Demoing the most innovative new ChatGPT features with Sunny Madra and Vinny Lingham | E1732

发布时间 2023-05-01 23:58:17 来源

摘要

(0:00) Jason kicks off the show (2:06) ChatGPT's new code interpreter (9:24) OpenPhone - Start your free trial and get 20% off at ⁠https://openphone.com/twist (10:58) ChatGPT's Code Interpreter example with EV data (23:50) Coda - Get a $1,000 startup credit at ⁠https://coda.io/twist (25:13) The global GPU shortage (28:10) ChatGPT's Code Interpreter example with US Bank Failures (31:19) How ChatGPT will change the modern-day organization (38:55) Release - Get your first month free at ⁠https://release.com/twist (40:27) Getting more efficient with ChatGPTs new updates (47:53) Web browsing with ChatGPT (56:11) How this technology will enable people (1:04:15) How this has impacted Sunny Subscribe to This Week in Startups on Apple: https://rb.gy/v19fcp Check out Waitroom: https://waitroom.com/ Check out Definitive: https://definitive.io/ FOLLOW Sunny: https://twitter.com/sundeep FOLLOW Vinny: https://twitter.com/vinnylingham FOLLOW Jason: https://linktr.ee/calacanis Thanks to our partners: (9:24) OpenPhone - Start your free trial and get 20% off at ⁠https://openphone.com/twist (23:50) Coda - Get a $1,000 startup credit at ⁠https://coda.io/twist (38:55) Release - Get your first month free at ⁠https://release.com/twist Listen here: Apple: https://podcasts.apple.com/us/podcast/this-week-in-startups-audio/id315114957 Spotify: https://open.spotify.com/show/6ULQ0ewYf5zmsDgBchlkr9 Overcast: https://overcast.fm/itunes315114957/this-week-in-startups-audio More from us: Twitter: https://twitter.com/twistartups Instagram: https://www.instagram.com/twistartups Official site: https://thisweekinstartups.com Subscribe to our YouTube to watch all full episodes: https://www.youtube.com/channel/UCkkhmBWfS7pILYIk0izkc3A?sub_confirmation=1 Subscribe to TWiST Clips for all the best moments: https://www.youtube.com/channel/UCS7tJlcUA6PzVHEMo-X7ddg?sub_confirmation=1 #startups #entrepreneurship #investing #angelinvesting #tech #news #business

GPT-4正在为你翻译摘要中......

中英文字稿

Hey, everybody, welcome back to this week in startups. We're doing another AI roundtable. And this is the best one ever, Vinny and Sunny join me again to demo chat GPT's new code interpreter. This was just released on Friday. We're playing with it over the weekend and we're gonna play with it here on the show.

大家好，欢迎回到《本周创业》节目。我们继续进行人工智能圆桌讨论。这次是最棒的一次，Vinny和Sunny再次加入我，演示Chat GPT的新代码解释器。它在上周五刚刚发布。我们在周末玩弄它，现在我们要在节目中演示。

We take a random couple of CSVs that we grabbed off government websites. We uploaded to chat GPT and it takes this and acts like a data scientist and it starts doing analysis of these documents. It's incredible magic. Make sure you listen to this episode with your teams because at your startup, you're probably wasting tens of thousands of dollars that this new tool is going to remove from your expenses.

我们随便选了一对从政府网站上下载的CSV文件。我们将它们上传到聊天GPT中，然后它会像一个数据科学家一样开始分析这些文档。这是一种不可思议的魔法。请确保和你的团队一起听这个节目，因为在你的初创公司中，你可能正在浪费数万元，而这个新工具将从你的开支中删除这些费用。

These rapid innovations AI are going to change the world. I've been talking about it multiple times per week here on this week in startups and on the all in podcast. I think people are gonna become 30% more efficient this year. But, but Sunny thinks I'm wrong. He thinks it's 300% or more. We get into it. I show you a bunch of details of some GPT stuff I did over the weekend and some stuff I'm doing in Python on a Replet. It's gonna be a great show. You might even blow your mind, stick with us.

这些快速创新的人工智能将改变世界。我已经在这个周刊和“全芯”播客中多次谈到它。我认为人们今年将变得更高效，提升30％。但是，Sunny认为我错了。他认为增长率会达到300％或更多。我们深入探讨了这个问题。我向你展示了我在周末做的一些GPT工作，以及我在Replet上用Python进行的一些工作细节。这将是一场精彩的节目。你甚至可能惊奇地发现我们的讨论。请跟随我们。

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本周创业公司由Open Phone赞助。Open Phone将您团队的业务电话、短信和联系人整合到一个令人愉悦的应用程序中，可在任何地方使用。在OpenPhone.com/twist上注册，您可以享受首六个月20%的优惠。

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Coda是专门为团队打造的全能工具集。如果你使用了许多有限的工作流程工具，或者迷失在许多应用和电子表格中，Coda可以帮助你整合所有工具，让你更加高效。现在，通过在coda.io/twist上注册，你可以获得1000美元的创业信用额度。对于SaaS初创公司来说，大型企业提出了独特的挑战。使用release delivery，即可免去自主设计和管理私有、独立的网络托管的麻烦，为有独特需求的客户解决问题。现在，前往release.com/twist注册即可享受首月免费优惠。

Hey everybody, welcome to another episode of this week in startups with me again, Vinny Lingham and Sunny Sundeep, Madra. We were doing a crypto round table, boys and AI has taken over all of our lives. Crypto still seems like an important technology but it does feel like the amount of energy putting into being put into AI startups, language models is 100x or 1000x what's happening in crypto.

大家好，欢迎来到本周创业的另一个节目。我是Vinny Lingham和Sunny Sundeep，Madra。今天我们将进行一个加密圆桌讨论。现在，人工智能已经占据了我们生活的所有领域。虽然加密货币仍然是一项重要的技术，但它似乎吸引的关注度远远不及人工智能创业公司和语言模型，它们所消耗的能量大约是加密货币的100至1000倍。

So we'll skate to where the puck is going and continue our discussions about AI here. So this is our weekly AI round table. You have ideas for the producers here. Producers at this week in startups.com if you see something interesting, say something, email producers at thisweekinstartup.com.

因此，我们会滑到冰球去的地方，并在这里继续我们关于人工智能的讨论。这就是我们每周的人工智能圆桌会议。如果你有给制作人的想法，可以在本周创业.com联系他们。如果你看到有趣的东西，记得说一声并发送电子邮件至[email protected]。

All right, so let's get right into it. You shared a link with us, Sunny, on the group chat that some chat GPT users now have access to a code execution or code interpreter plugin. What is this and why is it important? Yeah, so this is really, really big and what chat GPT hasn't enabled, open AI has enabled is the ability for the interface to run code and what's interesting and you can now input data via an upload feature. So one of the really cool examples that people are doing this week and as was just released on Friday, just go show you the paces that you can take a spreadsheet.

好的，让我们开始吧。Sunny在群聊中与我们分享了一个链接，说一些聊天GPT用户现在可以访问代码执行或代码解释器插件。这是什么以及为什么它很重要呢？是的，这非常重要，聊天GPT还没有实现的是，OpenAI已实现了接口运行代码的功能，并且你可以通过上传功能输入数据。人们本周正在做的一件非常酷的事情之一是，正如上周五发布的那样，你可以使用它处理电子表格。

That spreadsheet can have data in it. You can upload it and then you can basically have a chat GPT do some basic data science for you. And so it's really, you know, the process to do that before would have been to, you know, go get a data scientist or write a Python program and so it does all of this in line in a very similar way to how we saw the plugins work. We're seeing that now for, you know, running code. And that code interpreter, if you were to just do a Google search right now for, if you do a Google search for chat GPT and you go into chat GPT on the drop down you see, especially if you're paying the default, which is 3.5 version of chat GPT GPT 4 and then you'll see some other things. Like GPT 3.5 with browsing, which is an alpha GPT 4 with browsing that's an alpha and then code interpreter, which is marked as alpha.

这个电子表格可以包含数据。您可以上传它，然后基本上可以让聊天GPT为您进行一些基本的数据科学。所以它真的很不错，之前需要做的工作是去找数据科学家或者编写Python程序，现在它可以在线完成，就像我们看到插件工作的方式一样。我们现在看到它可以用于运行代码。如果您现在搜索聊天GPT，然后在下拉菜单中选择聊天GPT，特别是如果您选择默认的3.5版本，您会看到GPT 4等其他选项。例如GPT 3.5 with browsing，这是一个alpha版本，还有一个带浏览的GPT 4 alpha版本和标记为alpha的代码解释器。

And you see this all in the drop down menu. And if you happen to have applied to the plugins, which I applied to and I've been using and I got my team on, you'll see plugins alpha. I think paying for a chat GPT the 20 bucks a month, we'll get it there. So is code interpreter available to everybody, do you know? I think it's only available to those folks that have plugins enabled, which means that they've been allowed into this very limited beta or alpha group that are kind of developer or centric or people that are real publishing stuff to the community to help educate everyone. So it's not widely available yet.

你可以在下拉菜单中看到所有这些内容。如果你也申请了我使用和我的团队也在使用的插件，你会看到插件alpha。我认为支付20美元一个月的聊天GPT，我们会得到它。你知不知道，代码解释器是否对所有人都可用？我认为它只对那些启用了插件的人可用，这意味着他们被允许进入这个非常有限的beta或alpha组，这些人是真正发布内容来帮助教育所有人的开发者或中心人物。因此，它还没有普及。

Got it. And so an example of this might be what? And this is stuff you might ask a data scientist to do and Google Sheets or Excel previously or to query an SQL database or something.

明白了。那么，请问这的一个例子是什么？这些都是你可能会请数据科学家在Google表格或Excel中完成，或者查询SQL数据库等任务。

Exactly, that's normally how someone would deal with it. Yeah. So inside your organization, Vinny, people are like, oh, we got this Google Sheet. Oh, we exported our Google Analytics. Oh, we downloaded some data. We got some client data. We've got, we exported something from Salesforce or whatever tool we're using. Now the team has to go find somebody smart who is either in the accounting department, the data science department or it just happens to be good at hacking this stuff together. And this is something that civilians, the other 80% of people who work at a company just don't know how to do. It would be too hard for them to do. You have that experience, I guess, in your startups as well, Vinny?

没错，那通常是人们处理这种问题的方法。嗯。Vinny，你们的组织内部，人们会像这样说：哦，我们有一个谷歌表格。哦，我们导出了我们的谷歌分析数据。哦，我们下载了一些数据。我们有一些客户数据。我们从Salesforce或其他工具中导出了一些东西。现在团队必须去找到一个聪明的人，他可能在会计部门、数据科学部门，或者只是擅长拼凑这些东西。这是民用人员所不知道的，公司工作80%的人都不知道如何做。他们做起来会太难。在你的初创公司中，你也有这样的经验，对吗，Vinny？

Yeah, I mean, it's definitely a lot easier to, I mean, the barriers to using data science right now is coming down by the day. Yeah, this is where it's democratizing data science. Like I've got a friend who's a data scientist and you know, I invest in his company and he's been using data science models for years. And like, it's just, I think it's a game changer for them. I mean, some of the data science companies out there right now, they tried to ridiculous amounts of money. I mean, we're talking like millions and millions of dollars to do data science for companies and there's some big businesses out there. I think one's data dog, I think, and there's a couple others. And opening eye and chat to PT is basically reduced the ability to do this to, you know, it's a means enterprise individuals can do it.

是的，我的意思是，使用数据科学现在变得越来越容易了。这就是数据科学民主化的地方。我有一个朋友是数据科学家，我投资了他的公司，他已经使用数据科学模型多年了。我认为这对他们来说是一场革命。目前有一些大数据公司，他们为企业提供数据科学服务，需要支付巨额费用，有些甚至需要数百万美元。但是，开放的技术和平台，如PT，使得个体和企业能够使用数据科学，使得这项技术变得更加普及和民主化。

What I think is interesting though, on a slight deviation here is Google has got access to so much company data to the Google suite. So if you like to run a startup and you're on Google, Google Drive, you know, Google Docs, Google Docs, Google Sheets, everything, that information is incredibly powerful. So now Google just need to take part and say, we'd like to activate BOD on your company documents and then create like, you know, obviously, to figure out the privacy stuff and, you know, rights, I mean, but basically you have access to DOS. I've already been done in an organization, right? Like generally speaking, the organization should have set their permission. So, well, so just keep this in mind, right? If BOD starts learning across the company, it needs to be able to partition the knowledge and not infer information.

我认为有趣的是，Google可以访问大量公司数据，并将其整合到Google套件中。因此，如果你正在使用Google挑战创业，通过Google Drive、Google 文档、Google 表格等等，这些信息将非常有用。因此，Google只需要参与并说：“我们想在您的公司文件中激活BOD（机器学习算法），然后创建像——和——这样的东西，当然，需要解决隐私和权利问题，但基本上您可以访问DOS（数据操作系统）。一般情况下，组织应该设置他们的权限，而这已经在一些组织中完成了。因此，需要注意的是，如果BOD开始跨公司学习，它需要将知识划分开，不得推断出信息。

Sure. That only you have access to. So if I'm the HR department and I've got a bunch of documents that only the HR departments are and then somebody in sales does a query, hey, how much do we pay our people internally and what's their compensation? You don't want that coming up in the results. Exactly.

肯定。只有你有权限访问这些文件。所以，如果我是人力资源部门，我有一堆只有人力资源部门才有的文件，然后销售部门的某个人查询，嘿，我们内部员工的薪资是多少，他们的补偿是多少？你不想让这些结果出现。确切地说。

So that is an important permission issue. Yes, but, but, but if you're the CEO, you should have, you know, do you have access to something? Do you have access to anything? Or do you have access to something? And what about like if J.Kell's got a private Doc Sheets in there that no one else actually, are you allowed to see that or? Of course, I mean, the organization owns it. This is like a fallacy that some employees have that. I'm paying corporate account. Yeah. I agree to. Yeah. If it's personal information, you shouldn't have it on the company's servers anyway. I am the company's foundation. It should not be, if it's company information, it should be available to your manager. Your manager.

