing the method had a private company as an institutional affiliation, that company was added to a list. This resulted in 15 companies or organizations within companies, which was then filtered to exclude any that had not received private funding since 2018, leaving only one (SenseTime) that was not already included in our list of notable labs. |
| - Finally, we added companies that are known to us to be major players in AI development, or that commonly appear in lists of companies advancing the state of the art in AI. Only three such companies had recent funding data on Crunchbase, and had not already been included for other reasons (Cruise, Darktrace, and Stability AI). | - Finally, we added companies that are known to us to be major players in AI development, or that commonly appear in lists of companies advancing the state of the art in AI. Only three such companies had recent funding data on Crunchbase, and had not already been included for other reasons (Cruise, Darktrace, and Stability AI). |
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