The AI Future Has Arrived: Here's What You Should Do About It

这段视频讨论了人工智能的变革潜力，并敦促观众利用他们对这项技术的认识来改善生活和事业。演讲者道尔顿和迈克尔强调，人工智能不是一种潮流，而是一个与互联网、智能手机和比特币的出现相当的重要趋势。他们认为，那些尽早认识并采取行动的人将获得巨大的优势。 核心信息围绕着这样一个观点：我们正处于一个类似于互联网早期发展的关键时刻。正如早期采用网络浏览器、Gmail、iPhone和比特币的人能够利用他们的知识获利一样，现在理解并参与人工智能的人也能够体验到深刻的积极变化。演讲者明确表示，坐拥这种知识是一种浪费机会。 他们为观众提供了几个可行的步骤供考虑： **1. 创业：** 如果有人曾经考虑过创业，现在就是理想的时机。人工智能驱动型企业的大环境已经成熟。不要被那些将人工智能视为炒作的人吓退；相反，回顾历史，在重大技术变革之后，涌现出了许多具有变革意义的公司。工具、模型和知识都足以构建以前无法想象的应用程序。他们特别强调了Y Combinator (YC)在人工智能领域取得成功的公司。 **2. 明智地选择工作地点：** 仔细考虑你的工作地点，优先选择那些积极采用人工智能工具并且能够从这项技术中受益的公司。至关重要的是，你要被精通人工智能并能从中学习的人所包围。演讲者认为，初创公司可能比大型企业更快地采用人工智能，从而提供更多的实践学习经验。 **3. 发展相关技能：** 他们鼓励观众提升人工智能相关领域的技能，无论他们目前的教育水平如何。进入门槛相对较低，在线资源丰富，尤其是YouTube。从头开始学习人工智能的工作原理是无价的，并将提供终身的优势。 **4. 成为用户：** 积极使用人工智能产品和服务。不要等到它们“完美”再使用。寻找更好的工具，并准备好为此付费。在理解该技术的能力和局限性方面，现实世界的经验是无价的。就像Google的采用使信息更容易找到一样，找到能够提高生产力的人工智能是值得投入的。 **5. 不要无所作为：** 最重要的信息是采取行动。根据这些信息做出改变。利用你的知识来抓住人工智能革命的机遇。拖延会导致机会的浪费。 他们还提到了一种观点，即在人工智能驱动的世界中，编程技能可能变得不那么具有战略意义。他们认为，虽然编程的某些方面，例如记忆API，可能不再那么重要，但对人工智能工作原理的深刻理解将会受到高度重视。当问题发生时，需要有人来解决问题并理解人工智能在做什么。演讲者认为，调试技能和对人工智能基础知识的理解仍然是必需的，并且不容易被取代。即使你不懂技术，与技术联合创始人合作也比以往任何时候都更加重要。 最后，他们讨论了人工智能进一步发展的可能性，并指出变化的速率和新模型的出现表明，我们尚未达到“规模化瓶颈”。他们的结论是，人工智能将继续改进，因此现在参与这项技术变得更加重要。早期和聪明的创始人将最适合抓住这波新进展的浪潮。

The video discusses the transformative potential of AI and urges viewers to leverage their awareness of this technology to improve their lives and careers. The speakers, Dalton and Michael, emphasize that AI is not a fad but a significant trend comparable to the advent of the internet, smartphones, and Bitcoin. They argue that those who recognize and act upon this insight early will gain a substantial advantage. The core message revolves around the idea that we are at a pivotal moment similar to the early days of the internet. Just as early adopters of web browsers, Gmail, iPhones, and Bitcoin could capitalize on their knowledge, those who understand and engage with AI now can experience profound positive changes. The speakers explicitly state that sitting on this knowledge is a wasted opportunity. They offer several actionable steps for viewers to consider: **1. Start a Company:** If one has ever considered starting a company, now is the ideal time. The landscape is ripe for AI-driven businesses. Don't be deterred by those who dismiss AI as hype; instead, look to history, where transformative companies emerged after significant technological shifts. The tools, models, and knowledge are sufficient to build applications previously unimaginable. They highlight the Y Combinator (YC) successes with companies that have been revolutionized by AI. **2. Choose Your Workplace Wisely:** Carefully consider where you work, prioritizing companies that are actively adopting AI tools and that can benefit from the technology. It's crucial to be surrounded by individuals who are proficient in using AI and from whom you can learn. The speakers suggest that startups may be adopting AI more quickly than large corporations, offering more hands-on learning experiences. **3. Develop Relevant Skills:** They encourage viewers to upskill in AI-related areas, regardless of their current education level. The barrier to entry is relatively low, with numerous resources available online, particularly YouTube. Learning how AI works from scratch is invaluable and will provide a lifelong advantage. **4. Become a User:** Actively use AI products and services. Don't wait for them to be "perfect." Look for better tools, and be prepared to pay for them. Real-world experience is invaluable in understanding the technology's capabilities and limitations. Like the adoption of Google where information became easier to find, finding an AI that increases productivity is worth the cost. **5. Don't Do Nothing:** The overarching message is to take action. Change something in response to this information. Use your knowledge to capitalize on the AI revolution. Procrastination leads to wasted opportunities. They also address the notion that programming skills might become less strategic in an AI-driven world. They argue that while some aspects of programming, like memorizing APIs, might be less critical, a deep understanding of how AI works will be highly valued. Someone needs to fix the issues when they happen and understand what the AI is doing. The speakers maintain that debug skills and the understanding of the foundations of AI are going to remain a necessity and will not be readily replaced. Even if one is not technical, it's more important than ever to partner with technical co-founders. Finally, they address the likelihood of further advancements in AI, noting that the rate of change and the emergence of new models suggest that we haven't reached a "scaling wall." They conclude that AI will continue to improve, making it even more critical to engage with the technology now. Early and smart founders will be best positioned to ride that new wave of progress.