这是一个重要的权限问题。如果你是CEO，你应该能够访问一些东西吧？或者你能够访问什么？如果J.Kell在里面有一份私人的Doc Sheets，没有其他人看到，你能看到吗？当然可以，因为这是组织的财产。有些员工认为这是一种谬论。我正在支付公司的账户。对于个人信息，你不应该将其存储在公司的服务器上。我是公司的基石。如果这是公司的信息，那么经理应该可以访问。

Alright. So that's a pernition to flag. But, you know, just as a fair warning to everybody there who works at a company, everything you say on your email is saved for all attorney, your documents, your Slack for all eternity, do not expect anything. Focal's as well. A lot of companies record all calls in coming in. I mean, in some of its compliance and some of its just the default, when you leave a company, you assign the documents to the next person or to the CEO. So if you wrote your diary or your journal in your corporate account, I mean, wake up people. It's 2023. Don't do that because it's going to be indexed. And then somebody's going to be able to pick it up.

好的。那是一个注销标志。但是，你知道，作为对每个在公司工作的人的公平警告，你在电子邮件中说的一切都会被所有律师、你的文件、你的Slack保存至永恒，不要指望什么。Focal也是一样。许多公司记录所有来电。我是说，在某些方面是合规的，有些方面是默认的，当你离开公司时，你会把文档分配给下一个人或CEO。所以，如果你在公司账户中写日记或日志，我的意思是，醒醒吧，人们。现在是2023年，不要这样做，因为它会被索引，然后有人会捡起来。

So poor initial flag. Stop using your personal phone for your startup in 2023. You have to stop doing this. It's such a common mistake that founders made open phone has totally rethought every detail of what a business phone should look like in 2023. And it's so affordable. You have no excuse. They make it super easy to get a business phone number for everybody on your team. It works through a beautiful web app on your phone or your desktop. And I can tell you it's amazing because our sales team and our ops teams use it daily.

起步标志比较糟糕。 2023年请停止使用个人手机来开创业。你必须停止这样做。这是创始人常犯的错误，在2023年公开的电话已经完全重新考虑了业务电话应该是什么样子。而且价格非常实惠。你没有任何借口。他们使每个团队成员获得商务电话号码变得非常简单。它可以通过你的手机或桌面上的美丽网络应用程序工作。我可以告诉你，这真是太神奇了，因为我们的销售团队和操作团队每天都在使用它。

Recently, we found so much values in open phone for our angel summit communications. Open phone is the number one rated business phone on G2 for customer satisfaction. And Twistner's are going to love it. Brian Jagger, he's the co-founder of startup called Atlete. He tweeted the following, I'm literally cashflow positive from listening to this week and startups for listener deals. And he explains that he previously got open phone money from this incredible discount that they give to this week and startups founders. And he says, I'm not paid to say that. I don't know Jason. Pure honest for you back in appreciation. And you know what? I'd love to hear this because there's so many people who listen to this podcast were founders and you need to use these tools. But listen, you might be cash constrained or you might want to put that cash into your product. Open phone is already affordable. Had a starting price of only $13 per user per month. But Twist listeners can get 20% off any plan for your first six months at openphone.com slash twist. And if you have existing numbers with another service, no problem. Open phone will pour them over at no extra cost. So head to openphone.com slash twist start your free trial and get 20% off.

最近，我们发现开放电话对于我们的天使峰会沟通非常有价值。在G2上，开放电话是客户满意度排名第一的商务电话。 Twistner（笔者注：指听众）会喜欢的。创业公司Atlete的联合创始人Brian Jagger在Twitter上这样写道：“我从这周的Startups for the Rest of Us节目中获得的折扣已经让我实现了现金流盈余。之前他已经从开放电话中获得了资金，因为他们会为这周和其他创业公司的创始人提供惊人的折扣。我不是为了说这些话而受到报酬，我也不认识Jason（指节目主持人）。我是真诚地表达我的感激之情。”我很高兴听到这样的消息，因为有很多听众是创业者，他们需要使用这些工具。但是，你可能会有资金限制，或者你可能想把这些资金投入到产品中。开放电话已经非常实惠，每个用户每月的起始价格只有13美元。但是，Twist的听众可以在openphone.com/twist上的任何计划中获得首6个月20%的折扣，如果你已经有了其他服务的号码，也没问题。开放电话会免费转接。所以，请前往openphone.com/twist开始你的免费试用，享受20%的折扣。

You have an example to show here, so many of people are watching at youtube.com slash this weekend or Spotify or the video. Let's go for a GPT4 here. And I have to stop that with this weekend. They got interesting too that I'll share. Okay, so I'm gonna share here. Give me a second. All right, and we're doing this live because we just got the data set from our producer. Okay, so we're inside of chat GPT here and we're gonna upload this electric vehicle data set. And that when you said send a message, there's a link on the right there. And if you on the left of send a message and that's where you upload from. Yeah, right here. There's like a little like a, there was a, yeah, see this little plus icon and normally the, so you can see the first thing. I didn't know that. Is that only for? That is only for the code interpreter. Got it. And so show just so people can see the interface here because we have never done this. But we just hit a new chat there. Let me just show people the interface and then just describe that for folks. Okay, we'll go ahead and chat. Okay, let's go. You click new chat on the top left. You hit this down arrow, Kate. Now you can see all the different items, plug-ins, default, et cetera. So you got a sports guest. That's a little bit so people see it. And then it gives you a little description of what it is and how good it is and the sort of internal rating of what it does. But you picked cold out code interpreter. Interpreter correct. Got it. All right. And then you hit the flood suite. And now, yeah, this is about, I think, a 29 meg file. And so it's going to take, you know, a few seconds to upload here. I see that.

你有一个示例要在这里展示，很多人正在观看Youtube.com/本周末或Spotify上的视频。让我们在这里尝试GPT4。我必须在这个周末之前停止。他们还发布了一些有趣的内容，我会分享给大家。好的，我现在要分享一下。我们正在现场操作，因为我们刚刚从制片人那里收到了数据集。现在我们在聊天GPT里，我们要上传这个电动汽车数据集。当你发信息时，右边有一个链接。如果你在左边发送消息，那就是你从哪里上传的。是的，在这里，有一个小加号图标。通常情况下我不知道那是什么意思。那只用于代码解释器。明白了。所以让人们可以看到这里的界面，因为我们从来没有做过这样的操作。但我们刚才点击了新的聊天。让我展示一下这个界面，然后为大家描述一下。好的，我们来聊天吧。你点击左上方的新聊天，然后点击这个向下箭头，你现在可以看到所有不同的选项、插件、默认等等。所以你选择了代码解释器。理解了。好的，然后你点击风暴套件。现在，是的，这大概是29兆的文件。所以上传需要花费几秒钟的时间。我看到了。

And so now what it's going to do, and none of us have really seen this file yet, which is fascinating. It is fascinating. And so you're doing this alongside of you. Yeah. So this is the code. So it's generated this code. This is Python code here. Jay, Kyle, you're asking about this weekend to read that file. And it's still generating and it's understanding. Now you can see here it's starting to tell us, hey, the data has been rolled into a data frame. And from the first few rows, we can understand that this is the data. So we're going to let this just let this complete. And I'll tell you the next, the next piece, which would Vinny was talking about a second ago was like, you know, where you normally have to go get a data scientist and so to do something like this. And so, and it, you know, throws some things up here and it says, okay, so it's done. So then my next question is going to be this. Well, let's just run what I showed there. It's loaded the data. And it says, oh, it looks like the data contains Vin location, model year, make vehicle type MSRP, and light department of licensing vehicle ID, some locations, utility and some census track.

现在，它要做的是什么，我们中的任何人都没有真正看到这个文件，这很有趣。这很有趣。所以你现在与你一起在做这件事。是的，这是代码。所以它生成了这段代码。这是 Python 代码。Jay、Kyle，你们在问这个周末要阅读那个文件。现在，你可以看到它开始告诉我们，“嘿，数据已经转换成数据框架了。”从前几行数据中，我们可以理解这些是数据。所以我们就让它自己完成。我告诉你接下来的部分，Vinny刚才说过的是，你知道，通常你需要去找一个数据科学家来做这样的事情。它在这里扔出一些东西，它说：“好的，完成了。”那我的下一个问题就是：“好的，让我们运行我刚才展示的内容。它已经载入了数据。它说：“哦，看起来数据包含了Vin位置、车型年份、制造商、车类型、MSRP、轻型车辆证书、一些位置、一些实用工具和一些普查区域。”

So what Nick, producer Nick gave us was the electric vehicle population data. And if you're not what's in there and it's reflecting that back to you in plain English. Correct. It is. And it's saying, hey, I'm ready to do something. It's loaded it. What I'm showing here is the prompt where it's loaded it into like a Python library called pandas, which is what a lot of data scientists would use to start analyzing data. So there was a, and it showed a carat there that said show the work. So after it uploaded it, when it finished work, it asked you to do that. And fascinating, when it did yours, for me, it did a different response to the same data, which is really interesting. Like Chatchy P4s told me the data second tains information about electric vehicles with each where I'll represent a specific electric vehicle.

所以Nick生产者给我们的是电动车的数据。如果你不了解其中的内容，他会用简单易懂的语言向你展示这些数据。没错，就是这样。这份数据显示出它已经准备好了要做些什么。这个数据集已经被加载进了一个叫做Pandas的Python库里，这也是很多数据科学家开始分析数据时会使用的工具。在数据上传后，它会显示一个指示符要求你展现处理过程。有意思的是，当你选择你的数据后，它会有一个不同的反应，即使是同样的数据，这真的很有意思。Chatchy P4s告诉我，这份数据包含了一些有关于电动汽车的信息，每一个“where”都代表着一个特定的电动车型。

The columns in the data set are as follows and it did it one through 10. It actually gave me a list of them, which is really like a totally more helpful response as very fascinating that we had two different. And that's sort of the nature of LLMs that can happen.

数据集中的列是1到10，它给了我一个列的列表，这个回答非常有帮助，让我感到非常有趣，因为我们有两个不同的列表。这是LLM的本质，这种情况可能会发生。

But this next question, which I'm putting down in the prompt, so I'll read to everyone, says, can you conduct whatever visualizations and descriptive analysis you think would help me understand the data? Because I have this producer next centess this file. And so now, let's see what it does in this next phase here.

但接下来的问题，我已经在提示中写下来了，我会念给大家听。它说：你能进行任何你认为有助于我理解数据的可视化和描述性分析吗？因为我有这位制片人在接下来的阶段中会使用这个文件。现在，让我们看看它在下一阶段中的作用。

And so what it's starting to tell us is we'll look at the following aspects of the data, the distribution of electric vehicle types, battery electric vehicles versus plug-in electric vehicles that's BEV versus P-Hav, top 10 most popular electric vehicle makes and models, distribution of the vehicles by year, geographic summary of the vehicles, and summary statistics of the range and base MSRP.

因此，它开始告诉我们，我们将研究以下几个方面的数据：电动汽车类型的分布，电池电动汽车与插电式混合动力汽车，即BEV与P-Hav，最受欢迎的前10种电动汽车品牌和型号，按年份分布的车辆，车辆的地理概述以及电动汽车的续航里程和基础MSRP的摘要统计数据。

And that's all of that just based on this question, which was, can you conduct whatever visualizations and descriptive analysis you think would be helpful to understand this data? And so now it's doing the work to basically do those five things for us. And again, you could imagine that is that you did a very generic question, which is you asked the CEO question, all right, thanks for the data. Data scientists in a meeting. Why do I care?

这一切都基于这个问题，即你能进行任何你认为有助于了解这个数据的可视化和描述性分析吗？现在，它正在为我们完成这五个任务。你可以想象这是一个很普通的问题，你问了CEO一个问题：“好的，谢谢你提供这些数据。数据科学家在开会时要问自己一个问题：我为什么要关心这些数据？”

Just get to the point. What did you learn by studying the data? And it's basically just starting with some general ideas here to get you started and you could pick one to double click on.

直截了当地说，你通过研究数据学到了什么？基本上这里只是一些概括性的想法，让你开始思考，并且你可以选择其中一个来深入探究。

Yes, correct. It's now doing the work and what you can see here. Oh my god. Like, you know, yeah. And so what does it remember? Imagine people are listening, sunny, source cascades.

是的，正确的。它正在进行工作，你可以在这里看到。哦，我的天。就像你知道的那样。那么它记忆了什么？想象人们在听着，阳光，源头的瀑布。

Okay, so it gave us five examples of things to look at the data. So the first is the distribution of the different, yeah, exactly of chart that shows us the distribution between battery electric vehicles and plug-in hybrid electric vehicles. And this is a visualization.

好的，它给我们提供了五个查看数据的示例。第一个是不同类型的电动汽车的分布，是一种表格展示了纯电动汽车和插电式混合动力汽车之间的分布情况。这是一种可视化呈现的数据。

It would have taken someone a few minutes to, you know, maybe 30 minutes to generate this chart in PowerPoint. And it's been generated for us automatically. And it shows us that the distribution is almost five to one here, right? Maybe four to one in terms of there's way more battery electric vehicles and plug-in electric vehicles. And according to the data set that we were given.

这张图表在PowerPoint里制作的话，可能只需要几分钟时间。但是这张图表是自动生成的，显示出电池电动车和插电式电动车的比例几乎是五比一或四比一。这个数据集告诉我们的信息。

The next chart is we're going to look at the 10 most popular electric vehicle makes. And we see here that Tesla is a clear leader with Nissan at number two, then Chevrolet, then Ford, and we see a visualization that chart there. Next, we're going to look at not by make, but we're going to look by model. And we can see here that the most popular model is the model three, then the model Y, then the leaf and so forth if you look at this chart.

下一个图表，我们将看看最受欢迎的10种电动汽车制造商。我们可以看到，特斯拉是明显的领导者，尼桑排名第二，然后是雪佛兰和福特，图表显示了这一趋势。接下来，我们将按车型而非制造商来看。通过这张图表，我们可以看到最受欢迎的车型是_model 3_，然后是_model Y，再是_leaf_ 等。

And then when we look at by year, and obviously, you know, this, we're only part way into 2023. And we see that the by year, the distribution of electric vehicles has generally been increasing with a little bit of a slowdown in 2019 and 2020 and a pick up back in 21 and a huge jump back in 2022.

然后，如果我们按年份来看，很明显，我们现在还只走过了2023年的一部分。我们可以看到，按照每年的数据来看，电动车的销售趋势总体上是在增长的，但在2019年和2020年有些减缓，而在2021年重新加速增长，在2022年则迎来了一个巨大的飞跃。

And we're only, you know, quarter, a little bit more than a quarter away from 2023. It would be my interpretation. But what's interesting here is now that you start to see some of these things, you could actually ask Chad, GPT, why is there a spike? But you could just do that in another window with Chad, GPT-4.

