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1、Artificial Intelligence&Machine Learning OverviewIndustry and taxonomy update with latest VC activityEMERGING TECH RESEARCH2023Published April 10,2023REPORT PREVIEWThe full report is available through the PitchBook Platform.Contents2023 Artificial Intelligence&Machine Learning OverviewCONFIDENTIAL.N
2、OT FOR REDISTRIBUTION.PG 2PublishingReport designed by Julia Midkiff and Joey Schaffer Published on April 10,2023Institutional Research Group AnalysisDataMatthew Nacionales Data AnalystBrendan Burke Senior Analyst,Emerging Technology Vertical overview3VC activity5AI&ML landscape6AI&ML VC ecosystem m
3、arket map7Segment overview11Horizontal platforms12Vertical applications17Autonomous machines23AI&ML semiconductors26Appendix 312023 Artificial Intelligence&Machine Learning OverviewCONFIDENTIAL.NOT FOR REDISTRIBUTION.PG 5AI&ML landscape$3412Horizontal platforms Vertical applications SemiconductorsAu
4、tonomous machines24132023 Artificial Intelligence&Machine Learning OverviewCONFIDENTIAL.NOT FOR REDISTRIBUTION.PG 7VC activity2022 challenged the highly funded AI vendors that are unlikely to drive the fields future.VC funding for the vertical declined more than for IT overall,falling 34.9%in VC dea
5、l value to$78.0 billion.The median venture growth valuation step-up declined below the overall VC median,to 1.3x,demonstrating the prevalence of flat rounds and outlying down rounds faced by leading vendors such as Dataiku and Noodle.ai.As with global IT,2022 deal value exceeded 2020s total.Deal cou
6、nt also declined more than for IT,at 13.2%,as early-stage deal count regressed even as late-stage deal count remained high.The sector experienced deal count declines of over 50%in autonomous vehicles,processor design,automation platforms,and intelligent sensors as investors avoided hardware-and labo
7、r-intensive businesses.Consumer AI proved to be the most resilient vertical application,declining only 20.5%in VC funding year-over-year,as consumer interest in AI applications emerged.VC exit count continued to decline in Q4,though deal value rebounded due to significant listings in China.We tracke
8、d$7.0 billion in VC exit value in Q4up from Q3,but the second-lowest value we have tracked since Q2 2020.Exit count has remained above pre-pandemic levels.Among tech giants,active acquirers included Meta,Oracle,and Spotify.PE found opportunities in generative AI,with growth equity PSG using generati
9、ve copywriting startup Copywriter AI as a platform to add on two writing startups in Frase and Rytr,forming a new platform called Copyrytr.This platform play gives an early look at the synergies of generative AI startups as they proliferate in different use cases.AI copywriting leader Jasper has als
10、o become an acquirer as part of the companys strategy to deliver a unified content suite across formats.Source:PitchBook|Geography:Global|*As of December 31,2022Median AI&ML VC pre-money valuation step-up by stage1.8x1.8x2.6x2.3x2.0 x2.0 x1.7x1.3x0 x0.5x1.0 x1.5x2.0 x2.5x3.0 x20122013201420152016201
11、720182019202020212022*Angel and seedEarly-stage VCLate-stage VCVenture growth2023 Artificial Intelligence&Machine Learning OverviewCONFIDENTIAL.NOT FOR REDISTRIBUTION.PG 8Source:PitchBook|Geography:Global|*As of December 31,2022Q4 2022 AI&ML VC deal activity by segment*$961.8$2,572.2$2,539.1$8,027.4
12、4865222601AI&ML semiconductorsAutonomous machinesHorizontal platformsVertical applicationsDeal value($M)Deal countVC ACTIVITYSource:PitchBook|Geography:Global|*As of December 31,2022TTM AI&ML VC deal activity by segment*$3,699.8$9,371.6$15,679.5$45,821.91862917982,273AI&ML semiconductorsAutonomous m
13、achinesHorizontal platformsVertical applicationsDeal value($M)Deal count2023 Artificial Intelligence&Machine Learning OverviewCONFIDENTIAL.NOT FOR REDISTRIBUTION.PG 17Vertical applicationsOverviewVertical applications in AI&ML address specific problems within industries and are not always AI first.M
14、any startups in this category design a solution to an industry problem using software and integrate AI&ML to optimize some part of their product.These solutions typically differentiate based on the quality of the dataset used to train the industry-specific model and the industry expertise of the dat
15、a scientists identifying decision-making areas that can be enhanced by AI&ML models.As a result,many of these startups help automate specific functions within their industry but have limited ability to cross apply their AI&ML to other industries.Current subsegments include:AI&ML in financial service
16、s:Includes technologies that embed AI&ML into existing financial services via advanced analytics,process automation,robo-advisors,and self-learning programs.Product categories include financial chatbots,intelligent banking,lending analytics,payment optimization,predictive underwriting,and robo-advis
