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打破GenAI的7个神话实现可操作的影响.pptx

上传人: 王** 编号:171066 2024-07-23 18页 38.96MB

1、 2024 Domino Data Lab,Inc.1 2024 Domino Data Lab,Inc.1Shatter the 7 Myths of GenAI to Operationalize ImpactDomino Data LabMay 8th,2024Kjell Carlsson,PhD 2024 Domino Data Lab,Inc.2 2024 Domino Data Lab,Inc.2Kjell Carlsson,phdHead of AI Strategy Domino Data LabHost of the Data Science Leaders PodcastS

2、elect GenAI episodes:(10/4)James Cham,Bloomberg BetaUnlocking the disruptive potential of generative AI(13/3)Rahul Todkar,TripadvisorAI Will Plan Your Next Vacation:GenAI at Tripadvisor(12/2)Brandon Allgood,FogPharmaDisrupting Drug Discovery&Development with AI(19/1)Rowan Curran,ForresterShattering

3、the Myths of Gen AI(3/1)Mikhail Korolev,BoltMore Human Than Human?GenAI Customer Service(6/12)Peter Wang,AnacondaThe State and Future of Generative AI:Reflections on the Anniversary of ChatGPTThe Tech Executives Primer On Data Science,ML,And AIAI 2.0:Upgrade Your Enterprise With Five Next-Generation

4、 AI AdvancesForrester Wave:Notebook-Based Predictive Analytics&MLForrester Wave:Multimodal Predictive Analytics&MLIntroducing ModelOps To Operationalize AIQ&A:Scale AI With Automated Machine LearningShatter The Seven Myths Of Machine LearningThe Forrester New Wave:Computer Vision PlatformsNew Tech:E

5、nterprise Computer Vision SolutionsAll Enterprises Need(Computer)VisionThe Future Of Machine Learning Is UnstoppableAugmented Intelligence Unlocks The Intelligence in AIForrester New Wave:AI-Fueled Speech Analytics SolutionsBest Practices:Scaling Data Science Across The EnterprisePreviously:Principa

6、l Analyst Forrester 2024 Domino Data Lab,Inc.3 2024 Domino Data Lab,Inc.3Transformative,real-world GenAI successes existDrug DiscoveryCustomer ServiceProductivityNone of them fit the conventional wisdom on GenAI!Note:Images generated using Midjourney 2024 Domino Data Lab,Inc.4 2024 Domino Data Lab,I

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本文由Domino Data Lab发布,主题为“破除7大关于生成式人工智能(GenAI)的迷思,实现影响力操作”。作者Kjell Carlsson博士,是Domino Data Lab的AI战略负责人,也是Data Science Leaders Podcast的主持人。文章指出,尽管存在关于GenAI的迷思,但实际上已经存在通过GenAI实现药物发现、客户服务、提高生产率等领域的转型性成功案例。文章提出了GenAI影响深远的7大核心特征,包括由经验丰富的领导带领、专家数据科学家团队开发、完善的AI产品开发流程、利用广泛的GenAI和ML技术生态、先进的MLOps能力等。同时,文章预测,将有90%的GenAI项目未能实现变革性的价值。作者强调,破除关于GenAI的迷思,实现对AI的真实影响至关重要。
哪些误解需要打破?" "如何实现生成式AI的实际应用?" 哪些真相你不得不知?"
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