我们距离2023年只有不到四分之一的时间了。这是我的理解。但有趣的是，现在你开始注意到一些东西，你可以向Chad、GPT询问为什么有一个峰值。但你可以在另一个Chad、GPT-4的窗口中进行。

What's your takeaway here, Vinnie, just to bring you in on the conversation? I mean, I'm, I mean, I've thought using this to analyze my wine condition. Fantastic. You have it. I can see that. I see that. I see that. I'm uploading. What would it tell me about? That's exactly what I'm going to do. I'm going to go and just put it right now and see if I can go, you know, come up with some some, some train stats.

请问你的心得是什么，Vinnie？我想就这个话题让你加入进来。我是说，我考虑过用这个来分析我的酒状态。太棒了，你拥有它，我看得出来。我正在上传中。它能告诉我什么？那正是我要去尝试的。我要立即测试一下，看看能否得出一些有用的统计数据。

It's, you know, recommend other wines for me. That's what I'm going to tell you. You had, do you have plugins? Go do it. It will show it on the air if you're comfortable. What's interesting here also is based on the visualization and summary statistics.

嘿，你知道的，可以为我推荐其他葡萄酒。这就是我要告诉你的。你有吗？去做吧。如果你感到舒适，它会在直播中展示。这里有意思的是基于可视化和摘要统计。

There are some key insights from the data. It actually wrote some of these and it said, top 10 most popular electric VLSS.3, Tesla Model 3 is the most popular electric vehicle model, followed by Nissan Leaf, etc.

这些数据提供了一些重要的见解。数据表明，最受欢迎的电动车型排名前十名中，特斯拉Model 3是最受欢迎的电动车型，其次是尼桑Leaf等。

So you start getting into some really interesting concepts here. And for mine, I, let me share mine. This will be very interesting to do if I may. Oh, did you have another one you wanted to do, sunny? No, no, no, that's what, you know, I wanted to just show that capability because that's the new feature that I'm logged is uploading the data set, which I know you've been thinking about a little bit, Jay, because you have a lot of spreadsheets.

在这里，你开始涉及一些非常有趣的概念。让我分享一下我的观点。如果可以的话，这将非常有趣。哦，阳光，你有另一个想做的吗？不，不，不，我只是想展示这种能力，因为我知道你一直在考虑上传数据集这个新功能，Jay，因为你有很多电子表格。

I know. A lot of spreadsheets I got. Can you see my screen now? Okay. Yes.

我知道。我有很多电子表格。你现在能看到我的屏幕吗？好的。可以。

So I did the same thing. I uploaded the same file, but what you'll see here is that, if you're seeing it, remember I said it gave me just a list of what are the columns. Is it a game in the list of columns? And then I asked a slightly different question. What are the three most interesting trends in this data?

所以我也做了同样的事情。我上传了同样的文件，但是如果你正在看到它，记住我说过它只给我列的列表。游戏是列的列表中的一项吗？然后我问了一个略微不同的问题。这个数据中最有趣的三个趋势是什么？

I said, to identify interesting trends in electric field population, we need to analyze various aspects of the data set pretty generic. Let's explore the following three trends. Electric field vehicle adoption over time. Most popular electric vehicles makes a model distribution of electric field types like yours. And then it gave me a couple charts. It did a different design style, which is weird, but electric vehicle adoption over time instead of using a histogram, it did a line chart for time. It did the same thing. It did the same thing, the distribution, and it, too, gave me some highlights here.

我说，为了确定电场人口中有趣的趋势，我们需要相当通用地分析数据集的各个方面。让我们探索以下三个趋势：随时间的电动汽车采用情况，最受欢迎的电动汽车品牌和型号分布，以及与您的电场类型相似的型号分布。然后，它给了我一些图表。设计风格不同，有些奇怪，但在时间轴上，它做了线图来表示电动汽车采用情况，而不是使用直方图。它做了同样的事情，进行了型号分布的分析，也在这里给我了一些亮点。

And what I could do here is an interesting one. Let's see if this works. Please give me the same analysis, but take out all Tesla models. And if it gets this right, that's like game over, right?

在这里我能做的是很有意思的一件事。让我们看看这是否有效。请给我相同的分析，但请去掉所有特斯拉车型。如果能做到这一点，那就像是赢了游戏，对吧？

Because this is something you might ask. You're like, okay, we know Tesla is running the table on everything, but I don't care. I mean, we all know Model 3 outsells everything because it's, you know, the greatest model why I think is the greatest car I've ever made. But those two, but let's just take out all Tesla's and see if it does that, right? So now you're starting to be able to do things with data. I mean, it's just stunning. What can be done here?

这是你可能会问的一个问题。你可能会说：“好吧，我们知道特斯拉在各方面都很厉害，但我不关心。我们都知道Model 3的销量超过了其他任何型号，因为它是我认为是特斯拉有史以来最棒的车型。” 但是，让我们把特斯拉都排除在外，看看其他车型能否做到这一点，对吧？现在，你可以开始利用数据来做一些事情了。这是令人惊叹的，到底可以做些什么呢？

I was over the weekend trying to do things here inside of it. I'll show it. Well, I can't leave the screen. Is one of the problems with chat GPT-4? I think if you leave the screen, it will look like a lot of things. It can stop. Yeah, sometimes. Yeah. I guess they're trying to get people to not do this. But all of these little blocking and tackling things will be worked out over time, like doing multiple queries simultaneously.

我在周末尝试在里面做些事情。我会展示一下。嗯，我不能离开屏幕。这是GPT-4聊天的问题之一吗？我想如果你离开屏幕，它看起来会像很多东西。它会停下来。是的，有时候是这样的。是的。我想他们正在努力让人们不这样做。但是所有这些小小的阻挡和处理问题都将逐渐解决，比如同时处理多个查询。

Like just for the love of God, Greg and give me a corporate account here. Let me put all my people into chat GP4, let all of this data be shared in a common repository. I need multiplayer mode for chat GPT-4 and I would pay $200 a person per month. I would pay $4,000 a month, $50,000 a year.

请务必给我一个公司账户，为了天啊，Greg！让我把所有的人都加入 GP4 聊天室，在一个共享库中共享所有这些数据。我需要 GPT-4 聊天室的多人模式，并且我愿意每人支付 200 美元每月的费用。我愿意支付每月 4,000 美元，年薪为 50,000 美元。

Right now I'm paying $20 across everybody in my organization and hopefully everybody in my companies is actually doing this now. If you hear my voice, I've been like tweeting about just, oh, wow, here we go.

现在我正在支付20美元给我们组织中的每个人，希望我们公司中的每个人现在都在这样做。如果你听到我的声音，我一直在推特上发推关于这个话题，噢，哇，我们开始了。（注：句子的意思比较难理解，有一些流行语词汇。大致意思为现在我正在支付20美元给我们组织的每个人，希望我们公司中的每个人都真正这样做。如果你们听到我的声音，我已经开始在推特上发布有关这个话题的推文了。）

Let's see. Electric vehicles over time without Tesla. That's interesting. And then the models, yeah, wow, it nailed it. Most popular electric vehicles makes without Tesla models. You see a very more even distribution in the chart, Nissan Chevrolet Ford BMW are one, two and three, but it's not as spiky because you're taking out. And then you see here that actually the hybrid, since I guess Tesla doesn't produce a hybrid versus battery electric vehicles becomes much more normalized.

让我们来看看没有特斯拉的情况下，电动汽车的发展趋势，这很有趣。再看看各种车型，哇，它查得很准。在没有特斯拉车型的情况下，最受欢迎的电动汽车品牌呈现出更均衡的分布，尼桑、雪佛兰、福特和宝马列在前三位，但由于去掉了特斯拉，所以不那么突兀。此外，你可以看到，混合动力车型与电池电动车型相比，变得更加普及。

So here peak sales in 2022, it looks like is 14 hours. Well, it's just the 23 is not complete yet, right? So that's why it's so small. Last complete year, it was 25,000 over 25,000. Oh, sorry, number of EVs, would that be 25 million? What is the left hand here? No, it can't be 25 million, it would be 2.5 million maybe. 5 million? Yeah, probably that makes more sense. So it's, it is like, yeah, it says 14,000, but it actually means add probably 2.0. So 1.4 million. So you're just taking out a lot of vehicles, probably. Yeah, Tesla sold what looks like 500,000, is that right? No, 50,000. This is maybe a commercial close to a million. This might be US, because it was a huge area. It had state vehicle and other information. What's the time frame for this? What's time frame for this? Like, yeah, mine. No, it's two thousand. It went back a few years.

2022年销售高峰似乎是14小时。嗯，因为23号没结束，所以数字很小。去年整个年份，超过25,000辆电动汽车销售。哦，抱歉，电动汽车的数量会是25百万辆吗？这左边是什么？不，不可能是25百万，也许是2.5百万？500万？是的，这可能更有意义。因此，它看起来是14,000，但实际上应该加上2.0，即1.4百万。因此，你可能要去除很多车辆。对了，特斯拉销售了大约50,000辆，对吗？不，这可能接近100万辆商业用车，可能是美国的，因为那是一个巨大的地区，涉及州车辆和其他信息。时间范围是什么？是我的时间吗？不，它回溯了几年。

Yeah, the data was back. I mean, this is just incredible. I mean, you just see like we're lifelong technologists. We know how much time this kind of takes to do this kind of stuff. Can you take your website information or your podcast data and then you start slicing and dicing that now? Yeah, and imagine the work and the number of people it took and the time it took.

是的，数据已经回来了。这太不可思议了。我们是终生的技术专家，知道这种事情需要花费多少时间。你能把自己的网站信息或者播客数据，现在开始分析和拆分吗？是的，想象一下需要多少工作人员和时间来完成这一切。

You Jason would want that answer right away. Where are the listeners from? Which ones? All the different, you know, you're going to go after this, Jason, and download all your data and going to be uploading it immediately is my guess. Right.

杰森，你肯定会想马上得到那个答案。这些听众来自哪里？哪些人？你知道的，你接下来会去追查这些信息，然后立刻上传。是这样吧。

Yeah, I mean. I mean, it doesn't need to have a developer account for that or like what do you need to have to be able to use this? Right now you have to be, um, have a developer account and you need to be, uh, let in by OpenAI. This is the year you need to perform. You need to be focused and I want your startup firing on all cylinders and how you're going to do that.

是的，我的意思是，你不需要有一个开发人员账户或者需要什么才能使用这个？目前你需要拥有开发人员账户并且被 OpenAI 允许使用。这是需要你发挥实力的一年，你需要集中注意力，让你的初创公司在全方位开火，这是你要如何实现的。

You're going to use code up code up helps you do more with less in code of your team can work on entire projects from start to finish. That's right. One product you have everything you need in one place where in the efficiency revolution, you have to do more with less and right now is the perfect time for you to jump in and learn about all the amazing features that Coda has. Coda is the dock that brings it all together and it's efficient and it's fast. We use Coda at this very podcast to track my J trades.

你将会使用Code Up。Code Up可以帮助你在代码上做更多的事情，你的团队可以从头到尾地处理整个项目。没错，一个产品，你可以在一个地方拥有你所需要的一切。在效率革命中，你需要在更少的资源下做更多的事情，现在正是你跳入并学习Coda所有惊人功能的最佳时机。Coda是一个将所有内容整合在一起的平台，高效快速。我们在这个播客中使用Coda来跟踪我的J交易。

If you just go to J trading.com, it'll take you to a gorgeous Coda page of all my J trades. Not an amazing product, it's always advancing. The templates are next level, but here's the important call to action. You can operate and collaborate in one place to get your projects done faster.

如果您只是访问J trading.com，它会带您进入一个美丽的Coda页面，展示我所有的J交易。虽然它不是一个惊人的产品，但它一直在不断进步。模板水平很高，但这里的重要呼吁是：您可以在一个地方操作和协作，以更快地完成项目。

Take advantage of the special limited time offer just for startups. Sign up today at Coda.io slash twist and you will get the $1,000 startup credit on your first statement. That's right. CODA.io slash twist for a $1,000 sign up credit and this offer is so generous. I want you to take advantage of it right now because I don't know how long this absurdly generous offer from Coda will exist. CODA.io slash twist for $1,000 in sign up credits right now.

趁现在有限时优惠机会，立即注册Coda.io slash twist，即可在第一个账单上获得1000美元的初创企业信用额度。这是正确的。Coda非常慷慨地提供这样的优惠，我希望您立即抓住它，因为我不知道这个Coda荒谬慷慨的优惠将存在多长时间。立即访问Coda.io slash twist，获得$1,000的注册赠金。

There is a wait list for plugins. But this is so. It's a compute intensive, Jay. Jay, let's go back to the old GPU shortage problem. This is compute intensive. They gave every $100 million users plus access to this. They were just fried the system. They don't have the capacity for it.

插件列表中有等待名单。原因是这个任务需要大量计算资源，Jay。Jay，让我们回到旧的GPU短缺问题。这个任务需要大量的计算资源。他们给了每个1亿用户，以及获得此服务的额外用户，结果超过了系统承受的极限。他们没有足够的容量满足需求。

Honestly, I think we're getting to the point where this is so valuable for organizations that Azure and AWS should just start offering your own. What is it A100? Is the Nvidia. I mean, Amazon is working on it, but it's not that simple just to expend these things up. It's going to take a couple of years to get. Oh, I mean, just racking them is going to take time producing them. You have to basically.

说实话，我认为这对组织非常有价值，以至于Azure和AWS应该开始提供自己的A100。什么是A100？它是英伟达的产品。我的意思是，亚马逊正在开发它，但这并不是简单地扩展这些东西的问题。这将需要几年来获得。哦，我的意思是，仅仅是将它们放在架子上就需要时间生产它们。你基本上必须。

Jay, kill. There's a shortage. There's a chip shortage update. I absolutely understand. But what I'm saying eventually was the word I use, Vinicius. Eventually, I think organizations are going to start provisioning their own GPUs for this because it's so valuable. If you told me right now, an A100, you know, cost $10,000, would you like me to sell you one for $20,000 to have it in your organization today to start doing this? I mean, it's a diminimous amount of money compared to the value created.

