{
  "schema_version": 1,
  "project": {
    "id": "2ff4b87b-2904-4b9c-b9e9-bdbd72962691",
    "name": "Fall 26 - Lecture 06",
    "url": "https://deepnote.com/workspace/ise3309jingao-5ba66b0a-4283-4f5a-ae06-3f68d3201e99/project/Fall-26-Lecture-06-2ff4b87b-2904-4b9c-b9e9-bdbd72962691?utm_source=openai&utm_medium=mcp&utm_campaign=openaimcp&utm_content=2ff4b87b-2904-4b9c-b9e9-bdbd72962691&utm_term=get_project"
  },
  "notebooks": [
    {
      "key": "CLS00",
      "id": "a96e110cfb0d4b28b79d41a01b714f92",
      "title": "CLS 00 · 第六讲实验导航",
      "url": "https://deepnote.com/workspace/ise3309jingao-5ba66b0a-4283-4f5a-ae06-3f68d3201e99/project/Fall-26-Lecture-06-2ff4b87b-2904-4b9c-b9e9-bdbd72962691/notebook/CLS-00-a96e110cfb0d4b28b79d41a01b714f92?utm_source=openai&utm_medium=mcp&utm_campaign=openaimcp&utm_content=a96e110cfb0d4b28b79d41a01b714f92&utm_term=get_notebook",
      "summary": "先按课堂问题找到本册和活动，再核对准备条件与证据类型。",
      "sections": []
    },
    {
      "key": "CLS01",
      "id": "e2c2fce2f81b40d59356bfe7a63361b0",
      "title": "CLS 01 · 训练目标与资源账本",
      "url": "https://deepnote.com/workspace/ise3309jingao-5ba66b0a-4283-4f5a-ae06-3f68d3201e99/project/Fall-26-Lecture-06-2ff4b87b-2904-4b9c-b9e9-bdbd72962691/notebook/CLS-01-e2c2fce2f81b40d59356bfe7a63361b0?utm_source=openai&utm_medium=mcp&utm_campaign=openaimcp&utm_content=e2c2fce2f81b40d59356bfe7a63361b0&utm_term=get_notebook",
      "summary": "对齐本讲的 8B 配置，分别计算训练目标、参数状态与资源账本。",
      "sections": []
    },
    {
      "key": "LAB01",
      "id": "e1f6f8c1ebd543c5ade548e0af61edc1",
      "title": "LAB 01 · 记忆：写入、读回与容量",
      "url": "https://deepnote.com/workspace/ise3309jingao-5ba66b0a-4283-4f5a-ae06-3f68d3201e99/project/Fall-26-Lecture-06-2ff4b87b-2904-4b9c-b9e9-bdbd72962691/notebook/LAB-01-e1f6f8c1ebd543c5ade548e0af61edc1?utm_source=openai&utm_medium=mcp&utm_campaign=openaimcp&utm_content=e1f6f8c1ebd543c5ade548e0af61edc1&utm_term=get_notebook",
      "summary": "固定查询与目标，比较写入、读回、干扰、选择性和容量。",
      "sections": [
        {
          "key": "M1",
          "title": "M1 · 同一查询与目标，写得更多会怎样？",
          "block_id": "90410919d6644f819f533e400dca3dae"
        },
        {
          "key": "M2",
          "title": "M2 · 改写入，还是改读取？",
          "block_id": "96c41419751341a8a0b667aaa5a447f5"
        },
        {
          "key": "M3",
          "title": "M3 · 归一化、选择性与有限容量扫描",
          "block_id": "61fb56544b374691b3eef5ed9d93bcbb"
        },
        {
          "key": "M4",
          "title": "M4 · 参数不变，内容可变；选择性也会放大错误",
          "block_id": "22f75058ab9d4d329b48a19e57a978b9"
        }
      ]
    },
    {
      "key": "LAB02",
      "id": "e6eecd2d72554ef4adacc0b797db4b32",
      "title": "LAB 02 · 视觉：学到了什么，怎样验证",
      "url": "https://deepnote.com/workspace/ise3309jingao-5ba66b0a-4283-4f5a-ae06-3f68d3201e99/project/Fall-26-Lecture-06-2ff4b87b-2904-4b9c-b9e9-bdbd72962691/notebook/LAB-02-e6eecd2d72554ef4adacc0b797db4b32?utm_source=openai&utm_medium=mcp&utm_campaign=openaimcp&utm_content=e6eecd2d72554ef4adacc0b797db4b32&utm_term=get_notebook",
