Mark Cuban: AI Hype vs. Reality, OpenAI "Shitting Away" $1 Trillion, Lebron vs. Jordan

现在根本不用了。

Not anymore.

确实不用了。

Not anymore.

对吧？

Right?

要是你连这点意识都没有，不愿意直接去用Claude学学怎么做最简可行产品MVP，那我肯定不会给你投钱的。

And if you're not willing or don't realize that you could just go to Claude and learn this stuff and do an m v a minimum viable product, then you're not somebody I'm going to invest in.

因为不管你是创业者、上班族还是学生，身上最值钱的能力就是好奇心。

Because the number one, skill set that you can have as an entrepreneur or as an employee or as a student is curiosity.

而要说有什么能满足好奇心、还能一直保持这份求知欲，AI绝对是最好的选择。

And there's no better way to fill that curiosity and keep you curious than AI.

我年轻那会儿，为了看书只能泡在书店的过道里，翻那些买不起的书；要么就泡图书馆，都一样。

I mean, when I was younger, I used to go into bookstores and sit in the aisles and look at the books I couldn't afford to buy or go to a library, same thing.

后来互联网普及了，大家就跟现在一样，一上网就忍不住在各种内容里越陷越深，跟掉进兔子洞似的停不下来。

Where then, you know, like many of us, when the Internet hit, it'd be like, okay, and you find yourself going down these rabbit holes on the Internet.

但现在快多了，也简单多了，直接多了。

But now it's just so much faster, easier, more direct.

这只是一个更好的工具，你得学会怎么用。

It's it's just a better tool that you need to learn how to use.

还有另一方面，市场一直在打压软件股，因为现在做软件太容易了。

There's one more side to this, which is that the market has been really punishing software stocks because it's become that easy to build software.

我觉得投资者渐渐明白，这些新开发的软件虽然能快速扩张，但从来没法完美贴合用户的真实需求。

And I think one of the things investors have realized is that all this software that's being built is built to scale, but never perfectly suits people's needs.

对。

Right.

其实呢，

There's a

AI 完全有机会打破这种局面。

lot of room to disrupt them with AI.

你完全可以做出更多定制化的软件。

Potentially, you can have a lot more custom software

没错。

Exactly.

他们管这叫SaaS末日。

And they're calling it the SaaS apocalypse.

对。

Yeah.

你觉得这次抛售有道理吗？

Do you think that that sell off is justified?

有道理，但也不全有。

Yes and no.

得看是哪家公司。

Depends on the the company.

对吧？

Right?

等等。

So wait.

这太好了，我很想知道哪些公司能挺住，哪些会被淘汰。

That's great because I'd love to know who is safe and who's gonna be disrupted.

没错。

It's a yeah.

不管怎样，我是打算进场的。

Anyways, I'm a go there.

那这些公司的基本面上，你觉得怎么样？

How about how about just the fundamentals of these type of companies?

对。

Yeah.

不对。

No.

你得有独一无二、别人拿不走的知识产权。

What you gotta have is some unique IP that is not shared.

明白。

Okay.

我给你举个例子，有个公司叫DocuSign。

So I'll give you an example, a company called DocuSign.

对吧？

Right?

我们平时签的所有文件，你可能觉得这事儿挺简单，毕竟Adobe那些公司也干这个。

All the things that we sign, you would think that's easy because there's other companies, Adobe and others who do all that.

但DocuSign是全球业务，每个城市、每个州、每个国家的法律对合同签署的要求都不一样。

But it's a global company and all the laws associated with signing a legal document are different from city to city to state to state to country to country.

你得把所有这些规矩都摸透。

And you have to know all those things.

所以这才是真正的核心优势，你可不能指望AI来帮你搞定这个。

So that's a unique differentiation that you don't want to be dependent on the AI having right.

没错。

Mhmm.

这就是一个典型的例子。

So that's an example.

那我们再快速回一下刚才的话题。

So back on that quickly.

AI代理会自己去查当地的法规，

It's just that the AI agent will go and find the local regulations

然后直接用上。

and then put it.

不行。

No.

但你得先动手啊。

But you've gotta go.

你得知道该往哪儿发，又让它干啥？

You gotta know where to send it to go first and you what are gonna have it do?

得爬遍每个国家、每个州、每个城市的每一个行政区。

Spider every single municipality in every city, in every state, in every country.

这成本比它带来的价值还高，根本不划算。

It's just not it'll cost you more in tokens than it will in value.

对吧？

Right?

那样你才能真正拿到价值。

Then you'll get value.

所以我觉得，如果一家公司的软件里头有独家数据——我不是说那种‘我们的软件更好更快更便宜’的普通优势，我是说那种别处根本拿不到的专有数据库。

So I think if a company has IP that as part of their software, and when I say IP, not just, okay, our software is a little better, faster, cheaper, more this is a database of things that you can't get anywhere else.

他们没把这些数据开放给AI去训练。

That they're not making available to to AI to be trained on.

这可是他们的机密信息。

It's their classified information.

那这样的公司就没事。

Then I think those companies will be okay.

但如果他们只是靠普通软件混日子，那可就真麻烦了。

If they just, you know, if they're just sold by the seat and it's just a standardized piece of software, they're in deep doo doo.

是的。

Yeah.

之前有传言说Anthropic要推出一个法律领域的插件。

When Anthropic, there was a rumor that Anthropic was gonna release a legal plug in.

对。

Mhmm.

整个法律软件市场一下子就没了。

The entire legal section of the software market just went poof.

没错。

Yep.

不过这好像不太明智，毕竟他们手上有不少 proprietary 的信息。

But that that does seem like, though, maybe that's ill advised because they do have proprietary information.

但那些资料不都是来自Pacer和其他法律数据库吗？

Well, yes or no because all those are coming from Pacer and other legal databases.

对吧？

Right?

嗯，明白了。

Okay.

对吧？

Right?

因为我之前也跟一家律所聊过，正好在谈类似的事。

Because I I talked to a law firm because I was having the same type of conversation.

我就问：能不能把你们所有的法律简报啊、文件啊，拿来做训练？

And I'm like, can we take all of your, you know, legal briefs and this and that and train from them?

他们说不行，这些都涉及客户机密，不能外传。

Like, no, they're proprietary a and b, they're specific to a client and we can't share them.

不过这是律所的情况，跟法律软件还不一样。

And so but that's for a law firm that's not for the legal software.

明白了。

Okay.

说到另一个可能被颠覆的领域，咨询行业经常被提到，比如实施服务、商业分析这些。

Speaking of another area that may be disrupted, consulting is a field that people talk about often as things like implementation and doing business analysis.