杰伊，紧急情况。芯片短缺了。芯片短缺的情况有了最新进展。我绝对理解。但是我所要说的，最终使用的词语是Vinicius。最终，我认为组织将开始为此提供自己的GPU，因为它非常有价值。如果你现在告诉我，一台A100芯片成本为10,000美元，你是否愿意花20,000美元买一台为了让你的组织今天开始进行这项工作？我的意思是，与所创造的价值相比，这是微不足道的一笔费用。

I just answered another question. I was like, which dates had the most growth in 2021 and 2022? And it's based on this, the electric vehicles dates 2021. Here are the two top states with the most growth. You want to take a guess? Which dates had the most growth percentage rise? Without California? No, no, without California. No, I said percentage growth. I said, which dates had the most growth in 2021 and 2022? Interpreter that as percentage, not run numbers.

我刚刚回答了另一个问题。问题是，哪些日期在2021年和2022年增长最多？基于此，2021年的电动汽车日期是关键。以下是增长最多的两个州。你能猜出来吗？哪些日期的增长率最高？不包括加利福尼亚吗？不，我说的是百分比增长率。我说的是哪些日期在2021年和2022年增长最多？把它理解为百分比，而不是数量。

So it is. I'll say Texas. I'll say Texas. Okay, which are okay, keep going. I'm not going to say this right. Texas and probably move Florida. Maybe Washington. Yeah, I'd say yeah, like Washington. Yeah, smart. Sorry. What a number of minutes in F bomb.

没错，我会说德克萨斯州。我会说德克萨斯州。好的，接着说。我可能说不准这个。德克萨斯和可能转移到佛罗里达州。也许还有华盛顿州。是的，我会说，像是华盛顿。很聪明。抱歉，刚才说了几次脏话。该段言语并没有明确的意思，或者语境缺失，只能就字面翻译，尽量保持易读性。

Washington is number one. They grew from 18 to 27,000. Yeah. A growth of 9,000 EVs, 50% growth. And Texas was number two. Yeah. Actually, it got that wrong. It says number of EVs in 2021, 3, number in 2022 for. It's Washington state data specifically. It's in Washington state. Oh, this data set? Yes, this data sets Washington state data from Washington state.gov.

华盛顿州是第一。他们的电动车数量从18增长到27,000。增长了9,000辆电动车，增长了50％。而德克萨斯州排名第二。实际上，它错了。文中说2021年的电动车数量为3，2022年的数量为4。这是特指华盛顿州的数据。这个数据集是来自华盛顿州政府网站的数据。

Oh, sorry. Okay. So what we're looking at has nothing to do with by state. Okay. That's why the numbers were low. Okay, great. Yeah. I'm looking at the CSV though. It does have all kinds of counties and cities. Like I see saying. I can't leave it all in. We just took, by the way, for the first listening, we just took a random data set the producers found and just uploaded it. So we found this data set. It doesn't have perfect information. And so just understand like the where this is kind of an interesting use case. Somebody sends you a CSV. You don't know what it is. And it starts interpreting it for you.

对不起，好的。所以我们正在查看的与州无关。这就是为什么数字很低的原因。好的，很好。是的，我在查看CSV文件。它包含各种县市。正如我所说的。但我不能把它们都留下。顺便说一下，我们只是拿到制作人找到的随机数据集并上传了它。所以我们找到了这个数据集。它并不是完美的信息。因此，理解这个案例是非常有趣的用例之一。有人给你发送了一个CSV文件，你不知道它是什么，然后开始解释它。

All right. Well, producer Nick, who is an exceptional producer. You hear people talk about producer Nick on all in and here at this week in startups. It a wonderful job producing today. And he said, uh, explain to the audience what you found and what you did while we were alive on air.

好的。首先，制作人尼克是一个非常出色的制作人。你可以在All In和此类创业节目中听到人们谈论制作人尼克。他在今天的制作工作中做得非常出色。他让我们现场告诉观众你找到了什么并且在直播时你做了什么。

Yeah. So I found a website where they have a bunch of CSV files from government data, one of which was the one that you just saw previously, the Washington State EV data. I also found one which has something to do with the topic that we're covering today about FDIC bank failures, which was from the actual FDC FDIC.gov website, which you can see right here. Pretty amazing.

是的。我找到了一个网站，其中包含大量政府数据的CSV文件，其中一个就是你之前看到的华盛顿州EV数据。我还找到了一个与我们今天所涉及的FDIC银行破产有关的数据，它来自实际的FDC FDIC.gov网站，你可以在这里看到。非常棒。

I uploaded it. It found a formatting error on the CSV file. And I was about to look up how to fix it. And Chatchee, we teach us fix it itself. Found a Unicode error. Okay. Yeah. That's common. And then just fixed it. Pretty crazy. Perfect.

我上传了它。CSV文件上发现格式化错误，我正要查找修复方法。然后Chatchee告诉我们修复方法。发现一个Unicode错误。好的，没问题。然后就修复了。相当不错。

Um, then it's, I asked it one of the most interesting ways to visualize this data. Gave me some examples. I said, okay, do that. Um, and here you go. Okay. So let's take a look here. Um, it said bank closures by year, bank closures by state, top acquiring institutions, fascinating heat map of bank closures, timeline, heat map of bank closures, timeline of bank closures. This is fascinating.

嗯，那么我用了一种最有趣的方式来展示这些数据，然后让它举了一些例子。我说，好的，就这样吧。然后，你看看这个。嗯，接下来我们来看看这个。他展示了按年份和按州别的银行关闭情况、顶级收购机构、引人入胜的银行关闭热力图、时间轴和银行关闭时间轴热力图。这很有趣。

So let's scroll down here and see what Chatchee came up with. Uh, again, finding errors and fixing them, scroll down. Now, let's proceed with creating visualizations. They'll start with bank closures by year, bank closures by state, type acquiring top acquiring institutions is fascinating. And obviously we see by year, scroll down 160 or so in, uh, the financial crisis and then it slowly went down. But what's interesting about that, Vinnie, if you look at it, you notice that the bank closures that started in 2008 peaked in 2010. So it was a full two plus year process of peaking and then trailing off, you're going to have some per year, but it still took a, it was basically four years of bank closures.

让我们往下滑动看看Chatchee想出了什么。再次查找错误并进行修复，继续往下滑动。现在，让我们着手创建可视化图表。它们将以年度银行关闭情况、各州银行关闭情况、最有吸引力的收购类型等为开端。当然，我们可以看到按年度来看，在金融危机期间，银行关闭数目急剧增加，然后慢慢下降。但有趣的是，如果您观察一下，会发现从2008年开始的银行关闭高峰出现在2010年。因此，它是一个连续两年以上的高峰期，然后逐渐下降，每年还会有一些银行关闭，但基本上持续了四年时间。

Well, well, so just remember, so a lot of this was back in the days we had, uh, we, we've had a lot of the smaller banks being consolidated up and then they passed the laws on other bigger banks as well. So it's unlikely for us to see the same sort of tail right now because all the small banks have been cleaned up. However, if you look at the latest data and just the amount of money that's in the banking sector is blowing up in the past two or three months out of like five banks, we've had, um, more AUM blow up.

好的，好的，记住，很多情况是在早期发生的，我们曾经有许多较小的银行整合，之后也通过了对其他更大的银行的法律。因此，我们现在看到同样的情况的可能性不大，因为所有的小银行都已经被整合。然而，如果你看看最新的数据，以及在过去两三个月中银行业中的资金规模呈现爆炸式增长，其中五家银行的资产管理规模得到了更多的扩大。

I think in 2023, then in 28 and nine in 1011, like the whole banking crisis, we, in the past three months, we've had like, like, like Washington Mutual versus Silicon Valley bank versus first republic, et cetera. Like the scale is so different right now because these banks are so big. It's interesting also about what Nick found here is like, you could see some of these didn't have acquires they just shut down some of them, uh, you know, were acquired by state bank and trust company, first citizens bank, the Maris Bank, US bank, NA. So just fascinating ways to look at data.

我认为在2023年，28年和1011年九月，就像整个银行危机一样，在过去的三个月里，我们看到了像华盛顿互助银行，硅谷银行和第一共和银行等之间的竞争。现在这些银行的规模非常大，所以差距也非常大。还有Nick在这里发现的有趣的东西是，你可以看到其中一些没有被收购的公司只是关闭，一些被州立银行和信托公司、第一公民银行、Maris银行、美国银行NA收购。所以这些数据的观察方式非常有趣。

If you're listening to this in your organization, there's going to be two possibilities of what happened. This is what I've been trying to explain to people. Maybe I have to go back to base cow and start using all caps on Twitter. But I am finding that 30% of what I do can be done inside of chat PT for today. I'm finding my producers and you sort of Nick pull up his thing there and I start questions in his thing that were questions I was asking during live this week and start up. So when I'm doing the show, the producers are looking up data. They're using chat GPT for all day long, um, and even during shows.

如果你在你的组织中正在听到这个，有两种可能性会发生。这就是我一直试图向人们解释的。也许我必须回到基本的cow，开始在Twitter上使用所有的大写字母。但是我发现我所做的30%可以在今天的chat PT内完成。我发现我的制片人以及像Nick这样的人在那里提供他的想法，我开始在他的想法中提出的问题，这些问题是我在本周直播中问的，他开始启动。所以当我在做节目时，制片人正在查找数据。他们整天都在使用chat GPT，甚至在节目期间也在使用。

So this to me is what I would implore people to try to understand right now. Smart people who are using this are taking, I would say between 10 and 50% of their job and automating it and then they're quiet quitting or they're doing more work and they're going to be more effective in their organizations or their boss is going to figure this out. And everybody's going to get more work done.

在我看来，现在我想要呼吁人们理解的是，聪明的人们正在尝试自动化在工作中占据10%到50%的部分，然后他们要么静静地辞职，要么就做更多的工作，这样他们就可以在自己的组织或公司中更有效率，或者他们的老板也会意识到这一点。这样每个人都会完成更多的工作。

And instead of hiring, people are going to start firing and getting more done. So just think about gains, 30% gains across an organization of let's take my investment firm about 20 people. That's the equivalent of having 26 people.

相反，人们将开始解雇员工，以完成更多的工作。因此，只需考虑到收益，对于一个大约有20人的投资公司而言，30％的收益意味着相当于拥有26个人的效力。

So one of two things is either going to happen. If you had 20 people, you're either going to go down to 14 and save that money or you're going to act like a 26 person organization or something in between. That's how management thinks. Now for my team, we're just doing a great job.

有两种情况之一将会发生。如果你原本有20人，你要么减少到14人并节省开支，要么就像拥有26人的组织那样运作，或是在两者之间。这是管理层的想法。对于我的团队，我们正在做得很出色。

I just want you to become 30% more efficient so we don't have to hire more people. But other people are going to look at this, Vinny, and they're going to take a different approach, which is, okay, we have how many data scientists? Great. Half their requests are not necessary.

我只是希望你的效率提高30%，这样我们就不用再雇佣更多的人了。但是其他人会采取不同的方法看待这个问题，比如我们有多少数据科学家？很好，他们的一半请求是不必要的。

They're going to be done by chat GP2Fore people are not going to need them. So we just get ready to half the data scientists. Now take a moment to think about what I just said.

他们将通过GP2Fore人工智能完成，人们不再需要它们。因此，我们要开始半数数据科学家。现在，请花一些时间仔细思考我刚刚说的话。

There's been a competition for data scientists. Some organizations say, how many of these data scientists do we need?

最近出现了一个数据科学家竞赛。一些组织在问，我们需要多少这样的数据科学家呢？

Well, I'd say right now, Jacob, we probably don't have enough on a global basis. So I don't think there's going to be a shortage of data scientists anywhere in the future. They may be reallocated from companies that have seven down to three and then those four go elsewhere that's needed.

嗯，我认为现在全球范围内我们可能还不够。因此，我不认为未来会出现数据科学家短缺的情况。他们可能会从那些公司被调配，从七家降至三家，然后那四家挪到其他需要的地方。

So I think you probably need fewer data scientists per company, but there's still companies out there that's going to need that never thought of having data scientists because they just didn't have the, you know, you sort of have to pay them for the licenses, right? And then they use it, which is like millions of dollars a year. So now the cost of the software has come down dramatically.

我认为每家公司可能只需要较少的数据科学家，但仍然有一些公司可能需要他们，因为以前他们从来没有考虑过需要数据科学家，因为他们只是缺乏支付许可费用的能力。而现在这种软件的成本已经急剧下降。

You still need the people to operate it because, you know, some people just need to be focused on the stuff and a lot of companies are data and multiple databases and spreadsheets and it's all very disparate, you start to build data warehouses that have all information et cetera. So it's not as simple as that. I think that. Is it not as simple as that?

您仍然需要人来操作，因为有些人需要专注于处理这些材料，许多公司都有许多数据和多个数据库、电子表格，它们都非常分散，您需要开始建立数据仓库，使其包含所有信息等等。因此，这并不像它看起来那么简单。我认为......这是这样吗？

No, I don't think so. I think in a world where everything was highly efficient and everything was run properly, not maybe, but we're so, I mean, the gap right now between the haves and the have-nots in data science is very, very, very, very big.

不，我不这么认为。我认为在一个一切高效且运营良好的世界中，不仅可能会发生这种情况，而且目前在数据科学领域，富有和贫困之间的差距非常非常大。

I don't know, Sonny. I might disagree. This weekend, I started learning Python. You already called me Sonny right now. Vinny. No, I was going to Sonny. I was going to throw to Sonny. I thought you did, I was like, oh my god. I was going to throw up Sonny. Listen, you guys are Sonny and Vinny. Two of my best friends, the names are different by one letter. Sonny and Vinny.

我不确定，Sonny。我可能会有不同意见。这个周末，我开始学习Python。你已经叫我Sonny了。Vinny。不，我本来是想喊Sonny的。我还以为你叫了我，我都快吐了。听着，你们是我的好朋友Sonny和Vinny，名字只差一个字母。Sonny和Vinny。

Two letters. Sonny and Vinny? Two letters. Oh, right. Yeah, sorry, sorry. I had a long weekend. I had the kids alone. Anyway, I am going to disagree Vinny and Sonny, I want you to reflect on this.

两封信。Sonny和Vinny？两封信。哦，对了。是的，抱歉，抱歉。我度过了一个漫长的周末。我一个人带孩子。无论如何，我不同意Vinny和Sonny的意见，我希望你们能反思一下这个问题。

You and I, we're chatting. We're trying to get together over the weekend to do a little co-gem, but you know, kids whatever got in the way. But I started on a warrior game. This loss, warrior is one incredible shout out stuff, Curry. Replit is like a coding environment. So I just signed up and I started taking their Python course. I was like, oh my god, this takes so much concentration.