      "summary": "区分训练、表示与独立评测；用配对干预和原研究图证检验解释。",
      "sections": [
        {
          "key": "V1",
          "title": "V1 · 训练目标下降，权重真的变了吗？",
          "block_id": "53d432e203fc440ebba39d9c09c21895"
        },
        {
          "key": "V2",
          "title": "V2 · 同一留出集：重建改善，读出也改善吗？",
          "block_id": "09c58e6186c64aa6a3392245acbca957"
        },
        {
          "key": "V3",
          "title": "V3 · 哪些单元被用到了？先选候选，再做配对干预",
          "block_id": "6ea12ebcb1a94634ad76ca46cfec6442"
        },
        {
          "key": "V4",
          "title": "V4 · 原研究证据台：预测、揭示，再审读边界",
          "block_id": "12bf3a75f0404c55bbedc705a3f30485"
        },
        {
          "key": "V5",
          "title": "V5 · 同一个受训表示，怎样落成矩阵计算？",
          "block_id": "b1269a5efcb447548fffc67787021016"
        }
      ]
    },
    {
      "key": "LAB03",
      "id": "9280cd5ad74c43cba2c65cd705ff8dd6",
      "title": "LAB 03 · 文本：目标、数据与参数更新",
      "url": "https://deepnote.com/workspace/ise3309jingao-5ba66b0a-4283-4f5a-ae06-3f68d3201e99/project/Fall-26-Lecture-06-2ff4b87b-2904-4b9c-b9e9-bdbd72962691/notebook/LAB-03-9280cd5ad74c43cba2c65cd705ff8dd6?utm_source=openai&utm_medium=mcp&utm_campaign=openaimcp&utm_content=9280cd5ad74c43cba2c65cd705ff8dd6&utm_term=get_notebook",
      "summary": "从前缀与目标到真实轻量 RNN 更新，再比较材料和计分位置。",
      "sections": [
        {
          "key": "T1",
          "title": "T1 · 完整材料怎样产生多个预测目标？",
          "block_id": "74c6517c9b184283a41a43808dbd1e8f"
        },
        {
          "key": "T2",
          "title": "T2 · 一次 backward 和优化器步，究竟改变了什么？",
          "block_id": "7b37d910f87943aebb396f3416ebb3c6"
        },
        {
          "key": "T3",
          "title": "T3 · 预算相同，只改变反复出现的材料",
          "block_id": "87e602bc25c841da9cd1fbf3d3e288f8"
        },
        {
          "key": "T4",
          "title": "T4 · 只给回应计分，会改变可读范围吗？",
          "block_id": "a10fcbd9065c405baa1fe8530af6a535"
        }
      ]
    },
    {
      "key": "LAB04",
      "id": "8d38f8a6b20944129b6587b282ab38d2",
      "title": "LAB 04 · 上下文：固定参数的对照",
      "url": "https://deepnote.com/workspace/ise3309jingao-5ba66b0a-4283-4f5a-ae06-3f68d3201e99/project/Fall-26-Lecture-06-2ff4b87b-2904-4b9c-b9e9-bdbd72962691/notebook/LAB-04-8d38f8a6b20944129b6587b282ab38d2?utm_source=openai&utm_medium=mcp&utm_campaign=openaimcp&utm_content=8d38f8a6b20944129b6587b282ab38d2&utm_term=get_notebook",
      "summary": "核对固定模型的输入与已保存输出，重新评分并检查结论边界。",
      "sections": [
        {
          "key": "I1",
          "title": "I1 · 哪些东西在这次运行中没有改变？",
          "block_id": "98722ed87eac4c9f8f8e47a170892bab"
        },
        {
          "key": "I2",
          "title": "I2 · 对照能回答什么？先核输入，再看输出",
          "block_id": "e17ab6d3843841b7a00d3da644aea46a"