这些其实用提示词就能一次性搞定。

You can prompt that and one shot it probably.

你提到你女儿要去搞咨询工作？

You mentioned that your daughter is going to work in consulting.

对啊。

Mhmm.

你支持她吗？

Did you bless that?

是的。

Yeah.

当然了。

Of course.

没错。

Yeah.

因为这行其实也还行。

Because there a little bit.

嗯，是啊。

Yeah.

你讲吧。

Go ahead.

肯定会有一段时间，得有人帮这些公司搞清楚怎么落地AI，不只是技术上线，还得重新设计整个商业模式。

There's gonna be a period of time where somebody's gotta help all these companies figure out how to implement AI, and not only implement it, but how to reformulate their businesses.

因为在AI时代，你想提高效率、增加利润、增强竞争力，做事的方式会彻底不一样。

Because how you do things in an AI universe where you're trying to be more productive, more profitable, more competitive, it's gonna be completely different.

对那些CEO来说，最难的决定是：你愿不愿意把公司彻底推倒重来，哪怕股价在这期间可能崩盘，然后你再一点点重建。

The hardest challenge for those CEOs is am I willing to blow up my business knowing that my stock price could collapse in the meantime, and then I have to build it up.

在咨询公司工作，你手上通常掌握大量独家信息，能帮CEO顺利走过这段转型期。

And working for a consulting firm, you know, you hopefully have a lot of proprietary information that will allow you to guide that CEO as they go through that process.

咱们简单聊聊AI的商业模式吧。

Let's talk briefly about the business of AI.

对。

Mhmm.

从你的角度看，这么多资金涌向AI公司，这景象肯定特别有意思。

I mean, for from someone in your perspective, looking at the amount of investment that's gone on to these AI companies must be fascinating.

OpenAI最近宣布融了1100亿美元，我觉得这可能是史上最大的IPO了。

OpenAI recently announced that they had raised a 110,000,000,000, which is I think three x largest IPO ever.

他们计划在未来几年投入超过一万亿美元用于基础设施建设。

They're planning to spend more than $1,000,000,000,000 in infrastructure in the coming years.

我不太想聊花多少钱，倒是想听听你对回本这事的看法——怎么才能让这些投入值得？

I'd love to hear your perspective, not on the spend, but on the return needed to make those numbers work.

他们根本别想回本。

They'll never get it.

对啊。

Yeah.

他们这就是在白白烧钱。

They're they're they're just shitting away that money.

说白了，就是规模问题。

I mean, it's scale.

对吧？

Right?

不是AI不靠谱，你看看苹果。

It's not that AI is not gonna work, but look at Apple.

对吧？

Right?

他们几乎没花什么钱，但早就打好了基础，能直接无缝集成到设备里。

They haven't spent next to anything, but they've got a foundation where they can just plug and play into their devices.

但现在外面到处都在渲染他们花太多钱的事。

But there's a lot of FUD being put out about the spending.

对吧？

Right?

我们非得花一万亿，说是需要这么多数据中心的算力。

We're gonna spend a trillion dollars because we need all this data center capacity.

可实际上，数据中心的处理能力只会越来越快、越来越便宜。

Well, data center that the ability to process is going to get faster cheaper.

对吧？

Right?

而且这事会比大家想的快得多。

And it's going to happen faster and quicker than people expect.

所以我觉得他们嚷嚷的那些数字根本实现不了，说白了就是胡扯。

And so I think a lot of the numbers that they're throwing out there aren't going to come to fruition, you know, which is why I say they're full of shit.

这事根本不会发生。

It's not going to happen.

但那些孤注一掷的人，有的花的钱比手头有的还多。

But those who have just gone all in, some of them are spending more cash than they have available.

我懂他们为啥这么干，但我真不觉得所有人都非得这么干。

And I I understand why I just don't I'm not convinced that for all of them.

AI基础模型能不能成，比如ChatGPT、Gemini、Grok、Claude这些，咱们还不知道呢。

It's going to work and the reason why is we don't know if the the business of foundational models, the chat GPT Gemini's Grock Clive, Etc.

它们会像流媒体那样，一个老大带一堆能赚钱的，还是像搜索那样，基本就一家独大？

Is going to be like the streaming industry where there's one leader and a bunch of players that make money or some that make money at least or search where there's effectively one company.

所以他们才拼命融资、押上全部、砸钱到处拉关系，就指望自己能当那个最后的赢家。

And so they need to raise all the money, go all in and spend everything they can kiss all the rings they need to kiss around the world in hopes of being the one.

对吧？

Right?

听起来像《黑客帝国》里的墨菲斯。

It sounds like Morpheus.

我就等着基努·里维斯推门进来了。

I'm just waiting for Keanu Reeves to walk through the door.

但这事儿肯定特别难，我觉得他们指望的回报根本实现不了。

But so it's it's gonna be very difficult, but I don't think it's gonna pay off the way they expect.

他们这是在大规模地烧钱。

They're shitting away the money at scale.

真不是件容易的事。

It's hard to do.

对吧？

Right?

但你要不拼一把，就融不到下一轮钱——这行业变来变去，谁也不知道终点在哪，如果你融不到钱，那才真叫危险，因为你根本不知道自己是不是那个能赢的人。

But but if you don't go all in like that, you can't keep on raising money because as it zigs and zags and you don't know where it's all going to go, if you're not still raising money, you're in deeper trouble because you don't know if, you know, if you're not the winner, then you've got problems.

我来替他们说说看，就当是打个辩论。

Let me make their case for the sake of argument.

现在AI圈里的情况是，训练已经没那么泛了。

Right now, what we're seeing is a moment in the AI world where the training has gotten to the point where it's less general.

大家开始专注某些特定能力。

You focus on certain capabilities.

我们知道Anthropic就专攻编程。

We know Anthropic focused on code.

OpenAI则盯上了医疗领域。

Open AI has focused on health care.

要在这些专业领域练到顶尖，真不是件容易事。

And it's difficult to train up really well in those disciplines.

所以Anthropic之前在编程上领先，就是因为他们在这块真下功夫了。

And you see things like Anthropic leading in code for a while because they've gotten good at it.

所以在我看来，这儿最后肯定不止一个赢家。

So that to me would suggest that there's going to be multiple winners here.

有可能，但在垂直领域，比如医疗，你手上有公开的数据。

Potentially, but in a vertical, right, like healthcare, you've got open evidence.

而公开数据其实是去购买知识产权。

And open evidence is actually going out and buying intellectual property.

但ChatGPT并没有这么做。

ChatGPT is not.

