创始人的直觉与坚持

As a founder, you just have this instinct for some market. That's the hard thing about being an entrepreneur, being a founder is like most people are not going to believe in what you're trying to do until all of a sudden they do. 作为一名创始人，你对某个市场会有一种直觉。这就是创业最困难的地方，大多数人不会相信你正在做的事情，直到突然有一天他们相信了。

I loved the idea of the product that we were building. As long as I feel really happy about the customers that we have and they're happy, then that's like the validation I'm in search of. You have to just like stay the course and keep going and keep showing up even if you know it's hard and even if you have doubts and moments, you just have to like keep going. 我热爱我们正在构建的产品理念。只要我对我们的客户感到非常满意，并且他们也满意，那么这就是我所追求的验证。你必须坚持下去，不断前进，不断努力，即使你知道这很艰难，即使你有疑虑和动摇的时刻，你也必须坚持下去。

AssemblyAI的崛起

My name is Dylan Fox. I'm the founder and CEO of AssemblyAI (AssemblyAI: 一家为开发者提供语音AI模型的平台)。 We've built the industry's most accurate and easiest to use developer platform for speech AI (Speech AI: 语音人工智能，让机器能够理解和处理人类语音的技术). We've raised over $130 million in funding to date from Excel Insight Partners Daniel Gross and Nat Freeman and Smith Point. That's led by Keith Block from Salesforce. 我是Dylan Fox，AssemblyAI的创始人兼首席执行官。我们构建了业界最准确、最易于使用的语音AI开发者平台。迄今为止，我们已从Excel Insight Partners、Daniel Gross、Nat Freeman和由Salesforce的Keith Block领导的Smith Point那里筹集了超过1.3亿美元的资金。

早期编程与创业经历

My older brother, he would order all the hardware online and he would be in our basement making computers and I would watch him and being around computers as a kid playing video games. I was addicted to these MMORPG (Massively Multiplayer Online Role-Playing Game: 大型多人在线角色扮演游戏) games. I love just working on technology. 我的哥哥会在网上订购所有硬件，他会在我们家的地下室组装电脑，我会在旁边看着他。小时候，我玩电脑游戏，沉迷于这些大型多人在线角色扮演游戏。我就是喜欢研究技术。

So in college, I started this company that helped other college organizations fundraise online and people that donated to this student organization would get like local rewards in their community. It was a terrible idea and it was, you know, didn't go anywhere. But we learned a lot about starting company and being a founder through that experience. What I learned from that experience was that I loved being a founder and I loved programming. And with programming, it wasn't so much the programming that was addictive. It was just this open-ended world that you could just build stuff. Any idea you had with programming, you could make it into something real and then you could get feedback from users and you could then keep building and keep building. And so it was this process of like building something that I found just so addictive. 所以在大学里，我创办了一家公司，帮助其他大学组织在线筹款，向这个学生组织捐款的人会在社区获得当地奖励。那是一个糟糕的主意，也没有任何进展。但通过那次经历，我们学到了很多关于创办公司和成为创始人的知识。我从那次经历中了解到，我热爱成为一名创始人，也热爱编程。对于编程，上瘾的不是编程本身，而是这个开放的世界，你可以不断地创造东西。任何你通过编程产生的想法，你都可以将其变为现实，然后从用户那里获得反馈，接着你可以不断地构建和改进。所以，这种构建东西的过程让我非常着迷。

毕业后的自我提升

So after college, I didn't get a job. We had shut the startup down. I just opened up a bunch of credit cards and I went like $30,000 into credit card debt. Basically just like learning how to program and reading programming books and building apps and just like all day. That's what I would do in my apartment. And I would make like one big bowl of pasta every Sunday and just like eat that all week with Diet Coke. As I was just like spending all day just programming and building stuff and seeing if I could launch anything new. 所以大学毕业后，我没有找工作。我们关闭了那家初创公司。我只是办了一堆信用卡，欠下了大约3万美元的信用卡债务。基本上，我整天都在学习如何编程，阅读编程书籍，构建应用程序。这就是我在公寓里每天做的事情。我会在每个星期天做一大碗意大利面，然后一整个星期都配着健怡可乐吃。我就这样整天编程和构建东西，看看我能否推出任何新产品。

