GPT-4o vs GPT-4: What's the difference?

Steal These Thoughts!
14 May 202405:08

Summary

TLDR本周科技界迎来了类似泰勒·斯威夫特演唱会的盛事,众多科技巨头发布了最新产品。OpenAI发布了改进版的Chat GPT模型,免费用户现在也能享受95%的优秀功能,付费计划的吸引力下降。视频中比较了新旧模型的性能差异,展示了新模型在简洁性、友好性和结构化方面的优势。作者推荐大家尝试新模型,无论是不是在L&D领域,都可能成为优秀的助手和教练。视频还提到了新模型的图像识别能力,并宣布自定义GPT在EMA的免费使用。

Takeaways

  • 🌟 本周技术社区举办了一场重要的活动,类似于泰勒·斯威夫特的演唱会,大家都在关注世界上最大的技术公司发布的最新产品。
  • 🚀 OpenAI,即聊天机器人GPT的创造者,举办了春季更新会议,推出了一个大幅改进的模型,并为免费用户提供了许多出色的功能。
  • 🆓 免费用户现在可以获得几乎所有GPT的出色功能,这使得付费计划不再那么吸引人。
  • 🔍 视频的重点是展示新旧GPT模型之间的性能差异。
  • 💻 API playground是许多开发者使用的平台,用户可以注册使用GPT API进行多种操作。
  • 📈 通过API playground展示新模型GPT-4.0与当前最佳模型GPT Turbo的性能对比。
  • 📝 视频作者建议非技术人士尝试使用免费版本的GPT,因为它可以作为一个出色的辅导工具和助手。
  • 📚 视频作者通过上传一张图表并询问GPT模型来测试它们的性能,比较了新旧模型的输出。
  • 📉 旧版GPT在描述图表时存在过度分享的问题,而新版GPT提供了更简洁、友好且结构清晰的输出。
  • 🎉 新版GPT在细节和总结方面做得更好,提供了更全面的信息,而不是仅仅部分列表。
  • 🔄 视频作者对GPT的新版本感到兴奋,并期待尝试其视觉、音频和语音功能。
  • 📲 由于新版本的发布,之前需要付费的定制GPT现在可以免费使用,作者在评论区留下了链接。

Q & A

  • 什么是生成式AI技术,它在技术社区中为什么如此重要?

    -生成式AI技术是一种可以创建新内容的人工智能技术,包括文本、图像、音频等。它在技术社区中非常重要,因为它代表了人工智能领域最新的创新和应用,能够极大地推动技术进步和行业发展。

  • OpenAI是什么,他们最近有什么重要的更新?

    -OpenAI是一个致力于开发和研究人工智能技术的组织,他们最近发布了一个春季更新,推出了一个大幅改进的模型,即Chat GPT的新版本,这个新模型为免费用户提供了许多优秀的功能。

  • 新旧版本的Chat GPT模型之间有什么性能差异?

    -新版本的Chat GPT模型提供了更加简洁友好的风格和更好的结构,而旧版本的模型则在某些情况下会有过度分享的问题,缺乏清晰的结构。

  • API playground是什么,它如何被开发者使用?

    -API playground是一个开发工具,许多开发者使用它来测试和使用Chat GPT的API。它允许用户进行多种不同的操作,即使非技术背景的人也可以注册使用。

  • 为什么新版本的Chat GPT模型对于免费用户来说更有吸引力?

    -新版本的Chat GPT模型为免费用户提供了几乎所有的优秀功能,这使得付费计划相比之下不再那么有吸引力,因为免费用户也能享受到大部分的高级功能。

  • 如何使用Chat GPT API进行图像识别测试?

    -用户可以上传一张图片到Chat GPT的API playground,并要求模型描述这张图片所展示的内容。通过比较新旧模型的输出,可以观察到它们在图像识别方面的差异。

  • 在图像识别测试中,新旧模型的输出有什么不同?

    -在图像识别测试中,新模型提供了更加简洁、友好的描述,并且给出了更详细的列表,而旧模型则在某些情况下会过度分享信息,缺乏重点。

  • 新版本的Chat GPT模型在哪些方面进行了改进?

    -新版本的Chat GPT模型在语言的简洁性、友好性、结构性方面进行了改进,提供了更加清晰和有用的输出,尤其是在处理图像识别和内容总结方面。

  • OpenAI的新版本Chat GPT模型是否支持视觉和音频能力?

    -是的,OpenAI的新版本Chat GPT模型预计将支持视觉和音频能力,这些功能将通过移动应用和Mac应用提供。

  • 如何免费使用定制的GPT进行性能咨询?