你会看到，现在已经开始发生，以后还会更明显：如果你拥有知识产权，申请专利的人会越来越少，因为一申请专利，信息就全公开了，每个模型都能拿去训练。

And what you'll see, you're starting to see happen and will happen even more, if you own intellectual property, you're going to see fewer people applying for patents because the minute you apply for the patent, it's available to everybody, which means every model can train on it.

当我跟Cost Plus Drugs那边聊，去跟医院、研究机构和学校交流时，我会告诉他们：别急着发表成果。就算你发了，感觉挺有成就感，好像在圈子里成了大人物。

And when I go and talk via cost plus drugs, when I go talk to hospitals and research campuses and schools, I tell them do not publish sell because the minute you publish even though it makes you feel better and you seem like you're, you know, a bigger dog in the community.

可一发表，所有模型立马就学走了，你的优势就没了。

All of a sudden every model has been trained on it and you've given away your advantage.

所以说到垂直领域，我不确定他们以后还能不能买得起自己需要的知识产权。

And so when it comes to verticals, I don't know necessarily that they're going to be able to buy the IP they need going forward.

至于Claude和Anthropic专注编程，这其实算不上一个垂直领域，对吧？因为编程能用在所有地方。

Now what, Claude is doing with Anthropic in focusing on programming, That's not really a vertical per se, right because it can be used for everything.

这完全是流程驱动的，我觉得这样挺聪明的。

It's really process driven and I think that's smart.

但看看其他的，比如Gemini，它有个优势，因为谷歌搜索就是Gemini。

But when I look at the other ones, you know, Gemini has an advantage because Google search is Gemini.

对吧？

Right?

所以你现在一搜索，它直接给你返回AI生成的回答，还能在旁边卖广告。

And so now when you do a search, comes back with an AI response and it can sell ads around it.

我不知道Meta会怎么搞。

I don't know what Meta is going to do.

我不知道OpenAI最后会怎么走，说实话，我觉得把医疗当成OpenAI的一个功能，这说法不太对吧？

I don't know what, OpenAI is going to do when it's all said and done because I don't think, you know, you can I always call it like healthcare for OpenAI is a feature?

这根本不是个产品。

It's not a product.

这只是一个功能，而Open Evidence有这个优势，别人只要砸钱买IP，也能轻松加上。

And it's a feature that, you know, Open Evidence has that others can add just by going spending money on the IP.

再就是个更大的问题了，想想现在这些基础模型，未来几年它们都是靠文字和图片训练的。

And then you've got the bigger problem, like when you think about all these foundational models today and for the next few years, they are built on text and pictures.

视频？根本不算。

Not really video.

它们根本不懂现实世界里发生的事。

They don't know what's happening in the real world.

我之前举过例子，两岁小孩把学饮杯从高脚椅上推下去，AI压根不明白这回事。

You know, like I mentioned the the example about the two year old pushing the sippy cup off the high chair, like it doesn't understand that.

你就算喂它再多信息，它也推不出 E=mc² 这种公式。

You know, it's not if if you fed it all kinds of information, it's not going to be able to come up with e equals m c squared.

要真能做到这个，得懂物理，得真正理解这个世界。

And to do that, have to understand physics, you have to understand the world.

所以我觉得，我们正从大语言模型转向一种‘世界观’模式——得懂物理规律，能看懂视频，理解真实世界。

And so we're going from large language models, I think to what's called a worldview approach where it's built on, you know, understanding the physics of the world and being able to take video and understand that.

我投了一家公司，他们发射卫星，能观测地表各种物质，直接告诉你这些天然材料的成分。

Invested in one company that's putting up satellites that can look at different materials and tell you what the makeup of those, you know, natural materials are.

是木头吗？

Is it wood?

是石头吗？

Is it rock?

不管里面是什么，都得靠光谱分析才行。

Whatever is in there like a spectrograph.

我觉得这会彻底超越Claude、Grok那些东西。

And I think that's going to supersede a lot of what Claude and Grock, etcetera are doing.

在我看来，AI的真正厉害之处还没出现呢，以后只会越来越离谱。

And so we haven't seen the best of AI in my opinion, and it's going to just get crazier and crazier and crazier.

所以你看，这么多人砸钱，如果你最擅长编程，那确实挺好，这就是你的优势。

And so when you think about all these people spending all this money, look, if you're the best programming, you know, like, is and that's your niche, great.

但我不清楚其他那些公司到底在搞什么方向。

But I don't know what the niche of these other ones are.

你知道吗？

Do you?

没有。

No.

但我觉得，除非真有三四个脱颖而出的，否则很难撑得住。

But I I don't think there's gonna I mean, if you have three, four winners, maybe that works.

三四个还行，再多就真吃力了。

Maybe three, any more than that, it's gonna be difficult.

那你就是个网站罢了。

I mean, it's like then you're then you're just a website.

对啊。

Yep.

你就是个App。

You know, you're just an app.

花了上万亿美金，就为了做个App。

And you just spent a trillion dollars to be an app.

这钱花得真多。

It's a lot

这么多钱。

of money.

让我问一下。

Let let me ask.

我在这档节目里采访过很多优秀的科技创始人，有一个出人意料的共同难题反复出现——找一个合适的域名。

I've interviewed a lot of great tech founders on this show, and one surprisingly universal challenge comes up again and again, finding the right domain name.

我当初推出《大科技》的时候，也碰过这问题。

It's something I ran into myself when launching Big Technology.

你想要的名字通常都被占了，很容易就想随便选一个凑合了。

The names you want are often taken, and it's tempting to just settle and move on.

但我最敬重的那些创始人，从不在根本问题上将就，域名就是其中之一。

But the founders I respect most don't settle on fundamentals, and your name is one of them.

它应该一上来就让人明白你到底做的是什么。

It should immediately signal what you actually build.

这正是我欣赏 .tech 域名的地方。

That's what I appreciate about dot tech domain names.

这再合理不过了。

It just makes sense.

它直接告诉世界、客户、投资人，还有任何搜索你的人：你搞的就是科技。

It tells the world, customers, your investors, anyone googling you that you're building in technology.

干净利落，不拖泥带水。

Clean, direct, no qualifiers.

我看到越来越多正经的初创公司开始用这个了。

And I'm seeing more serious startups lean into it.

nothing.tech、1x.tech、aurora.tech、ces.tech、ultra.tech、alice.tech、neuron.tech、blaze.tech、py.tech，还有好多好多。

Nothing.tech, 1x.tech, aurora.tech, ces.tech, ultra.tech, alice.tech, neuron.tech, blaze.tech, py.tech, and so many more.