After, you know, almost 2 years of doing that and going into credit card debt, I was like, "Okay, I need to go get a job." But I had found that I was really most interested in machine learning (Machine Learning: 机器学习，人工智能的一个分支，让计算机通过数据学习) and natural language processing (Natural Language Processing: 自然语言处理，简称NLP，人工智能的一个分支，处理人类语言). And so there was a team in San Francisco, the company called Cisco that was hiring for machine learning engineers to focus on building natural language processing products and interfaces around Cisco's collaboration products. Got really into neural networks (Neural Networks: 神经网络，一种模仿人脑结构的计算模型) and more advanced machine learning and deep learning (Deep Learning: 深度学习，机器学习的一个子集，使用多层神经网络) while I was out there at that job. And that was like 2015 2016 time. 在那样做了将近两年，并且背负了信用卡债务之后，我心想：“好吧，我需要去找份工作了。”但我发现自己对机器学习和自然语言处理最感兴趣。当时旧金山有一支团队，思科公司正在招聘机器学习工程师，专注于围绕思科的协作产品构建自然语言处理产品和界面。在那份工作中，我深入研究了神经网络以及更高级的机器学习和深度学习。那大概是2015、2016年的时候。

语音AI的萌芽与挑战

When I got the job at Cisco and I knew I always wanted to start another company. I'd always spend nights and weekends just still tinkering with random ideas I would have. And I think the Alexa (Alexa: 亚马逊的智能语音助手) launched around the time I was in Cisco. So the Alexa product was like the first computer you could talk to. And I as a machine learning engineer that was working in natural language processing. I wanted to start experimenting with my own ideas for voice interfaces (Voice Interfaces: 语音界面，允许用户通过语音与计算机系统交互) or voice products, voice driven products. 当我在思科找到工作时，我就知道我一直想再创办一家公司。我总是利用晚上和周末的时间，捣鼓一些随机的想法。我想亚马逊的Alexa大概是在我还在思科的时候推出的。所以Alexa产品就像是第一台你可以与之对话的电脑。作为一名从事自然语言处理的机器学习工程师，我当时想开始尝试自己关于语音界面或语音产品、语音驱动产品的想法。

And the leading company at the time that was building that technology was this big company. And I contacted them to try to get access to their developer SDK (Software Development Kit: 软件开发工具包，用于创建应用程序的工具集合). And they mailed me a CDROM. It was like a $10,000 evaluation agreement that you had to sign. I didn't even have a CDROM drive to like load their SDKs. It was just this complete archaic experience. As a developer, I really wanted this super accurate, really easy to use developer platform because I saw back then that the technology was going to just get orders of magnitude better and that was going to make what was a small market huge. That was a really exciting thing that I just wanted to build and work on. 当时开发这项技术的领先公司是一家大公司。我联系他们，试图获取他们的开发者SDK。结果他们给我寄来了一张CD-ROM。那还需要签署一份价值1万美元的评估协议。我甚至没有CD-ROM驱动器来加载他们的SDK。这简直是一种完全过时的体验。作为一名开发者，我真的想要一个超高准确度、易于使用的开发者平台，因为我当时就看到这项技术将会有数量级的提升，这会将一个小市场变得巨大。那是一个让我非常兴奋，想要去构建和投入的事情。

As a founder, you just have this instinct for some market and that's what gets you excited about working in that market or building in that market. And so for me, that instinct was voice interfaces and speech AI technology. That is one of the most important modalities for AI. And so we're really excited about that potential and especially that potential to create really accurate and amazing AI for speech and voice and then just put it into the hands of developers to build really creative stuff with and really amazing apps with. 作为一名创始人，你对某个市场会有一种直觉，这正是让你对在该市场工作或构建产品感到兴奋的原因。对我来说，这种直觉就是语音界面和语音AI技术。这是AI最重要的模式之一。我们对这种潜力感到非常兴奋，特别是它能够为语音和声音创造出真正准确且令人惊叹的AI，然后将其交到开发者手中，让他们能够构建出真正有创意和令人惊叹的应用程序。

Y Combinator的洗礼

I left my job and then a few months later got into Y Combinator (Y Combinator: 简称YC，全球知名的创业孵化器). I had no clue I was going to get into Y Combinator. I just wanted to submit the application as really a thought exercise to like crystallize what I was working on, what I was going to do. You know, I figured like no chance I'm getting in alone. No progress, no traction, no product, just an idea. But there was a YC partner at the time, Daniel Gross, who had worked at Apple, had worked around Siri, got an email, it's like, "Hey, what's your accuracy rate from Daniel?" And then the next day they were like, "Hey, we'd love you to come in for an interview." 我辞掉了工作，几个月后进入了Y Combinator。我当时根本不知道自己会进入Y Combinator。我只是想把申请当作一个思想练习，来明确自己正在做什么，将来要做什么。你知道，我当时觉得我一个人根本不可能进去。没有进展，没有吸引力，没有产品，只有一个想法。但当时Y Combinator的一位合伙人，Daniel Gross，他曾在苹果工作，参与过Siri项目，我收到了一封邮件，内容是“嘿，Daniel想问你的准确率是多少？”然后第二天他们就说：“嘿，我们很乐意邀请你来面试。”