17、ors.AI in healthcare:Includes technologies that leverage AI&ML to improve medicine and the provision of care.Product categories include AI-based drug discovery,clinical decision support,genetic analytics,healthcare administration,and personal health.Consumer AI:Includes technologies that use AI&ML t
18、o enhance B2C business models.Product categories include AI in media&entertainment,AI&ML advertising technology,digital avatars and gaming,e-commerce recommendation engines,education technology,intelligent price optimization,and smart retail.Industrial AI&ML:Includes technologies that automate indus
19、trial processes and unlock industrial data to find new efficiencies.Product categories include crop maximization,energy grid automation,geospatial analysis,heavy industry automation,IoT predictive analytics,supply chain optimization,and telecommunications optimization.AI in IT:Includes enterprise so
20、ftware tools that optimize specific functions typically administered by IT departments,including both back-end and front-end use cases.Product categories include human resource automation,information security(infosec)automation,IT infrastructure management,legal automation,property technology,sales&
21、marketing automation,and software development tools.AI in transportation:This category includes intelligent fleet management and driver assistance.It excludes autonomous vehicles.Industry driversGrowing availability of industrial datasets:Startups can build preliminary models based on data and frame
22、works from sources including Google Dataset Search,Kaggle,UCI Machine Learning Repository,Microsoft Coco,and GitHub.Governments support data sharing,as evidenced by President Bidens Executive Order on Enhancing Safeguards for United States Signals Intelligence Activities.5 This order codifies the EU
23、-US Data Privacy Framework for secure data sharing for AI training.Enterprise customers are achieving ROI with AI solutions:McKinseys State of AI survey found that over 40%of AI adopters in service operations,manufacturing,human resources,risk management,and sales&marketing achieved cost savings as
24、a result of their AI projects in 2021.6 Only around 50%of these adopters reported cost savings the prior year.5:“Executive Order on Enhancing Safeguards for United States Signals Intelligence Activities,”The White House,October 7,2022.6:“The State of AI in 2022and a Half Decade in Review,”McKinsey I
25、nstitute,December 6,2022.2023 Artificial Intelligence&Machine Learning OverviewCONFIDENTIAL.NOT FOR REDISTRIBUTION.PG 34APPENDIXSource:PitchBook|Geography:Global|*As of December 31,2022AI&ML VC deal value($M)by stage$0$20$40$60$80$100$120$14020122013201420152016201720182019202020212022*Venture growt
26、hLate-stage VCEarly-stage VCAngel and seedSource:PitchBook|Geography:Global|*As of December 31,2022AI&ML VC deal count by stage01,0002,0003,0004,0005,0006,0007,0008,00020122013201420152016201720182019202020212022*Venture growthLate-stage VCEarly-stage VCAngel and seedAbout PitchBook Emerging Tech Re
27、searchIndependent,objective and timely market intelAs the private markets continue to grow in complexity and competition,its essential for investors to understand the industries,sectors and companies driving the asset class.Our Emerging Tech Research provides detailed analysis of nascent tech sector
28、s so you can better navigate the changing markets you operate inand pursue new opportunities with confidence.2023 by PitchBook Data,Inc.All rights reserved.No part of this publication may be reproduced in any form or by any meansgraphic,electronic,or mechanical,including photocopying,recording,tapin
29、g,and information storage and retrieval systemswithout the express written permission of PitchBook Data,Inc.Contents are based on information from sources believed to be reliable,but accuracy and completeness cannot be guaranteed.Nothing herein should be construed as any past,current or future recom
30、mendation to buy or sell any security or an offer to sell,or a solicitation of an offer to buy any security.This material does not purport to contain all of the information that a prospective investor may wish to consider and is not to be relied upon as such or used in substitution for the exercise
31、of independent judgment.Additional researchEric Bellomo Gaming E-CommerceBrendan Burke Internet of Things Information Security Artificial Intelligence&Machine LearningAaron DeGagne Medtech Digital HealthAlex Frederick Agtech FoodtechJonathan Geurkink Supply Chain Tech Mobility TechDerek Hernandez Sa
32、aSAli Javaheri Emerging SpacesRobert Le Web3/DeFi Insurtech CryptoJohn MacDonagh Carbon&Emissions Tech Clean Energy TechRebecca Springer Healthcare Services Healthcare ITRudy Yang FintechComing soon Biotech PharmatechPitchBook Data,Inc.John Gabbert Founder,CEONizar Tarhuni Vice President,Institution
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