如果你做的东西是技术驱动的，别将就。

If you're building something tech first, don't settle.

赶紧从任意注册商那儿拿下你的.tech域名，从第一天起就把你的定位亮出来。

Secure your .tech domain from any registrar of your choice and make your positioning obvious from day one.

大多数管理者都知道工作该咋搞，但真到了日常用什么工具、团队怎么配合、任务怎么交接这些细节上，他们基本全靠猜。

Most leaders know how work is supposed to happen, but when it comes to how it actually gets done day to day across tools, teams, and handoffs, they're mostly guessing.

Scribe Optimize 就是为了解决这个问题而生的。

That's exactly the problem Scribe Optimize was built to solve.

它已被超过八万家企业的信赖，包括近一半的《财富》500强公司，能让你实时看清员工在哪些获批的业务软件里真正干活，完全不用访谈、手工绘图，也不用团队额外花功夫。

Trusted by over 80,000 enterprises, including nearly half of the Fortune 500, it gives leaders a live view into how work is really happening across approved business apps without interviews, manual process mapping, or extra effort from the team.

因为它持续分析真实的工作流活动，所以洞察永远是新鲜的，哪怕流程一变，数据也不会过时。

And because it's continuously analyzing real workflow activity, the insights stay current instead of going stale the moment a process changes.

你能清楚看到哪些流程在跑、时间都花在哪、用了哪些工具。

You can see which workflows are happening, where time is going, and which tools are involved.

它会自动揪出最核心的问题，解释原因，甚至给出解决方案，还附带预估能省下多少时间。

It automatically surfaces top issues, explains why they're happening, and even recommends ways to fix them with estimated time savings.

更重要的是，它从设计之初就特别注重隐私保护。

And importantly, it's built with privacy in mind.

只有管理员批准的业务软件里的活动才会被记录，用户级别的数据默认全部匿名化。

So activity is only captured in admin approved business apps, and user level data is anonymized by default.

以前要花几个月才能搞清楚的事，现在随时都能看到。

The kind of visibility that used to take months, now it's just always on.

如果你不想再猜来猜去，想真正看清楚，就去 scribe.how/bigtech 看看。

If you're ready to stop guessing and start seeing, visit scribe.how/bigtech.

就是 scribe.how/bigtech。

That's scribe.how/bigtech.

我问你个问题。

Let me ask you this.

你这个人，当年就是靠有点儿狂、跟体制对着干，才出名的，对吧？

You're someone who gained national notoriety by being, you know, somewhat brash and rebelling against the establishment.

别扯了。

Fuck that.

怎么可能。

No way.

你觉得你跟萨姆·阿尔特曼、达里奥·阿莫代伊这些人，有相似的地方吗？

Do you see some of yourself in the Sam Altman's and Dario Amodei's in the world?

达里奥那儿可能有一点儿，但萨姆身上真没有。

Maybe a little bit in Dario, but not in Sam.

再多说点。

Say more.

我的意思是，现在的Dario简直在吓唬所有人。

I mean, you Dario now is trying to scare the shit out of everybody.

对吧？

Right?

但这本来就是融资的一部分。

But that's part of raising money.

就像当年我们做Broadcast.com的时候，我老说咱们要彻底取代有线电视和卫星电视。

Like when we had broadcast.com back in the day, I would say, we're just gonna replace cable and satellite and all that.

虽然最后没那么快，但我一直说再过几年就成，结果一晃三十年过去了，现在还真差不多实现了。

And it didn't, you know, but I kept on saying it's gonna be in a couple years and here we are thirty years later and we've kind of gotten there.

所以我觉得Dario在推Claude，我觉得你说得对，他们在编程和智能代理这个领域确实有优势。

And so I think Dario is pushing forward with Claude and I think to your point their niche with programming and agents I think is going to hold for them.

而且他们也明白，未来可能还得转向更全局的环境。

And I think they're they understand they may have to move to a worldview environment as well.

萨姆这人想法太飘忽了，我觉得这迟早会害了他。

Sam is all over the map and I think that'll backfire on him.

我的意思是，他们之前可是买了这家公司40%的内存芯片啊。

I just think, you know, they were they were buying up 40% of this company's memory chips.

对吧？

Right?

结果现在又突然撤了。

And they just backed out of that.

这种事可不能这么干。

You can't do that.

你想想，人一旦不信任你了，谁还愿意跟你做生意？

You know, at some point people stopped trusting and stopped wanting to do business.

我记得他们好像是把他从安全委员会调去别的部门了。

You know, they just moved him to from their safety committee, I think to something else.

具体细节我真记不清了。

I forget all the details.

我觉得吧，萨姆确实做了不少了不起的事，但我真看不出来，他们俩这么频繁发声除了拉投资之外还有什么好处。

I think, you know, Sam's accomplished a bunch of amazing things, but I just I just don't see how either one of them communicating is beneficial for anything but raising money.

那你建议他们怎么做？

So what would your advice to them be?

他们根本不需要我给什么建议。

They're doing they don't need my advice at all.

对吧？

Right?

你知道的，现在还太早了。

You know, you just it's so early.

变化实在太快了。

It's just changing so fast.

你得尽量多跟人保持联系。

You you know, you've just got to stay connected to as many people as possible.

但我认为你得更深地参与到基层，不能只盯着程序员。

But I think you have to be more involved at lower levels as opposed to just programmers.

我觉得苹果在这方面其实挺对的，每个iPhone用户都能轻松接入任何型号，以后想换就换，就像他们对搜索引擎那样，要么付费，要么赚钱。

I think, you know, Apple's got it right in some respect in that everybody with an iPhone, it's going to be plug and play to plug in whichever model you want And they'll have the ability at some point just to swap those out for their own if they choose or just like they've done with search engines, just pay or be paid.

但我觉得你得往孩子们那儿去，帮学校用好AI，让教育真正平等，让老师能点燃每个学生的光芒。现在我们教课，全靠老师自己硬撑。

But I think you want to be where kids are and showing schools how to use AI so that it's a democratizer for education and a tool for teachers to be able to, you know, bring out that light in every student's eyes, you know, right now when we teach we teach by the the teachers there.

他们自己定教学大纲。

They create a syllabus.

懂专业知识，然后照着一个模式教所有人，还指望所有学生都答出同样的标准答案，老师能不崩溃吗？

They've got the subject matter and then we teach everybody the same way and then we expect all the students to know the answers to the same questions and teachers freak out.

其实你只要用上AI就行了。

Well, all you got to do is use AI.

