目前能力最强的 AI 是 GPT-4。GPT-4 是功能最强的人工智能写作工具，您可以在 Bing（选择“创新模式”）上免费访问，或者通过购买 ChatGPT 的$20/月订阅来使用。Claude 也是表现出色的 AI，紧随其后，并且提供了有限的免费选项。这些工具还被直接集成到常见的办公应用程序中，例如 Microsoft Office 将包括一个由 GPT 提供支持的副驾驶，Google Docs 将整合 Bard 的建议。
最佳免费选项：[Bing](https://www.bing.com/search?q=Bing+AI&showconv=1&FORM=hpcodx)和[Claude 2](https://claude.ai/)付费选项：带有插件的[ChatGPT](https://chat.openai.com/chat)4.0/ChatGPT目前，GPT-4仍然是功能最强的人工智能写作工具，你可以在Bing（选择“创新模式”）上免费访问，或者通过购买ChatGPT的$20/月订阅来访问。然而，Claude是紧随其后的第二名，也提供了有限的免费选项。这些工具也被直接集成到常见的办公应用程序中。Microsoft Office将包括一个由GPT提供支持的副驾驶，Google Docs将整合Bard的建议。[这些新创新对写作的意义是相当深远的。](https://www.oneusefulthing.org/p/setting-time-on-fire-and-the-temptation)以下是一些使用人工智能帮助您写作的方法。
OpenAI在其内部会议上分享了关于通用人工智能（AGI）的五个发展等级。OpenAI自2015年成立以来，一直将AGI作为其战略目标之一，随着ChatGPT、多模态大模型和AI Agent等技术的发展，我们似乎越来越接近实现这一目标。AGI的五个等级分别为：1.聊天机器人（Chatbots）：具备基本对话能力的AI，主要依赖预设脚本和关键词匹配，用于客户服务和简单查询响应。2.推理者（Reasoners）：具备人类推理水平的AI，能够解决复杂问题，如ChatGPT，能够根据上下文和文件提供详细分析和意见。3.智能体（Agents）：不仅具备推理能力，还能执行全自动化业务的AI。目前许多AI Agent产品在执行任务后仍需人类参与，尚未达到完全智能体的水平。4.创新者（Innovators）：能够协助人类完成新发明的AI，如谷歌DeepMind的AlphaFold模型，可以预测蛋白质结构，加速科学研究和新药发现。5.组织（Organizations）：最高级别的AI，能够自动执行组织的全部业务流程，如规划、执行、反馈、迭代、资源分配和管理等。
Here is one narrow way to look at human history:after thousands of years of compounding scientific discovery and technological progress,we have figured out how to melt sand,add some impurities,arrange it with astonishing precision at extraordinarily tiny scale into computer chips,run energy through it,and end up with systems capable of creating increasingly capable artificial intelligence.This may turn out to be the most consequential fact about all of history so far.It is possible that we will have superintelligence in a few thousand days(!); it may take longer,but I’m confident we’ll get there.How did we get to the doorstep of the next leap in prosperity?In three words:deep learning worked.In 15 words:deep learning worked,got predictably better with scale,and we dedicated increasing resources to it.That’s really it; humanity discovered an algorithm that could really,truly learn any distribution of data(or really,the underlying “rules” that produce any distribution of data).To a shocking degree of precision,the more compute and data available,the better it gets at helping people solve hard problems.I find that no matter how much time I spend thinking about this,I can never really internalize how consequential it is.There are a lot of details we still have to figure out,but it’s a mistake to get distracted by any particular challenge.Deep learning works,and we will solve the remaining problems.We can say a lot of things about what may happen next,but the main one is that AI is going to get better with scale,and that will lead to meaningful improvements to the lives of people around the world.AI models will soon serve as autonomous personal assistants who carry out specific tasks on our behalf like coordinating medical care on your behalf.At some point further down the road,AI systems are going to get so good that they help us make better next-generation systems and make scientific progress across the board.