AI Product Manager

Dr. Bart Jaworski
21 May 202208:32

Summary

TLDR本视频由Dr. Bob主讲,深入探讨了人工智能产品经理的角色与职责。AI产品经理是领域专家,负责引导团队构建最佳的AI服务解决方案。与通用产品经理不同,AI产品经理需要对算法和技术有深入理解,并能识别哪些项目适合应用AI技术。此外,他们还需具备出色的沟通能力,确保利益相关者理解AI的潜力与局限,并指导团队进行正确的数据收集与分析。Dr. Bob还强调了持续学习和评估解决方案的重要性。

Takeaways

  • 📚 AI产品经理是领域专家,负责引导团队构建最佳的AI服务解决方案。
  • 🎓 该职位要求深入的专业知识,通常需要达到博士水平,尤其是在深度学习和机器学习方面。
  • 🔍 AI产品经理需要了解不同的算法、技术和配置,以便为特定产品解决问题。
  • 🚀 成功的AI项目可能会极大提升产品性能,例如谷歌翻译通过使用机器学习提高了翻译准确性。
  • 🧠 作为专家,AI产品经理需要评估哪些项目值得投资,并准备好管理这些项目。
  • 📊 必须确保使用的数据集正确,并选择合适的指标来评估AI的效果。
  • 🛠️ AI产品经理应具备前瞻性,为团队和利益相关者提出最佳的AI实验和方法。
  • 💡 组织培训课程,提高公司对AI的认识,理解AI只是一种工具而非万能解决方案。
  • 🔄 每周评估现有解决方案,了解是否有更高效或更快速的方法,并保持对科学进展的了解。
  • 🔍 评估新的算法和技术,判断其是否适用于产品,是否能带来更好的结果。
  • 🌟 作为AI领域的专家,AI产品经理应不断提升自己的知识水平,确保在产品开发中发挥关键作用。

Q & A

  • AI产品经理与普通产品经理有何不同?

    -AI产品经理是某一领域的专家,他们使用自己的专业知识指导团队构建最佳的AI服务解决方案。与普通产品经理相比,AI产品经理不仅需要具备产品经理、项目经理和技术领导的能力,还必须对AI领域有深入的理解和专业知识。

  • AI产品经理需要具备哪些专业知识?

    -AI产品经理需要对不同的算法、技术和配置有深入的了解,能够根据特定问题选择最合适的解决方案,并具备将AI技术应用于产品以更好地服务客户和用户的能力。

  • AI产品经理在团队中扮演什么角色?

    -AI产品经理通常领导一个实验团队,这个团队独立于常规的产品路线图,以便产品不必依赖于实验结果。他们需要具备专业知识来指导团队构建产品、收集数据,并做出决策。

  • AI产品经理如何评估团队的进展和AI使用的数据集?

    -AI产品经理需要定义和选择用于评估数据集的指标,确保数据集的正确性,并建立警报系统以避免AI输出错误。

  • AI产品经理如何与利益相关者沟通?

    -AI产品经理需要与利益相关者沟通,让他们理解自己作为科学家的角色以及所进行的创新工作,同时明确AI不是万能的解决方案,而是一种可能需要投入大量时间和努力的工具。

  • AI产品经理如何确保团队使用正确的数据集?

    -AI产品经理需要确保团队使用正确、更新且完整的数据集,并建立警报系统以防止AI使用错误或过时的数据。

  • AI产品经理应如何处理AI项目的失败风险?

    -AI产品经理应该能够评估哪些AI项目值得投资,准备好接受失败,并从中学习,同时保持对新技术和算法的关注,以便不断优化产品。

  • AI产品经理如何提升自己的专业技能?

    -AI产品经理应该持续关注科学进步,学习新的算法和技术,以保持自己的专业知识处于行业前沿。

  • AI产品经理在推动AI项目时应该注意什么?

    -AI产品经理在推动AI项目时应该主动提出最佳的实验和方法,组织培训会议,提高公司对AI的理解,并确保AI的应用是可行且有效的。

  • AI产品经理如何平衡创新与实际应用?

    -AI产品经理需要在推动创新的同时,评估项目的可行性和实际效益,确保投入的资源能够得到合理的回报。

  • AI产品经理如何确保AI输出的准确性?