老师之所以搞砸，就是因为全班问的都是同一个问题。

Well, only reason teachers are getting it wrong is because there's they're asking the same questions of every student in the class.

对吧？

Right?

还非得让学生写作文，每个人都得交一篇一模一样的。

They're telling them to respond to it with an essay and every student has to respond the same essay.

其实我跟老师聊的时候说，最难的不是教知识，而是怎么点燃孩子们对某个学科的热情。

When in reality, when I talk to teachers, I tell them is, you know, the hard part for you is to get that light in the kids eyes to get them really excited about a subject matter.

有了AI，你就能为每个学生量身定制教学内容。

And with AI, you can personalize teaching to each individual student.

比如说我们在学美国历史，讲宪法，六年级的比利可能学习上有点吃力。

You can say, okay, we're we're doing American history and we're learning about the constitution, you know, Billy in sixth grade or whatever is, maybe isn't as good a student.

那我们就用AI给他设计一个适合他节奏的项目，根据他的回答调整问题，同时让老师和家长随时看到比利的进步。

So I'm gonna we're gonna put together, a project under AI that works at Billy's speed, reformulates the questions for Billy based off of his answers, and then keeps the teacher and parents in the loop so they can see where little little Billy is.

而且最好还能让AI把内容变得更有趣一点。

And hopefully, you can even mod you know, you can even have the AI personalize it so that it's more interesting.

比如孩子对保罗·里维尔比对乔治·华盛顿更感兴趣，对吧？

You know, if they like learning more about Paul Revere than George Washington, right?

那我们就多花点时间讲保罗·里维尔，激发他的兴趣。

You spend more time on Paul Revere to get them more interested.

有了AI，任何主题都能个性化定制。

You can personalize any topic with AI.

传统教学根本做不到，回到你之前问的AI公司那事儿。

You can't do it with traditional teaching and going back to your question about, you know, for the AI companies.

我觉得，只要让学生和老师对AI的功能感兴趣，他们就会愿意用，而且会一直用下去。

I think by getting students and teachers excited about the capabilities and features of the AI that you're offering creates a foundation that that they'll they'll wanna be comfortable with and they'll stick with those tools for a long, long time.

个性化辅导不是能让学生成绩比平均值高出两个标准差吗？

Isn't it true that personalized tutoring to a student gets you like two standard deviations above the mean?

我不清楚。

I don't know.

真不知道。

I don't know.

反正我觉得这很合理。

It just makes sense to me.

有人知道吗？

Let's someone knows?

不知道。

No.

你就在那儿笑呢。

You're just laughing.

行吧。

Okay.

确实如此。

It's true.

从前面，前排就能看出来。

From the front from the front row.

我敢肯定，数据就是这样的。

I'm pretty sure that's the numbers.

但之前因为价格太高，太多人根本用不上。

And it's just been inaccessible to so many people because of the expense.

但如果你能把它推广开来，你看——

But if you're able to scale that up Look,

这既花时间，也花钱。

there's time, there's expense.

家庭作业其实是有区别的。

And there's a difference between homework.

老师说我要写一篇关于……的作文。

Teacher said I got to write an essay on da da da da da.

我还得背一堆……东西。

I've got to memorize da da da da da.

但要是回家后，用电脑、手机这些设备，看到的是图文并茂、视频丰富的学习内容，而且有趣好玩，AI还能判断你是不是真在认真学，那就不一样了。

And going home and on your laptop or phone or whatever you have available to you, having it presented to you with graphics and videos and in a manner that's fun that the AI will understand if you're engaged with it or not.

你想想看。

And think about that.

AI其实很容易就能知道你是不是在认真答题。

It's not hard for an AI to know if you're answering questions.

它也很容易判断你给的答案是不是走心。

It's not hard to know if you're giving more engaged answers.

你有没有主动提问，或者学生有没有提问，AI一清二楚，对吧？

It's not hard to know if you're asking a question or if the students asking questions, right?

而且批改试卷、分析答案，再给老师和家长做个总结，也一点都不难。

And it's not hard to grade the test and grade the answers and then summarize it for the teacher and the parent.

家长可以根据这些对话提建议，老师也能。

And then the parent can make suggestions based off of conversations, the teacher can.

这真的太特别了。

That's just so unique.

这不光适用于教孩子，教任何人任何东西都行。

And not only does it apply to teaching kids, it applies to teaching anybody anything.

比如你要是用过谷歌的Notebook LM，能把任何内容转成播客当培训材料。

Like if you've ever used notebook LM from Google, where you could take it and turn whatever you want a training manual into a podcast.

你想想，做个播客教人怎么保持美国航空中心洗手间的清洁，这多离谱啊。

I mean, is insane, you know, doing a training podcast for, you know, how you wanna keep the restrooms at the American Airlines Center, clean.

而且还是男女两人对谈的。

And it's a man and a woman.

是的。

Yeah.

我们刚才就在聊这个。

We were just talking.

我们现在正听那个关于怎么保持洗手间干净的培训播客呢。

We're just going through the training manual of how to keep the restrooms clean.

这真的挺有意思的。

This is really interesting.

他们用的那些工具。

The the tools that they use.

我的天，谁想得到这么一把拖把还能这么用？他们这么设计，就是因为现在的孩子压根不爱看书。

I mean, whoever thought that this mop could work like this and they made it so know, because kids particularly today don't wanna read.

但你要把它做成播客，尤其是那种讲拖把、讲地板清洁液怎么配比都能让人笑出声的播客，那就不一样了。

But if you put it in a podcast format, particularly one that makes you crack up when you're talking about mops and you know, how you're gonna mix the solution to clean the floors.

这彻底改变了我们教育人的方式。

It's just changed how we educate people.

如果你能抓住这个趋势，学会用它、应用它，那你不管是当老板、当CEO、当经理、当员工、当学生还是当老师，都能占到大便宜。

And if you take advantage of that and learn from it and learn to apply it, you will have an advantage as an entrepreneur, as a CEO, as a manager, as as an employee, as a student, as a teacher, all across the board.

如果你还老一套地干，那得到的也只能是老一套的烂结果。

If you don't and you're doing it the same old way, you get the same old shit back.

那在这个时代，谁才能真正成功呢？

Who who does succeed then in this era?

谁能把这些工具用得最溜，谁就能赢。

Whoever learns how to use the tools the best.

你知道吗，在AI时代，最关键的那个词就是‘迭代’。

You know, whoever realizes that the operative word, the keyword in an AI world is iterate.