你和我正在聊天。我们想在周末一起玩点合作游戏，但是，你知道，孩子们却成了障碍。不过，我开始玩一款战士游戏。这个失利，战士打出了一个惊人的呼喊，库里。Replit是一个编程环境。所以我刚刚注册并开始学习他们的Python课程。我发现这需要很多注意力，真是太难了。

I'm never going to be able to do this. Like this is not going to be my chosen career, but I do want to see how far I can take it because they have a bounties thing on Replit and I put a bounty up and then I explained in details.

我永远不会能够做到这件事情。就像这不会成为我的职业选择，但我想看看我能走到哪里，因为在Replit上有一个赏金计划，我发了一个赏金，然后进行了详细解释。

I'd like an order GPT agent that checks our database of already contacted companies by URL. So these are startups we've talked to. So we say hey, calm.com and uber.com are in the database right now. We don't need to call them. Then finds new startups on CrunchBase.com to LinkedIn and sends them a semi-automated email from one of our researchers introducing our venture fund. Acceptance criteria.

我想要一个订单GPT代理，它可以检查我们已经通过URL联系过的公司的数据库。这些是我们曾经对话过的初创公司。比如我们会说"hey，calm.com和uber.com现在在数据库里。我们不需要给他们打电话。"然后它会在CrunchBase.com到LinkedIn上找到新的初创公司，并且从我们的研究人员中选择一个向他们发送半自动化的电子邮件介绍我们的风险基金。验收标准。

App is able to find a recently updated CrunchBase profile within a specific criteria, geography, investment stage and sends an email to that founder. Pretty simple, right? I put this up for 27,000 cycles, I guess they call them on Replit. Shout out to the team at Replit that emailed me immediately after I talked about it on the pod.

该应用程序可以按照特定的条件（如地理位置、投资阶段等）查找最近更新的CrunchBase资料，并向创始人发送电子邮件。非常简单，对吧？我在Replit上发布了这个功能27,000个周期（应该是他们的叫法）。向在我在播客中提到该功能后立即给我发送电子邮件的Replit团队致以感谢。

I put it up for $270. I got four applications. As you can see here, one person says Jason had built this in the past and building for a few funds. I'm not the only one thinking like this.

我以270美元的价格发布了这项任务，收到了四份申请。你可以看到，其中一个人说Jason过去曾经建造过这个项目，以及为一些基金建造过房屋。我不是唯一一个持这种看法的人。

We'd love to chat more about you and check my GitHub linked in for resources. He's done three bounties. I'm a fan of the pods. I've read your book, Dumb luck. I'm poking around Replit and see what all the fuss about. I'll tell you about it.

我们很想聊聊关于你的更多信息，并查看我的GitHub链接以获取资源。他已完成了三个赏金任务。我很喜欢这个群组。我已经读过你的书《愚蠢的运气》。我正在探索Replit，看看有什么大惊小怪的事情。我会告诉你的。

Regarding your bounty, I'd like to help ask you to flesh out your criteria. I do either of these free as long as we can take pretty much the time to coach you. My personal churn. I don't like taking free stuff.

关于您的悬赏任务，我想帮忙询问您的具体要求。只要我们可以花足够的时间辅导您，我可以免费为您完成其中的任何一项。个人来说，我不喜欢接受免费的东西。

Anyway, my point here, Vinny, and then I'll go to Sunny, is I am the CEO of the company. I'm the GP, the general partner of the fund. I'm looking at this and I'm like, I wonder how long it is between when I can describe something to a bounty program and have code sent to me.

无论如何，我的观点是，Vinny，然后我会转到Sunny，我是公司的CEO。我是这个基金的GP，也就是总合伙人。我在看这个东西时，想知道我向赏金计划描述东西后，能在多久收到代码。

Then I run it myself, just like I am using Chatship T4. I feel like I'm on a collision core sunny between using Chatship T4 with plugins and uploading stuff myself. Then working with the developer community to write tiny little scripts for $270, that a $50 salary or $40 salary or $60 salary for, let's say, an operations person in our organization. That would take five hours. I can basically take what is 50 hours a week of work in our company.

然后我自己运行它，就像我使用Chatship T4一样。我觉得我正在使用Chatship T4插件和自己上传东西之间的碰撞核心阳光。然后与开发者社区一起编写一些微小的脚本，以$270的价格雇佣一个我们组织中的运营人员可能需要50美元、40美元或60美元的薪水来完成。这将需要五个小时的时间。我基本上可以把我们公司每周50个小时的工作量解决掉。

Two researchers doing 50 hours a week of work, $1,500 a week, maybe $2,000 a week fully baked with benefits, $100,000 a year of work, and I can just automate it for $270. Am I crazy or is this going to change the world? No, I mean, you're 90 days away. To the count for 90 days away. At the pace we're going at right now because what you put in here is mostly just doable. I said we're entering a world where the core framework is being absorbed by OpenAI.

两位研究人员每周工作50个小时，每周获得1,500美元的报酬，加上福利也可能达到2,000美元，每年可收入10万美元，而我只需要花费270美元就能将其自动化。我是疯了还是这将改变世界？不，我的意思是，你离成功只有90天了。90天倒计时。根据我们目前的速度，你所提供的大多数东西都是可行的。我说我们正在进入一个由OpenAI主导核心框架的世界。

If you just saw what we did, they're taking their time right now from a safety perspective that the code interpreter that we were just playing with, J-Kell, doesn't reach out to the internet just yet. We know that they have browsing capabilities because there's other plugins that can browse. As soon as they allow code to go out to the internet, which they've controlled that, it's not like they don't know how to do it, then you have that problem solved right inside code interpreter.

如果你刚刚看到我们的做法，他们现在正在从安全的角度放缓时间，因为我们刚刚玩的代码解释器 J-Kell 还没有到达互联网。我们知道他们有浏览功能，因为有其他插件可以浏览。只要他们允许代码传输到互联网，他们已经控制了这一点，不是他们不知道怎么做，那么你就可以在代码解释器内部解决这个问题。

I'm not surprising because you would describe your problem inside code interpreter and say, here's my spreadsheet, go to CrunchPace. So the same thing you did in the Replic, you'll do inside there.

我不觉得意外，因为你会在代码解释器中描述你的问题并说：“这是我的电子表格，去CrunchPace。”在Replic中，你会做同样的事情。

Developer Talent is the most precious resource for B2B startups. You know that. And you want your developer's focus on product, not on compliance, right? When you're selling B2B software to large enterprises, you need to jump through a ton of security and compliance hoops, and one of those hoops is large customers need you to host your software on their cloud. And you need to build that out on a per customer basis. Think about that.

开发人才是B2B创业公司最珍贵的资源。您知道这一点，您希望您的开发人员专注于产品而不是符合合规要求。当您向大型企业销售B2B软件时，您需要通过大量安全和合规性审核，其中之一是大客户需要您将软件托管在他们的云上。而您需要根据每个客户的要求来构建托管方案。想想这个问题。

So B2B startup companies constantly face this dilemma. Do you keep developers focused on infrastructure, which could hurt your product velocity, or do you keep them focused on the product velocity, which would then delay your ability to close large customers? And I have a solution for you, and it's called release delivery. What release delivery does is it automates the creation of enterprise class app delivery for private clouds and single tenant applications.

因此，B2B初创公司经常面临这个困境。您是让开发人员专注于基础设施，这可能会损害您的产品速度，还是让他们专注于产品速度，这将延迟您关闭大客户的能力？而我有一个解决方案，它被称为发布交付。发布交付的作用是自动化企业级应用程序交付的创建，适用于私有云和单租户应用程序。

Basically, this led you to deliver your software seamlessly into any customer environment. This will unlock a ton of revenue potential for you, and release delivery will put all the tedious stuff on autopilot for you. So you can turn your ideas into apps and deploy those apps quickly and flexibly into their clouds.

基本上，这使您能够顺畅地将您的软件交付到任何客户环境中。这将为您开启大量的收入潜力，并将发布交付流程自动化，让您不必再费心琐碎的事情。因此，您可以将自己的想法转化为应用程序，并将这些应用程序快速灵活地部署到云中。

So here's your call to action. Let release show you the power of release delivery and get your first month free at release.com. Slash twist. What a domain name. Are EL E A SE dot com slash twist. Sub to $10,000 in value at release.com slash twist.

这是您的行动号召。让Release向您展示发布交付的强大之处，并在release.com/twist上获得首个免费月。这是一个多么棒的域名：EL E A SE点com/twist。在release.com/twist上获取高达10,000美元的价值。

I would agree with Sunny on this. I mean, guys, this is the fifth generation language. We never really got to it. This is natural language programming. Everyone's a programmer now. You just need to speak English at this point. You'll do it. Not even English, other languages as well. Check if you can translate for you. So as long as you can.

我同意Sunny的看法。我的意思是，这是第五代编程语言，我们从来没有真正掌握。这是自然语言编程。现在每个人都是程序员。你只需要说英语就可以了。甚至不仅仅是英语，其他语言也可以。检查一下它是否能为你翻译。只要你能做到就行。

Evening, but language is code. Natural language is code. We had to create this layer with digital software programs machines could interpret what we're saying accurately. And could the human brain so complex? The language is a very complex thing for us. But machines that we've had to instruct machines based on a very limited number of words, functions that we have that was written. And now it's fully expansive.

晚上好，但语言是代码。自然语言也是代码。我们必须使用数字软件程序创建这个层次，使机器能够准确解释我们正在说的话。人类的大脑有如此复杂的结构，但语言对我们来说却是非常复杂的。但我们必须基于有限的单词和功能对机器进行指令。现在，这些指令已经得到了完全的拓展。

Like now you have the entire English vocabulary that you can use and the machine understands what you mean. You can be extremely precise in what you're saying to it as well. Whereas in the past, you have to write functions to do certain things. It basically now understands every single word and English dictionary to a very, very deep level and every single word becomes effectively like somewhat of a function or a describe or something.

现在你有整个英语词汇可以使用，并且机器明白你的意思。你可以非常精确地向它表达你的意思。而在过去，你必须编写函数来完成某些任务。现在，它基本上可以深入理解英语词典中的每一个词，并将每一个词有效地转化为一个函数或描述之类的东西。

So like, I posted a tweet yesterday, we'll put it up and I think this is a very important point that we should very touch on today and get your views on this. I think that in the next cycle, so we're in a bare cycle right now. We're heading to one or whatever you want to call it.

就像昨天我发布了一条推文，我们会将其展示出来。我认为这是一个非常重要的观点，我们今天应该非常关注并听取您的意见。我认为在下一个周期中，我们现在处于熊市。我们正在朝着熊市前进，或者你可以怎么称呼它。

Obviously, we may not be in a recession. I think we are in a recession for what I'm seeing and seeing the signs of a recession already. The next cycle that we go through is either depression or it's a recovery and a boom. So whatever you want to define in the next cycle. Regardless, I think we're heading for deflation in a big way.

显然，我们可能不处于经济衰退中。从我看到的情况和衰退的迹象来看，我认为我们正处于经济衰退中。我们接下来经历的循环要么是萧条期，要么是复苏和繁荣。所以无论你如何定义下一个循环，我认为我们正朝着通货紧缩大幅度前进。

And I think that this will become the number one driver of deflation. I think you're exactly correct. What's going to happen is massive efficiency will come to the companies that get on this early.

我认为这将成为通缩的最主要推动因素。我认为你完全正确。会发生的事情是，那些早期使用这种技术的公司将会获得巨大的效率提升。

Then what will end, you know, if you're running a company right now, you should just give everybody the tool, ask them to show you what they did with it. And if you have 10 people in your department, if seven people use the tool and three people don't, you should fire the three people who don't use the tool.

如果你现在经营一家公司，你应该给每个人提供工具，让他们展示他们用工具做了什么。如果你的部门有10个人，如果有7个人使用工具，而3个人不使用，那么你应该解雇不使用工具的三个人。这样才能让公司取得成功。

I know this sounds crazy. But this is exactly what I saw happen in the early 90s. We put PCs on people's desks. Some people literally did not want a PC on their desk. They wanted their secretary to have the PC. And those people lasted, I think, you know, less than a decade in corporate America.

我知道这听起来很疯狂，但这就是我在90年代初看到的情况。我们把PC放在人们的桌子上。有些人实在不想在他们的桌子上放上一台PC，他们想让他们的秘书使用PC。但这些人不到十年就在公司里消失了。

And that was back then when, you know, you got to keep your job for a long time. There wasn't as much turnover for boomers. But there were boomers who were like literally when I was installing computers in the early 90s who were like, yeah, just I don't want the computer. You can, don't put it on my desk, put it on this like little cubby over here in my law office and my system will do it. And they never logged in. And those people got phased out. They were relationship people. If you're not using this every day, you're, you're literally a dinosaur. You're literally a dinosaur. That's my belief.

那时候，您知道的，保持工作时间很长。对于婴儿潮一代来说，没有那么多人员流动。但是，有些婴儿潮一代人在90年代初安装电脑时，就像字面意思一样，他们说：“不，我不要这台电脑。你可以把它放在我律师事务所的这个小隔间里。我的系统会处理它。”他们从来不登录。这些人被淘汰了。他们是关系型人才。如果您每天不使用这台电脑，您就是真正的恐龙。这是我的信念。

So you're exactly correct. This will be make every company 30, 40, 50 percent more efficient. And then what you have to ask yourself is, are there enough problems in the world that your company addresses for you to solve to generate revenue and a capitalist society? I believe there are decades of problems left. I don't think that this is going to result in a UBI universal basic income where all the jobs are done.

所以你说得完全正确。这将使每个公司的效率提高30、40或50个百分点。接下来你要问自己的是，你的公司解决的问题是否足够多，以便你能够解决这些问题并在资本主义社会中产生收入？我相信还有几十年的问题需解决。我不认为这会导致全民基本收入（UBI），所有工作都由机器完成的情况。

I think humans are going to be creative and find more things to do. But I literally believe efficiency of 5 percent gains per year for humans. Let's say if everybody got, maybe let's say everybody got 10 percent. And every year, every seven years people doubled their efficiency.