    -现在任何人都可以免费使用定制的GPT进行性能咨询。有兴趣的人可以通过在视频下方的评论中找到链接来参与。

  • 这段视频脚本的目的是为了什么?

    -这段视频脚本的目的是为了展示新旧Chat GPT模型之间的性能差异,并鼓励观众尝试使用新版本的模型,尤其是那些在L&D(学习与发展)领域或对AI技术感兴趣的人。

Outlines

00:00

🌟 技术社区的AI新动态

本周,技术社区迎来了类似泰勒·斯威夫特演唱会的盛况,每个人都对世界上一些最大的技术公司的最新发布感到兴奋。在生成性AI技术方面,OpenAI(Chat GPT的创造者)在春季更新会议上推出了一个显著改进的模型,为免费用户提供了许多出色的功能,这使得付费计划不再那么吸引人。免费用户现在可以获得几乎所有的优秀功能,即95%的优秀功能。视频中,作者通过API playground展示了新旧模型GPT 4.0与GPT turbo之间的性能差异。作者询问了关于大型语言模型的问题,并上传了一张图片,要求模型描述图片内容。新模型的回答更加简洁、友好,并提供了更好的结构。作者认为,新版本的Chat GPT是人们尝试使用的最佳模型,无论是在L&D世界还是其他领域,都推荐大家尝试使用。此外,作者还提到了对新模型的语音功能和视觉能力的期待,并邀请观众通过链接参与定制的GPT性能咨询。

05:01

📢 结尾提问与互动邀请

视频的结尾部分,作者邀请观众在评论区提出问题,并承诺在下一个视频中进行回答。这表明作者鼓励观众参与互动,并对观众的反馈和问题持开放态度,旨在建立一个积极的交流环境。

Mindmap

Keywords

💡技术社区

技术社区指的是由科技爱好者、开发者和专业人士组成的社区,他们共同讨论和分享技术相关的信息和知识。在视频中,提到技术社区对最新技术发布非常关注,类似于泰勒·斯威夫特的粉丝对她最新专辑的狂热。

💡生成式AI技术

生成式AI技术是一种人工智能技术,它能够生成新的数据,如文本、图像、音频等,而不仅仅是识别或分类现有数据。视频中提到,生成式AI技术是当前技术社区关注的焦点之一。

💡OpenAI

OpenAI是一个致力于人工智能研究和发展的非营利组织,它开发了包括Chat GPT在内的多种AI模型。视频中提到OpenAI发布了一个重大更新,推出了改进版的Chat GPT模型。

💡Chat GPT

Chat GPT是OpenAI开发的一种大型语言模型,能够理解和生成自然语言文本。视频中讨论了Chat GPT的新旧模型之间的性能差异,以及它们如何提供不同的用户体验。

💡API Playground

API Playground是一个交互式环境,开发者可以在这里测试和使用API(应用程序编程接口)。在视频中,API Playground被用来展示如何使用Chat GPT API,并比较新旧模型的性能。

💡GPT 4.0

GPT 4.0是视频中提到的新模型,它是Chat GPT的更新版本。与旧版本相比,GPT 4.0提供了更简洁、友好的回答风格和更好的结构。

💡GPT Turbo

GPT Turbo是视频中提到的当前最佳模型,直到新的GPT 4.0发布之前。它代表了Chat GPT在性能和功能上的高标准。

💡系统消息

系统消息是用户与大型语言模型交互时,系统提供给模型的指令或信息。在视频中,系统消息定义了模型应如何回应用户的问题,即作为一个友好的助手提供可信和简单的答案。

💡用户输入

用户输入指的是用户向系统提供的问题或指令。在视频中,用户输入是提出问题,要求模型解释大型语言模型的概念,以及识别上传的图像内容。

💡性能差异

性能差异指的是不同版本或模型在执行任务时表现上的不同。视频中通过比较GPT 4.0和GPT Turbo对同一问题的回答,展示了新旧模型在简洁性、友好性和结构上的差异。

💡自定义GPT

自定义GPT指的是根据特定需求或用途定制的GPT模型。视频中提到,现在任何人都可以免费使用之前需要付费的自定义GPT,用于特定的咨询领域,如EMA(欧洲管理咨询)。