    -AI产品经理需要确保输入到AI系统的数据是准确和高质量的,同时定期检查和调整AI模型,以保持其输出的准确性。

Outlines

00:00

🤖 人工智能产品经理的角色与挑战

本段视频介绍了人工智能产品经理的职责和特点。人工智能产品经理是专业领域的专家,负责引导团队构建最佳的AI服务解决方案。与通用产品经理不同,AI产品经理需要具备深厚的专业知识,通常达到博士水平。他们不仅要掌握不同的算法和技术,还要能够识别哪些项目适合采用AI技术,并对项目的成功有预见性。此外,AI产品经理还需要领导实验团队,处理常规产品路线图之外的事务,并且能够处理AI项目的风险和不确定性。

05:02

🚀 如何成为一名优秀的人工智能产品经理

这一部分讨论了如何成为一名成功的AI产品经理。首先,沟通是关键,需要让利益相关者理解AI的创新性和可能的局限性。其次,作为团队的领导者,AI产品经理需要具备微观管理能力,指导团队构建产品、收集数据,并确保数据集的正确性和有效性。此外,AI产品经理需要设定评估标准,组织培训会议,提升公司对AI的理解,并且保持对科学进展的更新,以便在产品中应用新的算法和技术。最终,AI产品经理需要具备辨别科学论文真伪的能力,以确保尝试的AI解决方案是有价值的。

Mindmap

Keywords

💡人工智能产品经理

人工智能产品经理是指专门负责指导团队构建基于人工智能服务解决方案的产品管理专家。他们不仅需要具备产品经理、项目经理和技术领导的融合技能,而且通常需要在深度学习和机器学习等人工智能领域拥有博士学位级别的专业知识。

💡通用产品经理

通用产品经理是指那些负责管理产品从构思到市场推广整个过程的专业人员,与人工智能产品经理相比,他们可能不需要在特定技术领域拥有深入的专业知识。

💡专家

在视频中,专家是指在某一领域具有深厚知识和技能的人,特别是在人工智能领域,专家需要对算法、技术配置等有深入的理解和实践经验。

💡机器学习

机器学习是人工智能的一个分支,它使计算机能够通过数据和算法自动学习和改进。在产品管理中,机器学习可以用于解决各种问题,如提高翻译的准确性或优化推荐系统。

💡风险

在视频中,风险指的是在开发和实施人工智能项目时可能遇到的不确定性和潜在的失败。由于人工智能技术的复杂性和不断变化,产品经理需要评估哪些项目值得投资,哪些可能不会成功。

💡创新

创新在视频中指的是在产品开发和管理中引入新的想法、方法或技术,以提升产品性能或解决现有问题。对于人工智能产品经理来说,创新意味着利用AI技术为用户和客户提供更好的服务。

💡数据集

数据集是指用于训练和测试人工智能模型的一组数据。在视频中,正确的数据集对于构建有效的人工智能产品至关重要,因为数据质量直接影响到AI输出的准确性和可靠性。

💡沟通

沟通在视频中被视为人工智能产品经理成功的关键因素。有效的沟通能够帮助团队和利益相关者理解产品经理的工作,以及人工智能项目的创新性和潜在的风险。

💡实验团队

实验团队是指在产品开发过程中,专门负责尝试和测试新想法、新技术的团队。在视频中,人工智能产品经理通常会领导这样一个团队,以探索和验证AI技术在产品中的应用。

💡进步

进步在视频中指的是人工智能技术和产品管理实践的持续发展和改进。产品经理需要不断更新自己的知识,以便能够利用最新的算法和技术来提升产品性能。

💡效率

效率是指在完成特定任务时所投入的努力与产出之间的比率。在视频中,评估数据集的效率是人工智能产品经理的重要职责之一,以确保AI技术的有效运用和产品性能的最优化。

Highlights

AI产品经理是领域专家,使用待办事项列表指导团队构建最佳的AI服务解决方案。

AI产品经理与API产品经理类似,但需要成为深度学习和机器学习方面的绝对专家。

AI产品经理需要了解不同算法、技术和配置,以解决特定产品的问题。

AI产品经理往往需要承担高风险的项目,但也可能带来巨大的成功。

AI产品经理通常领导一个实验团队,这个团队独立于常规产品路线图。

谷歌翻译从以前的翻译模式转变为使用机器学习作为翻译引擎,准确度显著提高。

AI产品经理可以将现有产品通过AI进行改进,如使用机器学习为零售产品建立推荐系统。

作为AI产品经理,沟通是关键,需要让利益相关者理解AI的创新性和可能的局限性。

AI不是解决所有问题的万能钥匙,它只是一种可能的工具。

AI产品经理需要指导团队构建产品,收集数据,并做出决策。

AI产品经理需要评估团队的进展,并确保使用的数据集正确。

AI产品经理应能够定义指标,评估数据集的效率,并确保数据的正确性。

AI产品经理需要建立警报系统,以避免AI使用不完整或过时的数据。

AI产品经理应主动提出最佳的实验和方法,使用AI改进产品。

AI产品经理应组织培训,让公司了解AI及其进展。

AI产品经理需要保持与科学进展同步,以了解新算法和技术。

AI产品经理要判断科学论文的实际应用价值,决定是否尝试新解决方案。

Transcripts

play00:00

in today's video i'll tell you

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everything you need to know about ai

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artificial intelligence product managers

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how are they different from generalist

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product managers and what you need to

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know to excel at this role

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let's begin

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hi i'm dr bob and i'll be your product

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management teacher continuing the series

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of telling you about different types of

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product managers today we'll be looking

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at ai product managers as always let's