我认为人类会变得更有创造性，找到更多的事情来做。但我实际上相信人类每年的效率只能提高5％。比方说，如果所有人都能提高10％，而且每七年人们的效率都会翻倍。

I think what we're going to see is everybody's going to become 10 percent more efficient, like a month or let's say quarter, which means every seven quarters, every year and nine months, people are going to be twice as efficient.

我认为我们将会看到每个人的效率都会提高10%，相当于一个月或者一个季度的时间，这意味着每七个季度，也就是每年九个月，人们的效率将会提高一倍。

What do you say, sunny? Well, I think there's a great example, Jay, Cal. And I've seen it, but Nick, if we can pull it up in terms of efficiency. So this is someone who's working on a do not pay plug-in. Oh, Josh Brown. He's not a program. Yeah, yeah. No, there you go.

"你说什么，Sunny？嗯，我认为Jay和Cal有一个很好的例子。我也看过，但是Nick，如果我们能提高效率就更好了。这是一个正在开发不支付插件的人，Josh Brown。他不是程序员。是的，就是他。" 这段话的意思是在讨论一个叫Josh Brown的人正在开发一个不支付插件，并且提到了他的职业身份，另外也在放心说他就是那个人。

So maybe Jay, just, you know, Josh Brown or his billbrow. I don't know if you're going to be able to do that or who wrote the book Red Notice's son. He's an entrepreneur. And he has do not pay his name of company. He's been on the podcast. And his whole thing was to help you like get out of like reoccurring subscriptions, et cetera.

也许是Jay，你知道的，Josh Brown或者他的账单Brow。我不知道你是否能够做到这一点，或者谁写了《红色通缉令》这本书的儿子。他是一位企业家，拥有一个名叫“Do Not Pay”的公司。他曾经在播客上出现过，他的主要目标是帮助你摆脱像重新订阅之类的重复的订阅服务。

But he's also a good. So let's do a reaction thing, Jay. Cal, why don't you read this because you've seen it. So go for it. I haven't seen this. So what did it say? Okay.

但他也是一个好人。所以让我们来做一个反应的事情，杰伊。卡尔，你为什么不读一下，因为你已经看过它了。所以就这样吧。我还没有看过这个，那么它说了什么？好的。

So this is, you know, do not pay. It's an app on top of a chat GPT leveraging it and goes, ask, how can I help you? He says, find me money is it connect the apps is connect your bank account, he connects account. And then it finds the subscriptions that this person is paying it. It's whatever. And it says, what do you want to do? Is this like a cancel? Yeah. Yep. Okay.

这是一个不需要付费的应用程序，它在聊天GPT的基础上进行了优化，通过问“我能帮你做什么？”来帮助用户。如果用户说“找钱”，那么应用程序会连接他的银行账户，并查找他正在支付的订阅。然后它会问用户想要做什么，是取消订阅吗？是的，没错，好的。

So let's go to the next spot. Incredible. Okay. And then this he says, first using do not pay at plaque connection. I had. It's scan all about 10,000 bank transactions. So it found $80.86 leaving his account every single month and offer to cancel, offer to cancel those. Great. Right. Let's keep scrolling. Okay.

那么，我们继续去下一个地方吧。太不可思议了。他说，首先使用不要在牌匾连接处支付。我有一个扫描了大约10,000笔银行交易的工具，所以发现每个月从他的账户离开了80.86美元，并提供取消这些交易的选项。太好了。继续滚动吧。

And the bots basically got working mailing letters in the case of gyms. Right. And it used a USPS API and chatted with the agents to basically start working on the cancellation. And so like we can scan through this and we'll maybe drop the link of the notes. But the beauty here is going back to efficiency. Think about the time and effort. There's one last example. If you can go back there Nick where it actually found a bill for a Wi-Fi connection. And he it turned around and asked, hey, was that did the Wi-Fi work properly? And he said no, it drafted a letter to send to go go whoever the Wi-Fi company was and asking for a refund for that.

机器人基本上开始工作，发送邮件来取消健身房的会员资格。它使用了USPS API，并与代理商聊天，开始工作。我们可以浏览这一切，我们可能会放下笔记的链接。这里的美妙之处在于效率。想想时间和精力吧。还有一个例子。如果你可以回到那里，Nick找到了一个Wi-Fi连接的账单。他转身问：“嘿，Wi-Fi运转正常吗?”他回答说:“不是”，然后起草了一封信，发送给Wi-Fi公司，请求退款。

And we all experience that where we pay for it and it doesn't work or it's bad. And basically, yeah. And so there's similarly negotiation process to cancel that and get a refund. Yeah. And then similarly it started a negotiation process for with Comcast. It's just that's what I'm saying, Jacob, where these are apps that are being built on top of the technology. So we are almost where you're talking about. So it's a less than 90 days away from incredible things happening for us, which then aligns the deflationary argument. It's definitely going to be super deflationary.

我们都经历过付钱却发现服务或产品不起作用，或者不好用的情况。基本上，是这样的情况。所以，如果要取消服务并获得退款，就要进行类似的协商过程。同样，我们开始了与康卡斯特的协商。就像我所说的，这些应用程序是建立在技术之上的，我们几乎就要达到你所说的那种程度了。因此，在不到90天的时间内，我们将迎来一些令人难以置信的事情，这与通货紧缩的论点是相符的。它肯定会极大地发挥通货紧缩的作用。

If you hear my voice, you know, like and you're not using this and you're not getting up to speed on it, man. Yeah. You're not really following how fast this is. I started playing with I'm giving a speaking gig on Wednesday in Laguna down in the Orange County, doing my paid speaking gig being corporate gig and I'm talking about travel. And so I started testing some I was like, you know, in this luxury hotel kind of situation. I would say which one? Okay. But let me share my screen here.

如果你听到我的声音，但你还没有使用这个，也还没有迅速了解它，那么你可能不知道这个东西有多快。周三，我将在橘郡的拉古纳（Laguna）进行我的付费演讲，是一个公司的演讲，我将谈论旅行。因此，我开始测试了一些在豪华酒店的环境中的演示。我可以告诉你酒店的名字，但现在让我分享一下我的屏幕。

So I started using the GPT forward browsing. Browsing. Web browsing. I don't know if you play with this, but it doesn't work very well. I had said on all in in Shamaaf and sax laughed about this that, hey, you're going to need to start citing your sources and then getting permission from them, et cetera, where else this thing is going to become normally and all these lawsuits have already been filed. But when you hear I said, what are the major trends in luxury hotel travel and it started a browse. And I guess it did a search and it said search major trends in luxury hotels 2023.

所以我开始使用GPT前向浏览。浏览。网络浏览。我不知道你是否尝试过这个功能，但它并不是很好用。我曾在Shamaaf上说过，萨克斯嘲笑过我，说嘿，你需要开始引用你的来源，并得到他们的许可，否则这个东西会变得普通，所有这些诉讼已经被提起。但当你听到我说，奢华酒店旅行的主要趋势是什么，它开始搜索。我猜它进行了一次搜索，并且显示了搜索奢华酒店2023年的主要趋势。

We found this link from a website, EHL and then it read the content. Yeah, a bunch of failures. It's not working very well. Their web crawler is terrible or it's really taxed. I don't know what's going on. My team today has been playing with the web crawler, but I only found this one. And then it basically just cribbed it. So now you can kind of see what's happening with chat GPT for. It is cribbing a lot of data and just rewriting it. And then it does some thinking on top of it.

我们从一个网站EHL找到了这个链接并读了它的内容。嗯，一大堆失败。它的网页爬虫不太好用，或者它的负担太重了。我不知道发生了什么。我的团队今天一直在与网页爬虫玩耍，但我只找到了这个。然后它基本上只是抄袭了它。现在你可以看到聊天GPT在做什么。它正在抄袭大量的数据并简单的重新编写它。然后在此基础上进行一些思考。

Well, I want to clarify something. This is so in the case when you're without the plug in, you're asking for something, then the cribbing is not occurring. And I think that's a discussion that's happened before. In this particular case, you're asking chat GPT to go look for something with the browser plug in. So then it will crib. It's two very different use cases that we have to be aware of here. So anyway, this EHL insights had written this. And you know, you can see it basically took what they had on their website and it summarized it a little bit better.

我想澄清一些事情。在您没有插件的情况下，您要求某些东西，那么就不会发生抄袭。我认为这是以前讨论过的问题。在这种特殊情况下，您要求聊天GPT使用浏览器插件搜索某些内容，那么就会发生抄袭。这是两种非常不同的用例，我们必须在此意识到。总之，EHL Insights撰写了这篇文章。您可以看到，它基本上是对他们网站上的内容进行了总结，概括得更好一些。

And then way down here, it gave a citation. You see that 12? It gave a little tiny citation. And then I said, which hotel chains are known for having the best hotel workspaces? And then offer dedicated work desk and high speed internet over ethernet connections. And it started browsing the web. It's actually doing it right now because it failed so many times. But I want to show you another one I did here.

在网页往下翻了一些，我看到了引用。你看到那个数字12了吗？它就是一个小小的引用。然后我问，哪些酒店连锁店被认为具有最佳的酒店工作空间？并且提供专门的工作桌和高速以太网连接的互联网。然后它开始浏览网页。实际上，它现在正在这样做，因为它失败了很多次。但我想向您展示我在这里做的另一个。

And this one was a fascinating. And I said, what are the major trends in luxury hotels? And it gave me up to September 21, this is without doing web searching. Personalization sustainability, wellness, authenticated experience, smart technology, blending home, blending work and leisure, unique design and architecture, multi-generational appeal, privacy and exclusivity partnerships. So I said, which three of these are the most important for maximizing a hotel's loyalty and revenue? So I'm asking you to think, you know, a bit here. And it said personalization smart technology and authentic experiences.

这是一个很有趣的话题。我问：“豪华酒店的主要趋势是什么？”它告诉我截止到9月21日，而且这还没有进行网络搜索。趋势包括：个性化、可持续性、健康、真实的体验、智能科技、融合家庭、融合工作和娱乐、独特的设计和建筑、跨代吸引、隐私和独家合作关系。我问：“其中哪三个最重要，可以最大化酒店的忠诚度和收入？”所以我要求你有点思考。它告诉我：个性化、智能科技和真实的体验。

And I was like, the first two definitely authentic experiences. I don't know if that's actually like, culturally immersive activities, genuine connecting to the destination. I was like, I don't know. It feels a little woke to me. I was like, what's the opportunity? I was exactly what I took my time with. I was like, what's the time? I was like, please give me 10 examples of how a luxury hotel might personalize a hotel guest's experience. So I just went after the personalization.

我认为前两点是确实的经历，但我不确定是否真正沉浸在文化中、与目的地真正的连接。我认为这听起来有点"觉醒"。我的问题是，这个机会是什么？我花费了时间来思考，我想知道它的时间价值。我请他举出10个豪华酒店如何个性化招待客人的实例，因为我想追求个性化的服务。

And this was incredible. Like, I don't know where it's getting all this from. Like, is it from its web crawl, you know, but it said pre-arrival communication, customized welcome amenities like a favorite drink or snack, tailored room setup, like temperature, preferred lighting, curated experiences, personalized dining options, customized spa treatments, dedicated, conscious service, flexible room configurations, tailored in-room entertainment, personalized turn down service.

这太不可思议了。我不知道它从哪里得到了这些信息。它是从网络爬虫中获取的吗？但是它说提供了抵达前的沟通、个性化迎宾礼物如喜欢的饮料或小吃、量身定制的客房设置如温度、光照、个性化餐饮选择、私人定制Spa护理、专门的、周到的服务、灵活的客房布置、个性化的客房娱乐、个性化的回头服务。

I said, you know what, expand that list of 25 ideas. And it just went to town, you know, and customized mini bar. I'm like, well, that's a great idea. I've never experienced a customized mini bar. I've had an idea before personally. Personalized is a wellness programs, customized transportation options, customized bedding and little linens. I've heard about that. Actually, Chimoff has that at the peninsula where they have CP pillowcases with his initials on them. So he had talked about that pet friendly personalization, scent experiences. That's dumb, but interesting. Personalized communication. They do that in Vegas. They do that in Vegas. Yeah. Communicate with guests with their preferred channels, such as text, email or phone. That's actually a really important one.

我说，你知道吗，把那个25个想法的列表扩大一下。然后就开始涌现了，比如定制迷你酒吧。我觉得，好主意，我从没享受过定制迷你酒吧。我个人曾有过其他想法，比如个性化健康项目、定制交通选择、个性化床上用品和小饰品。我已经听说过这些了，比如Chimoff在半岛酒店用CP枕套印有他的姓名缩写。他也谈到过宠物友好的个性化、香气体验。这听起来有些愚蠢但也很有趣。还有个性化通讯，拉斯维加斯就有这个。他们会用客人喜欢的方式（短信、邮件或电话）与客人联系。这其实是一个非常重要的点。

Everybody's got a different one. So then I was like, okay, well, let's take this to the next level. And I said, let's see if we can set up a scenario where we tell it, you know, to pretend it's something. I said, you are the CEO of a hotel chain. You're building a hundred room hotel. Take these top trends and write a three paragraph, 400 word description of this new hotel. Follow that with 10 bullets about what makes this hotel unique. And it does this. Introducing the premier destination for discerning travelers are 100 room luxury hotel expert leaf uses modern technology. Personalized experiences and authentic cultural immersion created truly unparalleled parallel retreat from the moment's guest arrived. They are welcome into a world of bespoke services and innovative amenities, all meticulously designed to cater to the individual preferences and needs.

每个人都有不同观点。所以我就想，好吧，让我们把这个推到更高的水平。我建议设置一个场景，告诉它假装成某件事情。我说，你是一家酒店连锁店的CEO，你正在建造一家100间客房的酒店。采用这些最新的趋势，撰写一个包含三段、400字的关于这家新酒店的描述。接下来，再列出10个标点符号，介绍这家酒店的独特之处。它是这样实现的。引入专家树叶迎接挑剔的旅行者的首选目的地——一家100间豪华酒店。使用现代技术、个性化的体验和真正的文化融合，从客人到达的那一刻起，创造出无与伦比的撤退场所。他们将迎来一个专门设计，精心规划的服务和创新设施的世界，所有这些都是为了满足个人喜好和需求而准备的。

It was like really like well written, et cetera. And then it gave like, you know, their top 10 bespoke guest experiences state of the art technology. Yeah. I said rewrite that in half the number of words. And so it's in half the number of words. So it was a little tighter. And then I said, okay, you're a branding executive who has been given the description and location on a beach in Southern California. And you're being paid to name the hotel. It was four ideas came up with terrible ideas. So Cal Serenity Retreat Pacific Sands Haven Coastal Bliss Retreat Azure shoreline sanctuary.