工具一直在变，你就得不停地迭代、持续迭代，明白自己会越来越聪明，员工会越来越聪明，客户也会越来越聪明，智能代理的沟通能力也会越来越强。

As the tools change, you have to keep on iterating, iterating continuously recognizing you're going to get smarter, your employees are getting smarter, your customers are getting smarter, agents will communicate and they'll be smarter.

所以你得让自己处在能应对这种变化的位置上。

So you have to be in a position.

作为创业者，我太懂那种我们拼命想突破的门槛了。

You know, as an entrepreneur, I know what it's like to have thresholds that we all try to hit.

我当年做到过五十万美元的销售额。

I got a half 1,000,000 in sales.

赚到一百万销售额。

Get a million in sales.

对。

Yeah.

赚钱嘛。

Making money.

对。

Yeah.

雇十来号人。

Up to 10 employees.

对。

Yeah.

然后你就会想，好了，公司我搞定了，客户也喜欢我，但在AI时代，你比现在更得不断改进。

And then you start thinking, okay, I've got this company down, my customers like me, but in an AI universe, you have, more so than now, you're going to have to continuously improve.

因为随便谁都能进来，说你没进步。

Because anybody can come in and say, they're not improving.

他们根本不了解这个新工具。

They don't understand this new tool.

所以我得去跟他们竞争。

And so I'm gonna go compete with them.

你得不断迭代才行。

You have to continuously iterate.

我听不少人说过，他们在公司里用这些工具，其实等于在训练AI来取代自己。

I've heard from more than a few people that they believe that using these tools inside their companies effectively means they're training the AI to replace them.

在某些情况下，这确实没错。

That has to that has to be true in some cases.

你觉得随着这项技术继续发展，对整个就业市场会有什么影响？

What do you think happens in the broader job picture here when this technology continues to ramp?

肯定会有人失业。

There's gonna be displacement.

这点毋庸置疑。

There's no question about it.

但我可不是那种人，像马斯克说的，觉得工作以后可有可无，或者失业率会到百分之五十。

But I'm not you're one of those people that says jobs will be optional like Elon Musk said or 50% unemployment.

不可能。

No.

如果你只是在做些重复性的事，比如改格式，或者回答一些简单问题。

There's things that if all you're doing is reformatting, you know, or you're answering a question.

就是非黑即白的那种，那八成你迟早会被AI取代。

Yes or no, then, you know, you're there's a good chance you're gonna be replaced by AI.

但如果你会独立思考，那你永远都有用武之地。

But if you're a critical thinker, you're there's always gonna be a need for you.

如果你会独立思考，还懂怎么用这些工具——知道什么时候该用AI代理，什么时候不该用，什么时候适合‘ vibe coding ’，什么时候不适合。就像我跟我女儿说的，只要你学会用这些工具，又能独立思考，保持好奇心，一直学习，你就永远不愁没工作。

If you're a critical thinker and you understand how to use the tools so that you understand where best to use an agent, where best not to use an agent, where best to do, you know, vibe coding, where best not to and you under it's like I was telling my daughter, if you learn how to use these tools and you know how to think critically, you're curious so you're always learning, you're always going to have a job.

因为我说过，AI根本不懂它自己行为的后果。

Because as I said, AI doesn't know the consequences of its action.

你可别干那种活儿，全靠AI，结果一抬头：‘天哪，它干了啥？’

You don't want to be in a business where you just trust the AI and it's like, oh shit, what did it do?

你需要有人当缓冲，懂得什么时候用、怎么用、为什么用或者为什么不用，这特别关键。

You know, you need somebody as the buffer to understand how, where, when and why or why not to use it and that's critical.

在很多情况下，这正是中层管理的职责。

And that's middle management in a lot of cases.

而且，就像我之前说的，有些公司必须彻底重塑自己。

And on top of that, you're going to have companies like I said earlier that have to completely reinvent themselves.

一旦要重塑，你就需要懂怎么把所有这些部分拼在一起的人。

And when you reinvent themselves, you're going to need people that understand how to make all these pieces work.

所以我觉得，工作机会多的是。

And so I, you know, I think there's going to be plenty of jobs.

要是我刚毕业，我女儿早就找到工作了。

And if I'm coming out of school, you know, my daughter already has a job.

但要是我现在16岁，刚毕业，或者是个16岁想找工作的孩子，我会把AI相关的知识全学透。

But if if I'm 16 years old, if I was graduating today, or if I was a 16 year old looking for a job, I would learn everything there is to know about AI.

然后我会去那些中小公司，直接上门说：让我进来，你们那些压在清单最底下、没人想干的活儿，我全包了。

And I would go to small and medium sized businesses and say, let me walk in the door and all those things that you know you need to do that are the bottom of your to do list.

我来教你用智能代理来搞定这些事。

Let me show you how to use an agent to do those things.

因为这么做，你效率更高、更有竞争力，赚的钱也更多。

Because in doing so, you'll be more productive, more competitive, you'll make more money.

我给你举个特别典型的例子。

And I'll give you a perfect example.

我投资过一家叫 RebelCheese.com 的公司。

One of my Shark Tank companies is called rebelcheese.com.

他们卖纯素奶酪，全球发货。

They sell vegan cheese and they ship it all over the world.

跟很多寄快递的公司一样，你知道吧，寄盒子有不同尺寸，UPS、DHL这些快递公司，从一个区域发到另一个区域，价格都不一样。

And they like a lot of companies that ship products in boxes, you know, for those of you who ship stuff in boxes, you know, there's different sized boxes for UPS, DHL, whatever, and you start in one zone and there's a different price to ship to a different zone.

而且你肯定也发现，他们从来不会按该收的价收你钱。

And then you also probably know that they don't ever charge you the right price.

这事儿是不是特耳熟？

That sound familiar?

没错。

Yep.

所以这家Rebel Cheese公司做了一个小代理程序，能在打包发货前拍下箱子的照片，自动识别尺寸，对比运费价目表和账单，发现不一致就自动生成退款申请，每个月能省下五万美元，全程自动化。

So what this company did Rebel Cheese was they wrote a little agent that took a picture of the box when it's getting ready to ship and determine the size, looked at the price list, Look at the invoice took a picture of the invoice compared them and when they were different created the credit request and are saving $50,000 a month and it's all automated.

根本不用人动手。

They don't have to touch it.

这就是智能代理的用武之地，你得懂怎么落地，但大多数中小公司还没意识到这点，也没资源专门配人手去做。

That's where the agents come in and come in handy and you have to know how to implement that and most small to medium sized businesses don't understand that yet and they don't have the resources to just, you know, allocate people.

