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2025-04-16
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AI攻克半世纪难题,华人学者崭露头角

人工智能再次刷新科学探索的边界!一位名为 Weiguo Yin 的华人学者,利用 OpenAI 的 o3-mini-high 模型,成功"啃"下了一个困扰学界长达半个世纪的数学硬骨头,完成了首个由 AI 辅助的非平凡数学定理证明。这事儿,有点意思,或许真能打开物理学研究的新局面。

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编辑
2025-04-16
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谷歌“海豚语”翻译器问世!星际迷航情节要上演?

Google's "Dolphin Language" Translator is Here! Is a Star Trek Plot About to Unfold? 🐬✨

谷歌最近扔出个重磅炸弹——DolphinGemma,一个能破译海豚叫声的AI模型。等等,这难道不是科幻电影里的情节吗?

Google recently dropped a bombshell – DolphinGemma, an AI model that can decipher dolphin sounds. Wait, isn't this something straight out of a sci-fi movie? 🤯

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编辑
2025-04-16
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OpenAI发布GPT-4.1系列模型,支持百万token上下文且价格更低

简报:

  • OpenAI于4月15日发布GPT-4.1系列模型,包括GPT-4.1、GPT-4.1 mini和GPT-4.1 nano三款
  • 新模型全系支持100万token上下文窗口,是GPT-4o的8倍
  • 在编程、指令遵循和长文本理解方面表现优于GPT-4o系列
  • GPT-4.1 nano是OpenAI迄今最快、最便宜的模型
  • 目前仅通过API向开发者开放,普通用户无法在ChatGPT中使用
  • GPT-4.5预览版API将于2025年7月14日弃用
  • 价格方面,GPT-4.1比GPT-4o中等规模查询成本低26%
Token /ˈtoʊ·kən/
n. 令牌;标记
"GPT-4.1 supports a context window of 1 million tokens."
[例句] GPT-4.1支持100万token的上下文窗口。
技术释义
在自然语言处理中,token是文本处理的基本单位,可以是单词、子词或字符。GPT系列模型使用token作为输入输出的基本单元,100万token约相当于75万英文单词。
相关术语
tokenization (n.) 分词处理
context window (n.) 上下文窗口

编辑
2025-04-15
News
00

抽一包烟、吃根香蕉、核电站“上班”,谁给你的辐射更大?

说起辐射,大家难免紧张。但抛开剂量谈影响,那都是耍流氓!今天咱们就来聊聊,抽烟、吃香蕉、在核电站工作,这三件事儿,哪个让你暴露在更大的辐射风险之下?

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Which gives you more radiation: Smoking a pack of cigarettes, eating a banana, or "working" at a nuclear power plant?

When it comes to radiation, people inevitably get nervous. But talking about effects without considering the dosage is just nonsense! Today, let's talk about which of these three things - smoking cigarettes, eating bananas, or working at a nuclear power plant - exposes you to a greater radiation risk?

编辑
2025-04-15
News
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苹果AI首秀翻车?Siri 升级疑成"PPT演示"

Apple's AI Debut a Flop? Siri Upgrade Suspected of Being a "PPT Presentation"

发布会Demo引质疑:苹果AI落地,真能行?

苹果WWDC 2024上,Siri大秀了一把AI新功能,但发布会后,质疑声浪不小。有前苹果员工直接爆料,说他们根本没见过发布会上演示的那些功能真正跑起来过。这不禁让人怀疑,苹果在AI上的实力,是不是PPT做得比实际强?

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Doubts Raised About Demo at Launch Event: Can Apple's AI Implementation Really Work?

At Apple's WWDC 2024, Siri showcased a bunch of new AI features, but after the launch event, there was a significant wave of skepticism. A former Apple employee even directly revealed that they had never seen the features demonstrated at the launch event actually running. This raises doubts about whether Apple's strength in AI is more about impressive PPT presentations than actual capabilities. 🤔