这段话是在描述看到一份精美的文件，并列出了十项针对客人的个性化体验，同时使用了最先进的科技。接着，要求将这段话的字数缩短一半，使其更紧凑。然后，假设你是一个品牌执行官，要为一个位于南加州海滩的酒店起名字，你提出了四个糟糕的主意：So Cal Serenity Retreat，Pacific Sands Haven，Coastal Bliss Retreat，Azure shoreline sanctuary。意思是作者看到一份文件，里面列出了十项客制化的体验服务，采用了最新的科技，非常出色。同时，作者提出了一项挑战，要把这段话减半，并以品牌执行官的身份为一个南加州海滩的酒店想一个名字，但他提出的四个主意都很糟糕。

I said, please do that again and come up with one word names. Microsoft sponsored number four. Exactly. So it came up with wave crest sun haven tied song and beach was much better. Much better. Like that. And then I said give me four more, but none of the names should include beach water or wave concepts because I was like, that's too obvious. Well, I like Elysian. Yeah. Zephoria Elysian Solsthi Eden Vista. And this is where I left off in this insanity.

我说，请再来一遍，并想出一个词的名字。微软赞助的第四个。没错。于是它想出了浪尖阳光港、绑定歌曲和海滩，这个更好了。更好了。就像这样。然后我说再给我四个，但是这些名字不能包含海滩、水或浪概念，因为我认为那太明显了。嗯，我喜欢Elysian。是啊。Zephoria、Elysian、Solsthi、Eden Vista。这就是我在这个疯狂计划中停下的地方。

Yeah. So Jacob, can I challenge something that you said you said 30% more efficient. Yeah. If you ask someone on your team to do that, that's more than a day of work, including the back and forth with you. I would say an average college educated person getting paid the average national salary for an operations position or an administrative assistant position, like a non-programming non-sales position is 60,000 a year, 70,000 a year, which if you divide by 2000, you know, is something in the range of 30 to 50 dollars, right? Yeah, that's 50 hour.

是的。Jacob，我可以挑战你说的那句话吗？你说能提高30%的效率。如果你要求团队中的某个人做到这一点，那么包括与你来回沟通的时间，至少需要超过一天的工作时间。我会说，一个受过大学教育的人，拿着操作职位或行政助理职位的平均国家薪资，也就是一个非编程或非销售岗位，年薪应该是60,000到70,000美元，如果你将其平均分为2000，那么就是每小时30到50美元左右。是的，也就是50美元的时薪。

I think they would say 50 hours of work to put that presentation together. And to get that level of output because you would be starting from zero, you would basically surf the web for 20 hours. You would write down all your ideas. You would go eat a bunch of bagels and donuts and you'd have come up a meeting with you. And then you'd say, oh, that's too long. Make it shorter. I don't like these names. Come back. Yes. You'd have these each time. It's 50 minutes.

我认为他们会说需要50个工作小时来制作那个演示文稿。为了达到这种输出水平，因为你是从零开始的，基本上你需要浏览网络20个小时。你需要把所有的想法写下来。你会吃一大堆百吉饼和甜甜圈，然后会安排一个与你的会议。然后你会说，哦，时间太长了，让它变短一点。我不喜欢这些名字。再回来。是的，你会有这些需要每次解决的问题。它需要50分钟。

30 minutes is an interaction with you. Yeah. 50 hours of work. I put it out. Times 40 bucks is $2,000. Maybe a hundred hours of work. Yeah. And then forget about asking them to come up with names. You know, that's like a very specific thing. That's an agency which charge you $20,000 for those four names at the end, I think. Yeah. And so it's not 30 percent more efficient. I think it's 300 percent.

30分钟是与你互动的时间。是的。我花了50个小时的工作时间。40美元为倍数，就是2,000美元。可能需要100个小时的工作时间。是的。然后不要指望他们能提供名字。你知道，那是一件非常特定的事情。我认为那是一个代理机构会收费20,000美元最终给你起4个名字。所以它不是比效率提高了30％，我认为是提高了300％。

Yeah. I can be wrong. Then I wonder if the gains are sustained because these feel like early gains. So now my question back to you, Sonny, is are these like massive gains, 300 percent gains for the first year of AI and then we get to 30 percent a year? Or is it compounding and 300 turns into 3,000?

是的，我也可能错了。那么我想知道这些收益是否可持续，因为这些收益感觉像是早期的收益。现在我又回问你，Sonny，这些像是巨大的收益，第一年AI增长了300％，然后我们每年只增长30％？还是这些收益会持续复合，300％会变成3,000％？

That's a good question. I hadn't thought about it. But my guess is, you know, this is hard. Well, when the iPhone first came out, right? And even to this day, and we don't get as many Uberers and Airbnb's, but it's still it's still compounding on itself. Yeah. We're 10 plus here, I mean, we're 15 years in, we're saying 10, right? Yeah. We're 15 years in and an iPhone still compounds. Crazy. Yeah. So I think it compounds.

这是一个好问题，我之前没有考虑过。但我猜，你知道的，这很困难。当 iPhone 首次推出时，对吧？甚至到现在，我们没有接到那么多的Uber和Airbnb，但它仍然在不断扩大影响。是的，我们现在已经超过了10年，我是说15年了，但 iPhone 仍然在不断扩展。太疯狂了。所以我认为它是不断扩展的。

This is back to the whole thing with like human beings are really bad at being able to see like the compounded growth charts. Like we, you know, exponential growth, when it's sitting right in front of us over the three months or six months, we can't imagine how far this thing's going to grow. We have brains on why to understand the curve.

这个话题是关于人类在看到复合增长曲线时很不擅长的问题。我们很难想象在三个月或六个月内，一个指数增长的东西会变得这么庞大。我们的大脑难以理解这个曲线。

Yeah. That's really, yeah, we have an evolutionary, not an exponential mindset. Exactly. Exactly. We only understand evolution. And even evolution took thousands of years for humans to experience.

是的，那真的是这样的，我们有一个进化的思维方式，而不是指数型思维方式。确实，确实。我们只理解进化。即使进化也需要几千年时间才能被人类经历。

Yeah. The idea that we evolved from primates and primates evolved from, you know, reptiles or whatever. I don't know what the exact forking was. That took thousands of years for us to understand this.

是的。我们从灵长类进化而来，而灵长类则从爬行动物或其他动物进化而来，我不清楚精确的分支情况。我们花了数千年的时间才理解这一点。

But if we have three billion people, three to four billion people who are, I would say, you know, activated in the global economy. So they have an internet connection. They have it, you know, they have access. Like it's a highly networked place. Like we think about this, right? Like a hundred years ago, I mean, the most connected network of people, maybe people living in New York or London or like, yeah, that's maybe a hundred thousand people.

但是如果我们有三十亿人口，在全球经济中都能参与的话，这就意味着他们可以连接到互联网，他们有接入设备。我们可以想象，现在的世界被高度网络化了。但是，如果想象一下一百年前，最高度网络化的人口可能只有纽约或伦敦等地的十万人。

Yeah. It was separated by obviously distance. And maybe, you know, what's the telephone? That knowledge. Yeah. And it's an access. And with the telephone came up, now you had like a wider connection. So you could access people, you know, over space and time quicker. But that, you know, it took airplanes. It took for airplanes, trust me.

是的，它显然被距离隔开了。也许，你知道电话是什么吗？那个知识。是的。它是一种接入方式。随着电话的出现，你现在可以更广泛地连接人们，更快地跨越时空进行接触。但是，你知道，这也需要飞机。相信我，需要飞机。

Now we've got, now we've got this. I mean, this is thinking. This is like taking the number of people. Like if you like work out some sort of, let's just say, for example, you said the number was, you know, this is, it's a hundred million people 20 years ago squared was the number, right? Now it's, yeah, and then you bring the 18, that's what it was, right? Now you've got three billion people squared.

现在我们有了这个。我的意思是，这是在思考。就像是在统计人数一样。比方说，如果你计算出了一个数字，比如二十年前有一亿人，那么现在这个数字是这个数字的平方，然后再乘以十八就是现在的人数了。现在我们有了三十亿人的平方。

Like that number is, or is a magnitude more than a hundred million squared. It's insane.

这个数字就像超过一亿的平方倍数一样巨大，简直是疯狂的。

What's really going to happen here, I think is such a great point is, think about the, the impact of giving somebody internet access, then high speed internet access. Now you give them this. So for somebody who's a knowledge worker, I said, oh, 30% more efficient. And suddenly said 3000. And now imagine you are a person 300, 300% sorry, 300%. Now you're a person in San Paulo. And you just, you had low speed access sometimes flaky internet access. Now imagine you get a Starlink connection and you've got a hundred megabits down and you get Cheshire beauty for.

我认为真正会发生的事情是，考虑给某人提供互联网接入，然后是高速互联网接入的影响是非常重要的。现在你给了他们这个。对于一个知识工作者来说，我说，哦，他们会提高30%的效率。突然地变成了3000。现在想象一下，你是一个在圣保罗的人。你只有低速的互联网接入有时候不稳定。现在想象一下，你得到了Starlink的连接，你可以获得100兆位的下载速度，你可以享受别样的网络美好。

And instead of you having to figure stuff out, you start asking a questions like this. And you ask it, okay, how do I create a hotel chain? How do I name a hotel? You start asking these questions, or how do I code? And it starts teaching our code. This is crazy. Like those people are going to experience, they're going to be comparable to somebody who is educated in New York at NYU or in Boston at Harvard, like the ability to close the gap in knowledge and ability. And network is crazy. Just like LinkedIn made it possible for I get people emailing me from Hong Kong or Australia because they found me on LinkedIn.

而不是让你自己摸索，你开始提出这样的问题：我如何创建一个酒店连锁品牌？我怎样给酒店起名？你开始问这些问题，或者说我怎样编程？它会开始教你编程。这很疯狂。像那些人将会体验到，他们将会与在纽约的NYU或哈佛大学在波士顿接受教育的人相媲美，他们缩小了知识和能力的差距。而且网络也非常疯狂，就像 LinkedIn 让那些来自香港或澳大利亚的人通过 LinkedIn 找到我一样。

But yeah, this is, it's hard to comprehend. It's when a billion people have access to this.

但是，这很难理解。当十亿人都可以接触到这个时。

So if you're taking down to like the biological compute stack of the human being, right? You've got this like ability to store data in our brains and we have ability to compute data. And so what's happened over the first, you know, the internet in the first 20 or 30 years, I'd say let's say the last 20 or 30 years on the internet was that we basically all floated and with mobile as well. We've all floated the storage layer to the internet. So whatever you wanted to know something, you didn't have to remember all these facts and figures. You had a Wikipedia, you searched, you find this information and we just did the compute on that. That's how we did research.

如果你所说的是人类生物计算层面的话，我们有存储数据的能力和计算数据的能力。在过去的20到30年里，特别是随着互联网的出现，我们已经把存储数据的工作都转移到了互联网上。现在只需要在维基百科等网站上搜索你需要了解的事情就好了，我们只需要从中进行计算，这就是我们进行研究的方式。随着移动设备的普及，这种趋势变得越来越明显。

You know, get this in fact, stake hours and hours to find the data. And then we go interpret that and see what it produces and then we'd like to apply it in our lives with this business or personal.

实际上，你知道的，我们花费了数小时的时间去寻找数据。然后我们会解释它并看看它会产生什么，然后我们想将其应用于我们的商业或个人生活中。

What what what open AI and check to be T and AI in general is doing is basically, you know, the compute function for the human brain is being now is the same process is happening to the story. So so now we've got storage on the internet and now we've got compute on open AI.

开放人工智能（Open AI）和普遍人工智能（AI）的所做的事情基本上就是模拟人脑的计算功能，现在这个过程正在发生在存储器上。因此，现在我们在互联网上拥有存储器，在开放人工智能上拥有计算能力。

So the human brain now is not is no longer about doing compute. Like we're not going to sit there. I'm not going to take a spreadsheet and do the graphs and do the analysis and trying to figure out the financials of a company now.

因此，人类的大脑现在不再是在进行计算。就像我们不会坐在那里，拿着电子表格做图表、分析并试图理解公司的财务状况。

I'm going to take the company financials, stick it into open AI and say, okay, this public company, you know, based upon Buffett's methodology, how would you value this if you saw sales growing at 20% faster than the current projections. It would do all the calcs for me.

我准备将公司财务数据输入到开放式人工智能中，然后问它：“如果你看到销售增长比当前预测的快20％，根据巴菲特的方法论，你会如何评估这家上市公司？”它会为我自动计算所有参数。

It would come back and say, yeah, actually, you know, based upon the Buffett style of investing, this is a great investment. I know it's a really shitty investment. And that happens in minutes. I can analyze the entire company's financial statements in minutes. And that's what I wanted.

它会反馈出来，事实上，根据巴菲特的投资风格，这是一笔很好的投资。尽管我知道这是一个非常糟糕的投资。这一切只需要几分钟。我可以在短短几分钟内分析整个公司的财务报表。这就是我想要的。

So yeah, so it's the very, it's the point. So what's really what's really happening with the human brain right now. So we've all flowed the storage. We've all floated or we offloading, you know, the compute starting to want the third thing which we're not offloading and we shouldn't. And this is where the debate gets in is, is decision making, right? Because these systems are not making decisions for us. Morality ethics decision making. Exactly. Exactly.

所以，这就是要点。现在人类大脑正在经历着什么。我们已经将存储空间全部释放出来，我们也正在开始释放计算能力。但有一件事情我们不会释放，也不应该释放，那就是决策。这也是争论所在，即系统不会为我们做出决策，包括道德、伦理和决策。

And then when you have this like now, you know, it says this is what it looks like. This, this company looks like a good investment. Now you make the decision, do I want to deploy my capital in there? Now you can automate that eventually. But that's, you know, and the financial decisions are the easy one. But the morality stuff is where we're going to have these conversations.

当你像现在这样拥有这个（数据），你会知道这是它的样子。这家公司看起来是一个不错的投资。现在你需要做出决定，我是否想要投入资本进入这个公司？最终你可以自动化这个过程。但是，道德问题是我们需要谈论的问题，而财务决策是比较容易解决的。

Let me go to you, Sonny, in a second, but I just want to give a shout out to Coro's Poe. And if you, you can log into it at the web now, it's poe.com and they have something called Sage, but they also have GT before, quad plus, quad instant, Nevis AI. They got everything here. I think you can create bots. It's, they're really cooking with oil over there.