他们既没有醉醺醺的实习生，也没法请到清醒的实习生来干这活儿。

They don't have the drunk interns or the sober interns, you know, to just go do it.

在座的创业者都懂，每到周六你总列一堆待办事项，结果一件都完不成。

And anybody here who's an entrepreneur knows there's always 10 things that you say you're going to do on Saturday and never get to.

对吧？

Right?

一直都是这样。

Always.

所以代理工具就是干这个用的。

And so that's what agents are good for.

要是我今天毕业，我就会去这些中小公司，一小时收他们一百美元。

And so if I were graduating today, I'd be going to these small medium sized companies charging them a $100 an hour.

因为这些AI系统每次更新都会有点偏差，这些代理可能还得经常调整。

And then because these these AI systems, kind of drift each time there's a new version, those agents might need to be modified.

你就能一直有稳定的收入，回头去检查、更新它们。

You have recurring income coming in all the time to go back and check and keep them up to date.

现在有多少孩子上过一节计算机课、懂点Python，就能干这些活儿了。

There are so many kids that took one computer class, you know, know some Python that are going to be able to go do these things.

这方面的就业机会多得是，根本不愁没工作。

There's not going be any shortage of jobs there.

但你要想去大公司当初级软件工程师或程序员，那条路基本没戏了——大公司的人早就受过培训了。

But if you try to work in a big company and become an entry level software engineer or programmer, that's just not going to be there because the people in that big company, they're gonna have training.

他们IT部门里那些老手，都知道得学这玩意儿。

They're gonna have older people that are in the IT department that know they need to learn this stuff.

那些初级岗位根本不会有了。

And those those entry level jobs aren't gonna be there.

别担心。

Don't worry.

现在根本没人招那种职位了。

They're not hiring for those anymore.

对。

No.

没人招了。

They're not.

是啊。

Yeah.

没人招了。

They're not.

没错。

Yep.

你刚才是想确认一下，我原以为你的建议是年轻人应该去公司内部工作。

You just to to clarify, I was thinking that your your advice was the young person should go in house at a company.

去一家小公司。

At a small company.

但既然这样，他们为什么不干脆自己创业，把这当成一项服务来卖呢？

But but why wouldn't they then just start their own business and sell that as a service?

我说的去中小型企业，指的就是这个意思。

Well, when I say go to small medium sized businesses, that's what I'm saying.

对吧？

Right?

去这些公司，就像那个‘叛逆奶酪’的例子那样，给他们展示一下。

Go to them and you know, show them just like the rebel cheese example.

展示那些又琐碎又耗时、雇人来做还不确定有没有回报的工作。

Show them all the the things that are too tedious time consuming and you don't know if you'll get a return, if you hire somebody to do it.

这种活儿特别适合请人来干几个小时、几周，帮他们设计好自动化流程，让系统替他们干活。

That's a perfect thing to bring somebody in for a few hours a few weeks and have them define agents and allow the agents to do the work for you.

如果你还不懂什么是智能代理，那你得赶紧学了。

And if you don't know what an agent is, you're going to have to learn.

学得最快的方法就是去ChatGPT或者别的平台，直接问它。

And the best way to learn is go to chat GPT or whatever and just type in there.

我也是刚接触这些AI的东西，完全是个新手。

I'm new to all this AI stuff.

到底啥叫智能代理啊？

What the hell is an agent?

你能教教我怎么用，它能给我生意带来啥变化吗？

Can you teach me how to do it and how it would impact my business?

我再跟你补充一点。

And let me just tell you part two to that.

如果你作为老板、经理或者员工，连跟AI来场真心话大冒险都不敢，那你迟早要被甩在后面。

If you as a CEO, manager, employee are afraid to have a heart to heart conversation conversation with your AI, you're going to fall behind.

我说的可不是你私生活的事儿。

And I'm not talking about your personal life.

这人适合我吗？

Is this the right guy for me?

我该跟这姑娘交往吗？

Should I date this girl?

别想了。

No.

但我想说的是，你开始跟AI聊天，聊着聊着还觉得：哎，我得再找一个，这感觉挺怪的。

But what I'm saying is, it's weird to start talking to your AI and then having a conversation and then thinking, okay, I need to have another one.

比如我车里就装了一个，开车的时候跟它唠嗑，自己都忍不住笑。

Like I have my hooked up in my car and I'll be driving and talking to it and I'll catch myself.

这事儿是有点怪，但你得克服这种犹豫，毕竟我刚才说的那个专利例子，答案其实挺靠谱的。

This is strange, but you've got to get over that hesitancy because by some of the answers like I gave you the patent thing up, they're good answers.

你肯定也觉得：这玩意儿真牛。

Like you were like, that shit is good.

如果你不敢让自己习惯这样，你的事业和生意只会越来越难搞。

And if you don't have if you don't do that, if you don't allow yourself to feel comfortable with that, your your career, your business life is gonna be a lot more difficult.

马克，如果你经常跟它聊天，会不会问它：‘你能告诉我我最深的秘密吗？’或者‘给我做个心理分析吧？’

If you speak with it a lot, Mark, do you ever ask it, can you tell me my deepest darkest secrets or psychoanalyze me?

确实有点怪，但你都已经放开了。

Can be weird, but you've given up

那个问题你早就抛开了。

that prompt.

他们倒数着时间呢。

They're they're counting us down.

再给几分钟行吗？

Couple more minutes?

当然可以。

Sure.

你们要不要再多待几分钟？

Do you guys want a couple more minutes?

行吧。

Alright.

有个好消息。

Good news.

我来个快问快答。

I have a lightning round.

哎呀，这对我可从来不是什么好事。

Oh, that's never good news for me.

乔丹和勒布朗一对一，谁赢？

Would Jordan or LeBron win one on one?

乔丹。

Jordan.

乔丹。

Jordan.

那还用说。

Yeah.

毫无疑问。

No question.

有可能

Could

科比能赢他们任何一个吗？

Kobe beat either of them?

当然能。

Yeah.

我的意思是，他们每个人在任何一场比赛里都可能发挥超神。

I mean, they're all so good in any given game.

谁赢谁输都说不准。

One can beat the other.

印第安纳大学的？

Indiana alum?

对。

Yep.

是

Is

行吧。

alright.

谁是印第安纳大学的球迷？

Who who Hoosiers?

费尔南多·门多萨能成为NFL前十的四分卫吗？

Is Fernando Mendoza gonna be a top 10 quarterback in the NFL?

那当然。

Of course.

好吧。

Okay.

2028年你最看好谁？

Favorite candidate in 2028?

他们都说马克·库班。

Mark They're saying Mark Cuban.