And so I bought a ticket home. I flew back to San Francisco where I was living at the time. The next day, drove down to Y Combinator for the interview, got in and I'd submitted the application. It was like 30 days late, past the deadline. I went in the first day and it was like all these other companies had so much progress, so much traction, and I was just getting started and it was a really hard idea to get started with like creating AI models for speech. That was probably one of the most stressful periods of my life. It was like those three months in YC where I was just like really trying to get things off the ground working mostly by myself. 于是我买了回家的机票。我飞回了当时居住的旧金山。第二天，我开车去了Y Combinator参加面试，然后成功入选了。我提交申请时已经晚了30天，超过了截止日期。我第一天进去的时候，发现所有其他公司都有很大的进展，获得了很大的关注，而我才刚刚起步，而且为语音创建AI模型是一个非常难的创业方向。那可能是我人生中最有压力的时期之一。那是在Y Combinator的三个月，我基本上是一个人努力让事情步入正轨。

A lot of founders think that getting into Y Combinator raising capital is like just going to make things happen. It doesn't. No investors are going to hand you customers, make your product better, fix things. You still have to make everything happen. So we just again like showed up every day and just tried to make progress and just like kept at it. I've really just tried to focus on is like as long as I feel really happy about the product that we're making and the customers that we have and they're happy, then that's like the validation I'm in search of is do I feel happy about our product? Are customers happy? Like those are the things I try to get validation from, not what do other people think about our company or what we're doing. 很多创始人认为进入Y Combinator并筹集资金就能让事情发生。事实并非如此。投资者不会把客户送到你手上，不会让你的产品变得更好，也不会帮你解决问题。你仍然必须亲力亲为。所以我们每天都坚持不懈，努力取得进展。我真正努力关注的是，只要我对我们正在生产的产品以及我们的客户感到非常满意，并且他们也满意，那么这就是我所寻求的验证。我是否对我们的产品感到满意？客户是否满意？这些才是我试图获得验证的方面，而不是其他人对我们公司或我们正在做的事情的看法。

Lovable：将创意变为现实（广告）

As a founder, you already know ideas are the easy part. It's the execution, actually building the product, that slows everything down. That's where Lovable comes in. It's not just an AI tool. It's your ondemand engineering team. Simply describe your idea. Lovable then builds a full frontend, backend, and database so you can launch real production ready software without writing code. It's already powering over a 100,000 new products a day, helping 2.5 million builders turn ideas into software just by describing what they want. No devs, no delays, no excuses. They're launching in weeks, not months. And guess what? These teams are still tiny. In fact, team EO is also using Lovable to build our upcoming EOS school platform, and we're loving it. If you're a non-technical founder or just want to build without bottlenecks, try Lovable today for free. Use the promo code EO2YT to get 20% off your first purchase of the Lovable Pro plan. 作为一名创始人，你已经知道想法是容易的部分。真正拖慢一切的是执行，是实际构建产品。这就是Lovable的作用所在。它不仅仅是一个AI工具，更是你的按需工程团队。只需描述你的想法，Lovable就会构建完整的前端（前端：用户直接交互的界面部分）、后端（后端：处理数据和业务逻辑的服务器端）和数据库（数据库：存储和管理数据的系统），让你无需编写代码就能发布真正可投入生产的软件。它已经每天为超过10万个新产品提供支持，帮助250万开发者通过描述他们的需求，将想法转化为软件。没有开发人员，没有延迟，没有借口。他们能在几周内而非几个月内发布产品。你猜怎么着？这些团队仍然很小。事实上，EO团队也在使用Lovable来构建我们即将推出的EOS学校平台，我们非常喜欢它。如果你是非技术创始人，或者只是想在没有瓶颈的情况下进行构建，今天就免费试用Lovable吧。使用优惠码EO2YT，首次购买Lovable Pro计划可享八折优惠。

