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feat: 新增 OpenAI 12 天发布会总结文章 (#168)
* feat: 新增 OpenAI 12 天发布会总结文章,涵盖 ChatGPT Pro 服务、o1 和 Sora 模型发布及应用层面更新 * feat: 添加中英文版本的 OpenAI 12 天发布会总结文章,涵盖 ChatGPT Pro 服务、o1 和 Sora 模型发布及逻辑推理问题
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---
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title: OpenAI 12 Days 事件总结
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categories: [ai, openai]
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date: 2024-12-22
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author: iugo
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last_modified_at: 2024-12-22 10:00+08:00
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---
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<details lang="zh" open>
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<summary>中文版本</summary>
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<div markdown="1">
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## 发布会
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OpenAI 最新办了一场 12 天 "发布会": <https://openai.com/12-days/>
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国内文章: <https://www.infoq.cn/article/WXPMviOWQ1LNZhqZC5ZE>
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总结这几天的内容, 核心为:
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1. ChatGPT Pro 服务, 200 美元/月 (Day 1)
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2. 正式发布 o1 模型 (Day 1, 9)
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3. 正式发布 Sora 模型 (Day 3)
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4. 技术预览 (微调与 o3 模型) (Day 2, 12)
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5. 更多应用层面的更新 (创作者助手, 苹果集成, 会话整理, 多媒体信息, 搜索,
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电话版 ChatGPT 等) (Day 4, 5, 6, 7, 8, 10, 11)
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应用层面的创建无疑是收入的一个重要增长点. 但是对于 OpenAI 来说, 应用不是撒手锏,
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模型才是.
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所以这里面除了影响营收的 Pro 版本的收费, Sam 仅参加了模型相关发布 o1, Sora, o3.
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## 模型
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感觉有意义的点还不如 Ilya Sutskever 在 NeurIPS 2024 的演讲.
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不过都在一个发力: **逻辑性**
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AI 的幻觉问题比较严重, 这个问题其实也是 AI 缺乏逻辑性的一个表现.
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可是人类的神经元就可以让自己有逻辑, 那 AI 为什么不能?
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这就是 AI 的下一步方向, 不是找更多数据, 而是利用当前数据如何让 "逻辑性" 显现.
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这种逻辑性, 而非知识性的问题我们也遇到了. 针对一些稍微复杂一点的逻辑问题,
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当前主流模型都回答得不好 (应该说不对).
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</div>
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</details>
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<details lang="en">
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<summary>English Version</summary>
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<div markdown="1">
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## Launch Event
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OpenAI recently held a 12-day "launch event": <https://openai.com/12-days/>
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Key announcements during these days include:
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1. ChatGPT Pro service at $200/month (Day 1)
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2. Official release of o1 model (Day 1, 9)
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3. Official release of Sora model (Day 3)
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4. Technical previews (fine-tuning and o3 model) (Day 2, 12)
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5. More application-level updates (Creator Assistant, Apple integration,
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conversation organization, multimedia handling, search, phone version of
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ChatGPT, etc.) (Day 4, 5, 6, 7, 8, 10, 11)
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Application-level innovations are undoubtedly an important growth point for
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revenue. However, for OpenAI, applications are not their trump card - models are.
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That's why among all these announcements, Sam only participated in model-related
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releases: o1, Sora, and o3.
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## Models
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The meaningful points here are not as significant as Ilya Sutskever's speech at
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NeurIPS 2024.
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However, they all focus on one direction: **logical reasoning**
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AI's hallucination problem is quite serious, which is actually a manifestation
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of AI's lack of logical reasoning ability.
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Human neurons can enable logical thinking, so why can't AI?
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This is the next direction for AI - not finding more data, but utilizing existing
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data to manifest "logical reasoning".
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We've also encountered this issue of logical reasoning versus knowledge. Current
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mainstream models don't perform well (or more accurately, don't perform correctly)
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on slightly more complex logical problems.
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</div>
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</details>

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