我们从一年的与LLMs建设中学到了什么（第一部分）

Learn faster. Dig deeper. See farther.

学得更快。挖得更深。看得更远。

It’s an exciting time to build with large language models (LLMs). Over the past year, LLMs have become “good enough” for real-world applications. The pace of improvements in LLMs, coupled with a parade of demos on social media, will fuel an estimated $200B investment in AI by 2025. LLMs are also broadly accessible, allowing everyone, not just ML engineers and scientists, to build intelligence into their products. While the barrier to entry for building AI products has been lowered, creating those effective beyond a demo remains a deceptively difficult endeavor.

现在是使用大型语言模型（LLM）进行构建的令人兴奋的时刻。在过去的一年里，LLM已经变得足够“好”，可以用于实际应用。LLM的改进速度以及社交媒体上的一系列演示将推动到2025年AI领域的预计2000亿美元的投资。LLM也广泛可用，使每个人都能够将智能引入他们的产品中，而不仅仅是机器学习工程师和科学家。尽管构建AI产品的门槛已经降低，但要创建出超越演示的有效产品仍然是一项具有欺骗性的艰巨任务。

We’ve identified some crucial, yet often neglected, lessons and methodologies informed by machine learning that are essential for developing products based on LLMs. Awareness of these concepts can give you a competitive advantage against most others in the field without requiring ML expertise! Over the past year, the six of us have been building real-world applications on top of LLMs. We realized that there was a need to distill these lessons in one place for the benefit of the community.

我们已经确定了一些关键但常常被忽视的机器学习启示和方法论，这些对于基于LLMs开发产品至关重要。了解这些概念可以让您在不需要机器学习专业知识的情况下，在该领域中与大多数其他人竞争时具有竞争优势！在过去的一年里，我们六个人一直在基于LLMs构建实际应用程序。我们意识到有必要将这些经验总结在一个地方，以造福社区。

We come from a variety of backgrounds and serve in different roles, but we’ve all experienced firsthand the challenges that come with using this new technology. Two of us are independent consultants who’ve helped numerous clients take LLM projects from initial concept to successful product, seeing the patterns determining success or failure. One of us is a researcher studying how ML/AI teams work and how to improve their workflows. Two of us are leaders on applied AI teams: one at a tech giant and one at a startup. Finally, one of us has taught deep learning to thousan...