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start with the definition

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ai product manager is a subject level

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expert who uses backlog to guide a

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dedicated team to build best possible ai

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based services solutions this

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position this specialist is again pretty

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similar to an api product manager

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but here

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apart from being a merge of product

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manager project manager and a tech lead

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you have to be an absolute subject

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mother expert and that goes to a

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doctorate level very often and funny

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enough my doctorate comes from the area

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of ai which is not even the ai needed

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the ai used by the modern

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industry

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and i wouldn't be an ai product manager

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with my doctorate so

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it's very hard to find the actual niche

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of the deep learning machine learning

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experts who can grow into ai product

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managers and we either will get experts

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doctors for the university growing into

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the pm role or ai developers who will

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have that

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spark of product manager in them in

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order to grow into this specific role

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that translates into knowledge of

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different algorithms different

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techniques different configurations

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that can be used in any given problem

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and will be most likely to succeed in

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solving it for the specific product

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it's very difficult it will not always

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work and there's a lot of risk involved

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but you are the expert to well play your

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cards and see which efforts

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which ai projects are the best one to

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take for your company and product thus

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you have to also understand which

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projects can you take on which of them

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will make sense and have

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that innovation spark the initiative to

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propose how to use those ai

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aspects those ai technologies to

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better serve your clients and users

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the ai product manager will often lead

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an experimental

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team that's on the side of the regular

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roadmap so that the product doesn't have

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to rely on the results because they

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won't always be good and

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they won't always pan out the way it's

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planned but if they do they work

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brilliantly there was a case few years

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back where google translate switched

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from their previous mode of translating

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to one that uses

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machine learning

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as the

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foundation as the engine for translation

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and the results blew the mind the

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accuracy i believe of the english

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translations went from like 50 to 70 80

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90. i'll check again

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while i'm editing and put the numbers on

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the screen because it's something that

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came up to me when i started recording

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and i didn't plan to mention it but i

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think it's very very relevant which only

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shows that one of the projects an ai

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product manager can take is to take

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something that exists already and see

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whether it will perform better using ai

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and the data collected thus far for

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example in a retail product to

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use the machine learning for a

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recommendation system to suggest

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additional stuff to buy

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so

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how to excel as an ai product manager

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for one thing

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communication here will be the key

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your stakeholders need to understand

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that you are a scientist that you are

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doing something innovative and that it

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might not work ai is not a golden

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universal solution to any problem it's

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just a tool

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one of many that can be used and

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sometimes it will be

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successful in the end but it might take

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too much time too much effort to achieve

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and something simpler might as well work

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brilliantly

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very early on so

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a you shouldn't use that as a holy grail

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of development and as mentioned you need

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to decide whether something is worth

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investing in or not be ready to be that

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micromanaging product manager you will

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have to guide your team exactly on what

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they need to build how they need to

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build what data they need to collect

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this kind of stuff they will heavily

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rely on your expert level knowledge in

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the field and you make the calls

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obviously you have to also make sure

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that you teach them on the way but you

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are the head of this project

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you will need to evaluate whether the

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team is making progress

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and you also need to be there to make

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sure that the data set that the

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artificial intelligence is to be used is

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correct

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and

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choose metrics to use to evaluate them

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as well you need to be able to

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define metrics

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that will

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characterize the data set whether it's

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efficient or not and whether you always

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have the right data for the

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artificial intelligence

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you need to have alerting system so that

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the

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recommendations the output from ai

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doesn't use all data by accident or it's

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using data that's not being updated or

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is incomplete because then you will get

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mumbo jumbo and if the data the input is

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broken even if the ai engine is correct

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and it has been proven to work

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effectively

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it will start putting out

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nonsense if nonsense is put inside be

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proactive

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suggest to the team and stakeholders the

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best experiments the best approaches you

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can take in the product to use ai

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make sure you organize training sessions

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for the company so they know more about

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the ai more about the team or about the

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progress

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make it public and make people

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understand that ai can work but it can't

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it's just a tool and you are the expert

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in this particular tool and just like

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with other specialist product managers

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make sure to spend a little time each

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week to evaluate the solution you have

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whether it can work better or quicker

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but on top of that

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be sure to stay up to date with the

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progress of science so that you are on

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top of any new algorithms any new

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techniques that might appear

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and you

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can determine whether the

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solutions that appeared that have been

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described by scientists can be applied

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in your product can give you better

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results

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is it worth trying or is a scientific

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paper just

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paper written to help some scientists

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get his or her funding it's up to you to

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decide you are the expert that should

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know better and there you have it that's

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all i have for you for the ai product

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manager

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and remember a specialist product

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manager is someone on top of a regular

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product manager and to become a great

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product manager

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make sure to check out my courses on

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udemy skillshare the links are now

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on the screen and i'll see you in the

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next video

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see you then

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[Music]

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Related Tags
AI产品管理专家角色技术创新项目管理团队领导风险评估数据集优化沟通技巧持续学习行业应用
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