Highlights

本周科技社区的盛事堪比泰勒·斯威夫特的演唱会,全球最大的科技公司发布了最新的产品。

OpenAI发布了春季更新,推出了改进版的Chat GPT模型,为免费用户提供了大量功能。

免费用户现在可以获得95%的Chat GPT的优秀功能,使得付费计划不再那么吸引人。

介绍了API playground,这是开发者和非技术用户都能使用的Chat GPT平台。

比较了新旧版本的GPT模型,以展示性能差异。

新版本的GPT提供了更简洁友好、结构更好的回答。

旧版本的GPT在回答时有些过度分享,缺乏结构。

上传了一张图表并让两个模型描述,比较了它们的输出。

旧GPT 4提供了详细的描述和总结,但有些过度解释。

新GPT 4模型的回答更简洁,提供了关键点和详细列表。

新GPT 4模型的回答更有助于下一步的工作考虑。

对新版本GPT的视觉和语音功能表示期待。

现在任何人都可以免费使用定制的GPT进行EMA的性能咨询。

视频旨在帮助理解技术的不同性能改进。

鼓励观众在评论区提出问题。

Transcripts

play00:00

Hello friends so for the non- Tey people

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out there this week for the tech

play00:05

Community is kind of like a serious

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Taylor Swift conferences where everyone

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is going crazy on latest releases from

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some of the world's biggest tech

play00:14

companies when it comes to generative AI

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technology now you haven't seen

play00:19

yesterday open AI the creators of chat

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GPT had their spring update conference

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where they launched a vastly improved

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model so they say to chat GPT and loads

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of really great capabilities for free

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users which actually makes the paid

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plans not so enviable anymore and free

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users are getting basically all of the

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great features I say 95% of the great

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features they're available with chat GPT

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but what I want to talk about is what is

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the performance difference between new

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models and old models so what you see on

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your screen here is the API playground

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on chat GP PT so this is what a lot of

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developers use for those of you in the

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non kind of tech lingo anyone can use

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this you can sign up to use the chat gbt

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API and do loads of different things on

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here so what I'm showing you on my

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screen is two things so I have got the

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new model of GPT

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40 versus GPT turbo which is the current

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best-in-class model until yesterday and

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the reason why I'm sharing this is that

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I think one the free version of chat GP

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right now as I speak is obviously the

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best model for people use to experiment

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with so whether you're in the L&D world

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or not I would definitely recommend that

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you check this out and use this

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certainly potential use cases in being a

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great tutor and assistant and helping

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you to coach through skills in

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particular but the point of this video

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is to kind of look at the incremental

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differences between the performance of

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the two models and the way that I can do

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this is this comparison here so new

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version of GPT old version of GPT

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basically what you're seeing here is the

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system message is what I told the large

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language model they were act as so

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they're a friendly assistant they're

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going to help answer questions with

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credible and simple answers the user

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input is me as a human asking a question

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so just did a really simple one my first

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question was explain a large language

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model to me as a non-technical person so

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from the new version of GPT we can see

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that we've got a little bit more of a

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succinct Style more of a friendly style

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and much better structure than if we

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look on the right hand side here with

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old kind of GPT and it does what I kind

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of call that oversharing piece doesn't

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give a lot of structure and I think that

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is quite interesting to see that just

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using a very natural language input

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we're already seeing the slight

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differences here in terms of the outputs

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which I quite like and then the second

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test is I uploaded a image from a recent

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report and I just said to each of the

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models tell me what this image is

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showing so we can compare the outputs

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here now I didn't think there was a huge

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amount of difference here but it was

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definitely some things that I enjoyed

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versus the other so on the old GPT 4

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what we can see is that you we've got

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the description to say where this side

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is from what is it showing we have got

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all of the structure which is very nice

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and we've got a summary here as well

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what I didn't like on this side here is

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the oversharing piece again so

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reaffirming what these components mean

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that might be great for some people but

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I am not looking for that what I liked

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on the new GPT 4 model is again very

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succinct very friendly I like the

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structure here where it's saying key

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areas where AI is not being included it

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gave me the full list not just a p of a

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list that was here so a bit more detail

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which was fantastic and it really hit to

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the the key core of that slide and then

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what I really liked here is the kind of

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a summary but really just some notes

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that I can consider and help me out with

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any kind of next piece of work that I'm

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trying to do so again I'm not using this

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from a Content creation perspective very

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much looking at this as a full partner

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this is a very simple test but gives you

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a glimpse into the little nuances and

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improvements between the two models of

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course there'll be more experimentation

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I am very excited to try out more of the

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vision capability ities and audio

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capabilities or voice capabilities I

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should say Via Mobile and the Mac App

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what the new releases also mean is that

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any of you who were not able to use my

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custom GPT for performance Consulting in

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EMA can now use that for free so anyone

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who wants to engage with that can and

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I'll leave a link in the comments below

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so look a little bit different than the

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usual but I hope that's helpful to

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understand the different performance

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impr improvements in terms of the

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technology that is available today any

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questions drop them below and I will

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talk to you in the next

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