深入市场与客户洞察

Most of my day is spent talking to customers, working with our product teams, playing with our product, and seeing where it's working, where it's not. Founders and startups, you really need to have this deep deep subject matter expertise in your market and in your customers in your product. I think in a lot of ways it's like undervalued and underappreciated versus functional expertise. Don't always have a lot of confidence in your functional expertise. And I think that's where startups can win. You know, there's a lot of people out there that have amazing functional expertise, but don't have the deep subject matter expertise that you have or that your team has over a certain market or a certain customer or product. 我大部分时间都花在与客户交流、与产品团队合作、试用我们的产品，并观察它的优缺点。作为创始人和初创公司，你真的需要对你的市场、客户和产品拥有深入的专业知识。我认为在很多方面，相比于功能性专业知识，这种专业知识被低估和不被重视了。不要总是对你的功能性专业知识抱有太多信心。我认为这就是初创公司能够获胜的地方。你知道，有很多拥有出色功能性专业知识的人，但他们没有你或你的团队在特定市场、特定客户或产品方面所拥有的深层专业知识。

And so, when I talk to customers, I don't want the flattery. I want like where does our product suck? Some of the questions I ask are like, hey, what are the top three things that you don't like about our product? Or if you were in charge of our road map, what would you prioritize? Those types of questions are really helpful because, you know, they give you that feedback and that insight over like where do you need to continue to push. I'm never satisfied with our progress. I really excited about what our customers are building. Like I see some of the apps they launch and they build and it's like I want to go talk about them with my friends cuz they're so cool and inspiring and exciting. 所以，当我与客户交流时，我不想要奉承。我想要知道我们的产品哪里做得不好？我问的一些问题是，比如，你最不喜欢我们产品的哪三点？或者如果你负责我们的路线图，你会优先考虑什么？这类问题真的很有帮助，因为它们能给你反馈和洞察，让你知道需要在哪些方面继续努力。我从不满足于我们的进步。我真的为我们的客户正在构建的东西感到兴奋。我看到他们发布和构建的一些应用程序，就好像我想和我的朋友们谈论它们，因为它们太酷、太鼓舞人心、太令人兴奋了。

And as all these new applications around speech are continuing to take off, the amount of speech data we're handling it just continues to grow rapidly. We'll handle this month alone about five pabytes (Pabytes: 拍字节，数据存储单位，1拍字节约等于1024太字节) of speech data through our API platform. That's about 10x the size of the entire Spotify library and catalog. And usage to our developer platform is growing over 250% year-over-year. So, the scale is like pretty insane. 随着所有这些围绕语音的新应用持续爆发，我们处理的语音数据量也在迅速增长。仅本月，我们将通过我们的API平台处理大约5拍字节的语音数据。这大约是整个Spotify音乐库和目录的10倍。我们的开发者平台使用量同比增长超过250%。所以，这个规模相当惊人。

速度、迭代与专注

Speed is probably more important now than ever. There's so many use cases that we're seeing developers want to build apps around that they need really good speech AI for. They need new capabilities. They need better tech. They need better models. They need, you know, all this stuff. They're hungry for it because the opportunities are enormous. An example of where a lot of speech AI models will struggle today is with hallucinations (Hallucinations: 幻觉，在AI领域指模型生成不真实、不相关或不准确的内容). So having an in-person meeting with 10 people or you're having a phone call and it's windy and the quality is bad, that's where the AI models still do struggle today. And that's an amazing opportunity because there's so many applications that are limited by those things. 现在速度可能比以往任何时候都更加重要。我们看到开发者希望围绕许多用例构建应用程序，他们需要真正优秀的语音AI。他们需要新的功能，更好的技术，更好的模型，他们需要所有这些东西。他们对此充满渴望，因为机会巨大。许多语音AI模型今天仍会遇到困难的一个例子是幻觉。例如，在有10人的面对面会议中，或者在风大的电话通话中，语音质量很差，这就是AI模型今天仍然会遇到困难的地方。这是一个巨大的机会，因为有太多应用程序受到这些因素的限制。

And so we're really excited to keep making the models that we're creating better and better. And as a startup company, you want to try to optimize everything you can for speed. You can start by just putting up a website and advertising the product that you want to build and just putting like a, you know, contact us button on there and see what are people reaching out about, are people reaching out, what do they want from your product and that can be really helpful to get validation early on are you building the right thing before you go spend a ton of time building. So I think that really fast iteration loop is important for startups to have with customers and the markets that you're working in. 所以我们非常高兴能够不断改进我们正在创建的模型。作为一家初创公司，你希望尽可能地优化一切以提高速度。你可以从搭建一个网站开始，宣传你想要构建的产品，并在上面放一个“联系我们”按钮，看看人们都在咨询什么，是否有用户联系，他们对你的产品有什么需求。这对于在投入大量时间构建之前，尽早验证你是否在做正确的事情非常有帮助。所以我认为，对于初创公司来说，与客户和市场之间建立快速迭代循环非常重要。