巴特·辛普森。

Bart Simpson.

我也不知道。

I don't know.

我还以为你会这么答呢。

I thought we might get that answer.

他说是巴特·辛普森。

He said Bart Simpson.

有没有谁是你绝对不投的？

Is there anyone you wouldn't vote for?

有啊。

Yeah.

我一堆朋友，压根儿不可能投他们。

I got a lot of buddies that no chance I would vote for.

没有。

No.

现在还没到2028年呢。

I'm it's not 2028 yet.

那你看看吧。

Then look.

关于政治，我说什么都没用，改变不了谁的想法。

There's nothing I can say about politics that's gonna change people's minds.

所以我干的是医疗行业，卖的是成本加价的药。

And so, you know, I'm in the health care business with cost plus drugs.

共和党需要便宜的药。

Republicans need low priced drugs.

民主党也需要便宜的药。

Democrats need low priced drugs.

我就关心这个。

That's all I care about.

这话说得真到位。

That's a winning message.

NBA该不该把比赛时间缩短？

Should should the NBA shorten games?

对。

Yes.

缩短到四十分钟。

To forty minutes.

再多说说这个。

Say more about that.

这儿有谁在看三月疯狂吗？

Anybody here watching March Madness?

如果你是杜克大学的球迷，你可能会觉得他们上一场少了八分钟，挺遗憾的。

Now if you're a Duke fan, you were upset there weren't eight more minutes in their last game.

但没人觉得比赛四十分钟有问题。

But nobody's upset that it's forty minutes.

如果你喜欢WNBA，你也不会觉得四十分钟太短。

If you're into the WNBA, you're not upset that it's forty minutes.

你看奥运篮球赛的时候，也不会觉得四十分钟不够吧。

If you watch Olympic basketball, you're not upset that it's forty minutes.

不管是高中篮球赛，还是所有大学联赛，都是四十分钟。

You know, high school basketball, you know, all college games.

如果把NBA比赛时长从48分钟压缩到40分钟，整个赛季的总时长加起来差不多能少打14场球，我觉得这能帮球员减轻身体负担，还能让比赛更好看——以前我们都得磨磨蹭蹭等到第四节才见分晓，现在第四节来得更快，每一轮进攻都更关键。而且还会涌现更多冷门，毕竟总进攻回合少了，NBA的球队本身都很强，一旦哪支球队手感爆发，冷门自然就多了。

And so by cutting back to forty minutes from forty eight, it's equivalent of shaving about 14 games off the season, which I think will help the players bodies and I think it would make the games better because you know, we all kind of pitter patter till the fourth quarter and now the fourth quarter comes quicker and every possession impacts more plus there's more upsets because you know, there's fewer possessions and every NBA team is still good And so one team gets hot, you'll see more upsets.

我觉得不管从哪个角度看，这对所有相关的人来说都是件好事。

I just think it's it's better across the board for everybody involved.

还有一点，你去看看电视收视率或者流媒体数据，现在第一运动是什么？

And the other thing is, if you look at TV ratings or streaming ratings, what's the number one sport?

还有橄榄球呢。

Football.

那一场橄榄球比赛里，真正用来打球的时间到底有多少分钟？

How many minutes of actual game time is there in a football game?

也就12到15分钟吧。

Twelve, fifteen.

你去看各类体育赛事的收视率就会发现，真正的有效比赛时长越短，收视率反而越高。

If you look at ratings for sports, the less amount of game time, the actual playing game time, the higher the ratings.

人们就得有薯片和牛油果酱。

People need their chips and guac.

至于NBA，你看看冰球，冰球在电视上最没人气。

And the NBA, I mean, you look at hockey, hockey has the hardest time on TV.

棒球缩短比赛时间后，收视率怎么样了？

What happened with baseball ratings when they shortened the game?

就是这么直接。

Straight up.

也许他们可以取消比赛最后时刻的所有暂停。

Maybe they could take away all those timeouts at the end of the game.

其实我对四十分钟里的暂停也不介意，毕竟我们已经删掉一些了。

Well, I don't even mind the timeouts in a forty because we did take away some of the timeouts.

但如果比赛只有四十分钟，而且每回合都更关键，我觉得这会彻底改变比赛。

But if the game's only forty minutes and there's just more action that counts, I think that changes the game.

我有个点子，可以让AI每场比赛都定一条新规则。

I had an idea that you could have an AI make a new rule every game.

有一场比赛，三分球算四分。

So one game, the three point is actually worth four points.

有一场比赛，你要是扣篮就算犯规。

One game, if you dunk, you're rejected.

有一场比赛，只打三节，不打四节。

One game, you're just playing three periods, not four quarters.

你先告诉我这个联盟怎么玩，我再给你打电话。

You tell me how that league goes, and then I'll call you.

我觉得你已经明白我的意思了。

I'm gonna I I think you're on board here.

最后一个，简单点的。

Last one, easy one.

你怎么改进NBA选秀？

How do you fix the NBA draft?

我觉得吧，缩短比赛时间是一方面。

I think, you know, shortening the games is one thing.

你知道吗，大家都以为这是在故意输球。

See, people think it's about tanking.

连NBA自己都搞错了这一点。

It has not even the NBA is wrong in this.

他们还以为这跟故意输球有关。

They think it's about tanking.

根本不是故意输球的事。

It's not about tanking.

关键是该怎么重建球队——当你成绩差的时候，工资帽低，操作空间就大。

It's how do you rebuild a team and to rebuild a team when you're bad, your payroll is lower.

这样你就有更多灵活性，也能交易选秀权。

So you have more flexibility and trading picks.

我觉得可以把比赛时间缩短。

I think you make the game shorter.

我觉得再进一步限制选秀权的数量，让球队只能在七年之内交易选秀权。

I think you limit the number of picks even more so that a team can trade from like it's for seven years.

你限制球队三年内不能交易，同时进一步减少球队在任何时候能拥有的首轮签数量——因为一旦你不能再囤积签位，就没必要刻意压低薪资了。既然压薪没意义，那还不如干脆去争取赢球。

You limited to not trade three years and you eliminate the you reduce the number of t number of first round picks that a team can own at every any one point in time because once you can't accumulate any more picks, there's no reason to stay under the cap and you know, if you can't stay under the cap, you might as well try to get better.

这大概就是我会做的。

So that's what I would do.

太棒了。

Love it.

好的。

Alright.

我这就把话筒交给杜安，也想对大家说声谢谢。

I'm gonna turn it over to Duane, and I just wanna say thank you to all of you.

你们真的太棒了。

You've been amazing.