OpenAI o1式思维链，开源模型也可以有，成功案例来了

北京时间 9 月 13 日午夜，OpenAI 发布了推理性能强大的 ο1 系列模型。之后，各路研究者一直在尝试挖掘 ο1 卓越性能背后的技术并尝试复现它。

---

当然，OpenAI 也想了一些方法来抑制窥探，比如有多名用户声称曾试图诱导 ο1 模型公布其思维过程，然后收到了 OpenAI 的封号威胁。

尽管如此，不过三四天时间，就已经有研究者宣称已经成功复现/开发出了与 ο1 性能差不多的推理技术，并且还不止一个！

Llamaberry：教会 AI 像聪明人一样思考

Llamaberry 的提出者是 Martin Bowling。他开发的项目包括 RAGMiner.dev 和 Replit；其中前者可以帮助用户毫不费力地将网站转换成 Markdown、XML 或 JSON 等格式以便 RAG 和 LLM 应用使用，而后者则是一个使用 AI 将想法变成代码的项目。

Llamaberry 的核心思路是使用思维链（CoT）来实现推理。这个名字自然源自代表 o1 模型的 Strawberry（草莓）。

HuggingFace地址：https://huggingface.co/spaces/martinbowling/Llamaberry

什么是思维链？Bowling 在博客中打了个比方：「思维链推理就像是给 AI 一个笔记本来展示其工作过程。其中不仅仅是简单地给出答案，而是会带领我们经历其思维过程。」

Llamaberry 能教会 AI 透彻地思考，就像是一位人类专家攻克难题时那样。

具体来说，Llamaberry 是一个多轮思维链推理系统的实现，其基于运行在 Groq 上的 Llama 3.1 70B 模型。

多轮推理是关键

多轮推理，顾名思义，就是让模型在给出答案之前进行多步思考，而不是一步给出答案。打个比方，这就像是看一位大厨从备菜到完成摆盘一步步地完成一道精美菜肴，而不是直接微波加热预制菜。

举个示例：

第 1 轮：AI 先尝试解决当前问题。
第 2 轮：AI 回顾第一次尝试并尽力改进或优化其思维过程。
第 3 轮：再进行一轮反思和改进。
综合结果：最后，将所有这些思考综合到一起，得到一个连贯且合理的答案。

下面展示了这个多轮过程的示意图：

可以看到，前一轮的输出会成为后一轮的输入，从而让 AI 可在每个阶段不断完善其思维。最后，所有这些…

如何实现

下面将深入 Llamaberry 的实现细节。

1.设置舞台

首先，我们需要为 AI 助手设置一些基本规则，代码如下：

initial_system_prompt = “””You are an AI assistant capable of detailed, step-by-step thinking. When presented with a question or problem, break down your thought process into clear, logical steps. For each step, explain your reasoning. Conclude with a final answer. Use the following markdown structure:

Reasoning

1. [First step]
   Explanation: [Detailed explanation of this step]
2. [Second step]
   Explanation: [Detailed explanation of this step]
   …

Answer

[Final answer]

Be comprehensive and show your reasoning clearly.”””

这就是提供给 AI 大厨的菜谱。它知道需要逐步…

2.思考过程

在每一轮推理中，都需要让 AI 对问题进行思考。但在第一轮结束后，还需要求它思考之前已经思考过的东西。这就像问朋友，「嘿，还记得你之前说过什么吗？让我们再想一想。」

下面是每一轮的生成方式：

async def generate_turn(query: str, previous_turns: list = None) -> str:
is_first_turn = previous_turns is None or len(previous_turns) == 0
if is_first_turn:
messages = [{
“role”: “system”,
“content”: initial_system_prompt
…

综合结果

经过三轮思考之后，再让 AI 检视其所有思考并得出一个合理的最终答案。这就像是让专家讨论问题，然后编写最终报告。

async def synthesize_turns(query: str, turns: list) -> str:
turns_text = “\n\n”.join(
[f”Turn {i+1}:\n{turn}” for i, turn in enumerate(turns)])
messages = [{
“role”: “system”,
“content”: synthesis_prompt
}, {
“role”:
“user”,
“content”:
f”Original Query: {query}\n\nTurns of Reasoning:\n{turns_text}”
…
单轮推理 vs 多轮推理

Martin Bowling 在其博客中简单比较了单轮和多轮推理。

这里他采用了一个简单示例，即询问 AI：「人工智能对就业市场有什么潜在影响？」

单轮推理：

AI: Artificial intelligence will likely have significant impacts on the job market, including:

1. Automation of routine tasks
2. Creation of new job roles in AI development and maintenance
3. Potential job displacement in certain industries
   …

使用 Llamaberry 执行多轮推理：

第 1 轮：

AI: Let’s approach this step-by-step:

1. Identify current AI capabilities
   Explanation: AI can perform data analysis, pattern recognition, and automate routine tasks.

2. Analyze vulnerable job sectors
   Explanation: Manufacturing, customer service, and data entry are likely to be affected.

3. Consider new job opportunities
   Explanation: AI development, data science, and AI ethics consultation may see growth.

4. Examine potential economic effects
   Explanation: Increased productivity might lead to economic growth, but wealth distribution could be a challenge.

Initial Answer: AI will likely cause significant shifts in the job market, with both job losses in some sectors and new opportunities in others.

第 2 轮：

AI: Let’s refine our thinking:

1. Reassess the timeline of AI impact
   Explanation: The effects won’t be immediate but will unfold over years or decades.

2. Consider the adaptability of the workforce
   Explanation: Retraining and education will be crucial for workers to transition to new roles.

3. Analyze potential societal changes
   Explanation: The nature of work itself might change, with more emphasis on creativity and emotional intelligence.

4. Examine global differences
   Explanation: AI’s impact will vary across different countries and economies.

Refined Answer: AI’s impact on the job market will be complex and gradual, requiring proactive measures in education and economic policy to ensure a smooth transition.

第 3 轮：

AI: Let’s delve deeper:

1. Explore the concept of human-AI collaboration
   Explanation: Many jobs may evolve to involve working alongside AI rather than being replaced by it.

2. Consider the ethical implications
   Explanation: Issues like algorithmic bias in hiring processes need to be addressed.

3. Analyze the potential for new economic models
   Explanation: Universal Basic Income or reduced working hours might become more prominent discussions.

4. Examine historical parallels
   Explanation: Previous technological revolutions, like the Industrial Revolution, can offer insights into potential outcomes.

Further Refined Answer: While AI will undoubtedly transform the job market, its impact will likely be nuanced, involving collaboration between humans and AI, ethical considerations, and potentially new economic paradigms.

综合答案：
…
。注意：Title、Date、Body 三个部分的内容，放入到对应的位置。最后只需要按照格式标准输出为Makedown源文件格式内容。

感谢阅读！如果您对AI的更多资讯感兴趣，可以查看更多AI文章：GPTNB。