让我稍等一下，Sonny，我想先夸一下Coro的Poe。如果你想了解，你现在可以在网站上登陆poe.com，他们有一个叫做Sage的东西，但他们也有GT，quad plus，quad instant，Nevis AI。他们这里什么都有。我认为你可以创建机器人。这个公司做得真的很棒。

And it's that I asked it, what are the major trends in luxury hotels to try to, you know, do the, the core data set. And it gave me really great stuff. What they do is they highlight keywords, which is really interesting.

我曾询问过有关奢华酒店主要趋势的问题，以尝试找出核心数据集。它给了我非常好的结果。它的做法是突出关键词，这真的很有趣。

So again, you get technology, local experiences, social responsibility. And then I said, okay, give me 10 specific trends around points two and four. And I said, sure, here are 10 specific trends around personalization and technology. Again, the same as I was doing in the other chat, you'd be two, for instance, it gave me all these things.

再次强调，你可以得到科技、本地体验和社会责任。然后我问，好的，让我列出10个关于第二点和第四点的具体趋势。我说，没问题，这里有10个关于个性化和科技的具体趋势。和之前聊天时一样，举个例子，它给了我很多这样的东西。

And so then I just clicked on smart room systems because I didn't know that smart room systems was a category. But I clicked smart room systems and it appended, tell me more about to that. And it started explaining, you know, one of the key features, adjust room sliding, temperature, all that stuff. And it gives you, it gives you prompts now.

那么，我之后就点击了智能房间系统，因为我不知道智能房间系统是一个类别。但我点击了智能房间系统，它就附加了一个“告诉我更多”的选项。接着它开始解释，你知道的，其中一个关键特点是，可以调节房间里的滑动、温度等等。现在它也会给你提示了。

So it's actually telling you what to ask next. This is really getting interesting. So it's, this is pre cog. If you watch a minority report, sunny, where like, no, you're going to commit a crime. It knows what you want to do next. And it kind of gives you the next one. What are some examples, smart room systems, how they prove and nagging, say what are examples. And boom, you just keep Philip, you, so now I'm like, you start thinking about the research, again, back to your point of like, how many hours this would take.

所以它实际上告诉你接下来该问什么。这真的非常有趣。这是预言神。如果你看过《少数派报告》，它就像告诉你：“不，你将会犯罪。”它知道你下一步要做什么。而且它会给你下一个提示。例如，智能房间系统如何提高效率，并提醒你需要哪些例子。然后，你只需要继续追溯，再回到你提到的耗费了多少时间的观点。

We're going to have companies that work 20 people will be five, you know, or they'll be able to do twice as much of the way I can told my team Sunday night and this morning was if you're not using this, like you're falling behind. And I said, offload as much as you can to these systems. And let's meet with twice as many founders, like let's actually spend more time talking to founders, suppose of researching stuff.

我们即将拥有能够让20人公司只需要5人的公司，或者他们能够实现两倍的效率。周日晚上和今天早上我告诉我的团队，如果你不使用这些系统，你就会落后。我说，尽可能将尽可能多的工作卸载到这些系统上。让我们花更多的时间与创始人交流，而不是只进行研究。

All right, let's wrap up here. Any final thoughts, sunny? We got Vinnie's. I want to get your final thoughts, sunny.

好了，我们结束吧。还有什么最后的想法，大晴天？我们已经得到了文尼的意见。我想听听你的最后想法，大晴天。

How is this impacting the work you do every day and how you're looking at your entrepreneurial career and running your own company, sunny? Yeah, I mean, I think we've touched on the major points, but like for us, we think about enabling this within the enterprise. That's our primary focus. Right?

你好，Sunny，这对你日常工作、你的创业生涯以及经营你自己的公司有什么影响呢？是的，我觉得我们已经讨论了主要的点，但对于我们来说，我们考虑在企业中实现这一目标。这是我们的主要关注点，对吧？

So we think that's really important. And how do we do that in an efficient way such that enterprises can harness this? It's not as straightforward for most enterprises to just go to chat GPT4 just yet, but you know, we're working on that problem alongside it.

我们认为这非常重要。那么我们该如何以高效的方式做到这一点，使得企业可以利用这一点呢？对于大多数企业来说，现在直接转向使用 GPT4 聊天机器人还不是那么容易，但你知道，我们正在与此问题并肩作战。

I think two, what we have to kind of focus in on is how does, how do you know what it's telling you is accurate? Right? And I think we saw a few examples of that where we're kind of questioning what it's told us. Where we started today's conversation, we could see if we give it a data set, it can be very kind of definitive about it. And if not, you have to be careful on what it's telling you and where it's pulling it from. Your example of the crawl was not sort of using Vinnie's framework of memory and compute. It wasn't doing that. It was kind of doing the cheating thing of humans. And so I think I think there's a lot of opportunity here and what everyone should think about is the speed at which you can move in this environment. Right? I think in the speed forces you to basically use the technology to its maximum capability. You have the folks. You can run literally 30% faster every week, compounding week after week. If you embrace these tools and you use them, stop what you're doing. If you hear my voice, this is not a drill.

我认为我们需要集中关注的是：如何确定它所告诉你的准确性？我们在一些例子中看到了这种情况，我们开始质疑它所告诉我们的信息。我们今天的对话中可以看到，如果我们提供给它一个数据集，它可以确切地告诉我们结果。但如果没有，你必须小心它所提供的信息以及它提供信息的来源。你所提到的爬行的例子并不是使用Vinnie的记忆和计算框架。它并没有这样做，相反却采用了人类欺骗的手段。因此，我认为这里有很多机会，每个人都应该考虑的是在这个环境中你可以移动的速度是多快，这种速度迫使你将技术的最大能力用于应用。如果你接受了这些工具并使用它们，请停止你正在做的事情。如果你听到我的声音，这不是演习。

I know in technology, we get really excited and we hype stuff up. Mobile, broadband, crypto, everything, VR, AR, we hype stuff up. We're excited about it. All of that stuff, different levels of impact. This is different. This is just very different. It's compounding at a pace that I think is a self-fulfilling prophecy on the way to AGI. We're getting to artificial general intelligence. It's so clear. You're beating the touring test already. You're smashing it, being it around like a dead mouse.

在科技领域，我们总是非常兴奋地吹嘘各种事物，如移动技术、宽带、加密货币、虚拟现实、增强现实等等。我们对这些充满热情。所有这些事物都有着不同的影响程度。但这一次却非常不同，它以一种非常快的速度进行着，这种速度本身就象征着它正在实现AGI(人工通用智能)的自我应验。我们正在逐步走向人工通用智能。这一点已经变得非常清晰了。它已经打败图灵测试了。现在我们已经可以把它当成死老鼠一样随意操纵了。

If I took this and I put it into a presentation and I gave you that pitch on your luxury hotel, you would think like a bunch of McKinsey people spend three months on it. Not even McKinsey, Jacob, if we can pull up one more thing and we're running short on time here, we won't listen to it but maybe we can drop it in the notes. This developer basically built an entire Google Translate but that works. It takes an account, two of these trends. We're talking about this AI voice treatments. What it does is it takes his voice and what he's asking, translates it and then speaks it in the language that he's looking for and he's got a link to the program here. It's all open source.

如果我把这个东西放进演示文稿中，并在你们的豪华酒店上进行宣传，你们会认为这是一群麦肯锡人花了三个月的成果。不仅如此，Jacob，如果我们能再展示一件事情，我们时间有点紧了，或许我们可以在笔记中记录下来。这位开发者基本上建立了一个完整的谷歌翻译，而且它还真的管用。它采用了两项趋势，我们刚刚谈到的 AI 语音翻译。它会抓取他的声音和他所问的内容，将其翻译并用他要找的语言发音，这里还有一个程序链接，它完全开源。

This one person basically built an entire Google Translate that speaks out the translated version of what you're asking for in his voice. So I can do this week. Yes, start-ups as in Spanish, but it would be in my voice. In Spanish. It would be in your voice. It's bonkers. He built that and all the code is there and it's just incredible. Think about the armies of people. This does take at the Google's of the world or meta-sale world. It wouldn't be done.

这个人基本上建了一个完整的谷歌翻译，可以用他的声音将您要求的翻译版本说出来。所以我可以这周做到。是的，创业公司的名字是西班牙语，但它会用我的声音说出来。用西班牙语。它将是您的声音。这太疯狂了。他构建了所有代码，并且它非常令人难以置信。想想这些人的大军。这在谷歌或者meta-sale的世界里是做不到的。

I've been pitched many years for taking this podcast and now all in and making a German language version or a Spanish language version and they're like, we hire voice actors to redo your podcast every week and for 500 bucks or a thousand bucks we can make another language version of it and I'm like, yeah, and they're like, you can sell advertising. I don't have the time to do this. This seems like a lot of work. But if I could press the button and take this podcast and put it into 10 languages and then have 10 different websites with it, I would do it. Yeah, for sure. I would do it. And I would pay 50 bucks to do that. I wouldn't pay 500 though. So if somebody wants to take this episode and translate it into Spanish and then use our voices, I would pay 50 bucks for that and you could do it every week and I'd pay you 50 bucks a week.

多年以来，我已经被推销许多次，让我将这个播客全部转换为德语或西班牙语版本，他们说，我们雇用配音演员每周重新制作您的播客，花费500美元或1000美元，我们就可以制作另一个语言版本的播客，我说，恩，他们还说，您可以出售广告。我没有时间做这个，似乎这是很多工作。但是，如果我可以按一个按钮，将这个播客转换成10种语言，然后在10个不同的网站上展示，我会这样做的。是的，我会这样做，我愿意支付50美元来实现这个目标。不过，我不会支付500美元。因此，如果有人想将这一集翻译成西班牙语，并使用我们的声音，我会支付50美元，每周向您支付50美元。

I mean, that literally might do all 250 episodes a year. It wouldn't be that much money. Yeah. Not that much. 10,000 bucks. For 10,000 bucks I would translate this all into Spanish every year. So that's a business opportunity for somebody. That's not a jump change if you can automate it. Vinny, any plugs? Any plugs? Your engine? I mean, your engine lunch here. Yeah, thank you. I mean, obviously excited about what we're doing at Weightroom and really would love to see what people are using.

我的意思是，每年翻译250个剧集可能会做到。这并不需要太多的钱。是的，不需要很多。1万美元。每年我会把这些翻译成西班牙语。所以这是一个商业机会的。如果你能自动化的话，这不是个小钱。Vinny，有什么推广吗？你的引擎？我的意思是，你的引擎 lunch 在这里。是的，谢谢。很明显，我们在Weightroom正在做的事情非常令人兴奋，我真的很想看看人们在使用什么。

Tell people about what that is. Yeah, Weightroom is basically a video advertising platform that's going to be fully AI-driven. We're launching our features in May, the AI features. Our first feature will be probably catch up, which means that if you jump into a core leg with your colleagues, it gives you a summary of what just happened before you got there. And I think that that's going to be rolled up. I mean, the features are running out the next month. It's going to be pretty awesome. So check out the website, www.weightroom.com.

告诉大家那是什么。是的，Weightroom基本上是一个视频广告平台，将完全由人工智能驱动。我们将在5月份推出我们的功能，其中第一个功能可能是“追赶”，这意味着如果你和同事一起参加一个核心腿部训练，它会给你一个在你到达之前发生了什么的摘要。我认为这将是一个很棒的功能。我认为这些功能在接下来的一个月内推出后将会非常出色。所以请访问我们的网站：www.weightroom.com。

I will say that in building weightroom now on, we're using OpenAI. It's really interesting because as we start working with companies to understand what their businesses are about, and integrating into their sales force and notion, et cetera. We may have to start building our own custom LLM. It's just basically understand how to take conversations and meld them into something more useful to the company because you need context around what the company does and training the language to understand the company better. We're using OpenAI right now. Maybe it evolves so fast we don't need to, but it's something that we think about building features.

我要说的是，在建造健身房的过程中，我们正在使用OpenAI。这非常有趣，因为当我们开始与公司合作了解他们的业务并融入到他们的销售部门和概念中等等时，我们可能需要开始构建我们自己的定制LLM。这基本上是了解如何将对话融合成对公司更有用的内容，因为你需要了解公司所做的事情并训练语言更好地理解公司。我们现在正在使用OpenAI。也许它发展太快了，我们不需要，但这是我们考虑构建功能的事情。

You have to ask yourself, is it some of your building, which is LLM sort of agnostic, or is it caught your business? I'm very interested in what happens over time, where the companies build their own ones, or take open source one, fork it, and build some customized ones, or you use the standard one.

你要问自己的是，LLM是一种agnostic建筑，还是适合你的业务？我非常关注公司在未来的发展，是建立自己的一套系统，还是采用开源系统并分叉，然后构建一些定制的系统，或者使用标准的系统。

If there's a cloud available, unless you're Dropbox or YouTube, you're going to rack your own storage. But if you're below Dropbox or Box, you're going to just use Cloud Storage. Well, the data privacy issues as well, and I know that OpenAI has tried to deal with that, but some companies probably wouldn't feel comfortable with, you know, your own platform. You just do on Cloud 5. And then if you do that, then you have to have your own LLM, because you can't really use OpenAI for on-prem. Maybe you can. Do they have on-prem? They do. They have versions now that allow you to do the demo. So any blogs? Any blogs?

如果有云存储可用，除非你是Dropbox或YouTube，否则你需要自己处理存储问题。但如果你不及Dropbox或Box，你只需使用云存储。另外，数据隐私问题也很重要，我知道OpenAI已经试图解决这个问题，但有些公司可能不放心使用你自己的平台。因此，你可以在云端做到这一点。但如果这样做，你需要自己拥有LLM，因为你不能真正使用OpenAI的本地部署。也许你可以。他们有本地版本吗？他们现在有允许你进行演示的版本。那么有任何博客吗？

Yeah, like definitive AI. A lot of stuff that we're looking at here today, which is enabling that within the enterprise.

是啊，就像决定性人工智能一样。今天我们正在研究的许多东西，都在企业中实现了这一目标。

So reach out if you want to do that with your own privacy. We'll see you next time on The Sweetest Service. Bye.

如果您想在保护自己隐私的情况下进行此操作，请与我们联系。下次在最甜服务中见。再见。