When you're making an AI model like at so many points you have to decide between trade-offs, right? What type of data do you use? What type of thing do you optimize for? When you know who you're building this AI model for, then you can make all those trade-offs a lot more intelligently in a way that makes your AI model have more product market fit (Product Market Fit: 产品市场契合度，指产品在一个良好的市场中满足了该市场的需求) for who you're building it for. You can always change your focus as you learn, right? But I think it's important to like have a focus and then you learn and then you can focus other areas. 当你制作一个AI模型时，在很多地方你都必须在权衡之间做出选择，对吧？你使用什么类型的数据？你为哪种东西进行优化？当你明确了为谁构建这个AI模型时，你就可以更智能地做出所有这些权衡，让你的AI模型对目标用户具有更好的产品市场契合度。你总是可以在学习过程中改变你的重点，对吧？但我认为重要的是先有一个重点，然后你学习，然后你可以关注其他领域。

Like we're super laser focused on, okay, people building voice agents, people building notetakers, people building sales intelligence apps, these are the 10 things they really, really care about. And so, let's make sure our models are hyper optimized for those things. And let's build the right training data and let's build the right model architectures and let's do all of the things we can to absolutely max out in those dimensions. And that's how we're constantly keeping our models the most accurate and the easiest to use for the developers that we're building for. 比如我们高度专注于：那些构建语音助手、笔记应用和销售智能应用的人，他们真正关心的是这10件事。因此，我们要确保我们的模型针对这些方面进行超优化。我们要构建正确的训练数据，构建正确的模型架构，并尽我们所能，在这些维度上做到极致。这就是我们如何持续为我们服务的开发者提供最准确、最易于使用的模型。

You might come to Assembly and maybe our models aren't as good for you as another model. And usually if that happens, it's because that's not an application or a use case that we're really focusing on. At least not right now. So for us, the way we really maintain our competitive advantage is by just really clearly focusing on who we're building for and not building general purpose tech, but building tech that's optimized for a specific use case and market. 你可能会来到AssemblyAI，也许我们的模型对你来说不如其他模型好。通常如果发生这种情况，那是因为那不是我们真正关注的应用或用例。至少目前不是。所以对我们来说，我们真正保持竞争优势的方式是，非常清晰地专注于我们为谁构建产品，而不是构建通用技术，而是构建针对特定用例和市场优化的技术。

独特的创业旅程

One of the biggest things I've learned is that every startup, you have your own journey. It's easy to compare yourself to other startups. You know, you have friends that are founders and maybe they're a stage or two ahead. But startups are not franchise businesses, I think, is one of the biggest things that I've learned. And what I mean by that is like you have to really figure out what your journey is. And every journey is slightly different. And there's a lot of startup dogma that you don't have to subscribe to. And in a lot of ways can actually make it harder for you as a founder because you feel like there's all this stuff you have to do when in reality you just have to really build a great product, make your customers happy and that's what you want to focus on. 我学到的最重要的事情之一是，每个初创公司都有自己的旅程。你很容易将自己与其他初创公司进行比较。你知道，你有一些创始人朋友，他们可能领先你一两个阶段。但我认为，初创公司不是特许经营业务，这是我学到的最重要的事情之一。我的意思是，你必须真正弄清楚你自己的旅程是什么。而且每个旅程都略有不同。有很多创业教条你不需要盲目遵循。在很多方面，这些教条实际上会让你作为创始人更难，因为你觉得有很多事情必须做，而实际上，你只需要真正构建一个出色的产品，让你的客户满意，这才是你应该关注的。

That realization has helped me a lot as a founder realizing, okay, we're on our own journey. Startups are all look different. All their journeys are different. And just be really focused on making a great product, on making customers super happy. And that's that's the north star. 这个认知作为创始人对我帮助很大，让我意识到，好吧，我们正在走自己的路。所有初创公司看起来都不同。它们的所有旅程都不同。你只需要真正专注于打造一个伟大的产品，让客户超级满意。这才是指引方向的北极星。