        },
        {
          "key": "I3",
          "title": "I3 · 改一次分析条件，看看结论是否稳固",
          "block_id": "24c067a20fa748269347e230a31b65ae"
        },
        {
          "key": "I4",
          "title": "I4 · 可选新推理：只改示例顺序，留下新证据",
          "block_id": "6b375e33eec343c48ff98426e1c3c54d"
        }
      ]
    },
    {
      "key": "LAB05",
      "id": "6cbbfbeaa7b941c3af8063f4ca5969f8",
      "title": "LAB 05 · 同一次更新，多个数据分片",
      "url": "https://deepnote.com/workspace/ise3309jingao-5ba66b0a-4283-4f5a-ae06-3f68d3201e99/project/Fall-26-Lecture-06-2ff4b87b-2904-4b9c-b9e9-bdbd72962691/notebook/LAB-05-6cbbfbeaa7b941c3af8063f4ca5969f8?utm_source=openai&utm_medium=mcp&utm_campaign=openaimcp&utm_content=6cbbfbeaa7b941c3af8063f4ca5969f8&utm_term=get_notebook",
      "summary": "将同一次更新拆到多个数据分片，比较局部梯度、汇总与参数更新。",
      "sections": [
        {
          "key": "D1",
          "title": "D1 · 同初值、同八条样本，怎样合回一次更新？",
          "block_id": "018523536049452face3504fb4c32022"
        },
        {
          "key": "D2",
          "title": "D2 · 每片同样一条序列，分母为什么仍不相同？",
          "block_id": "c21fe00d75534e5382ec6df4f68927f6"
        },
        {
          "key": "D3",
          "title": "D3 · 候选一起进入分母时，还能只合并局部loss吗？",
          "block_id": "a9494ac7c3eb42238d88fcdd1495bbec"
        }
      ]
    },
    {
      "key": "LAB06",
      "id": "56ea4de667c74a84a7be00689c8de2d9",
      "title": "LAB 06 · 资源：预算、搬运与执行选择",
      "url": "https://deepnote.com/workspace/ise3309jingao-5ba66b0a-4283-4f5a-ae06-3f68d3201e99/project/Fall-26-Lecture-06-2ff4b87b-2904-4b9c-b9e9-bdbd72962691/notebook/LAB-06-56ea4de667c74a84a7be00689c8de2d9?utm_source=openai&utm_medium=mcp&utm_campaign=openaimcp&utm_content=56ea4de667c74a84a7be00689c8de2d9&utm_term=get_notebook",
      "summary": "从训练预算与内存状态走到注意力搬运、请求缓存和受约束选择。",
      "sections": [
        {
          "key": "R1",
          "title": "R1 · 固定计算预算，改变模型与训练量",
          "block_id": "596d044a097841e989ee1ddc5e52b551"
        },
        {
          "key": "R2",
          "title": "R2 · 16 GB 权重，为什么会有128 GB训练状态？",
          "block_id": "99a7a488a4a347d0bf8e5a36bb31c3ff"
        },
        {
          "key": "R3",
          "title": "R3 · 同一 Q/K/V，分块怎样保持同一个读出？",
          "block_id": "c443b475b8e246b781dada9fba82493f"
        },
        {
          "key": "R4",
          "title": "R4 · 共享权重，为什么八份上下文仍占八份空间？",
          "block_id": "f9b67b005ffd42c2bcf2edd475f01766"
        },
        {
          "key": "R5",
          "title": "R5 · 先列可行集，再作一次真正会翻转的选择",
          "block_id": "fbaa3d39251c4f6eb017472ab8dff76b"
        }
      ]
    }
  ],
  "page_mappings": [
    {
      "pages": [
        "AR01"
      ],
      "states": [
        "b0",
        "b1",
        "b2"
      ],
      "targets": [
        {
          "notebook": "LAB01",
          "section": "M1"
        }
      ],
      "summary": "固定查询、目标和记忆前缀，比较 M=1、16、64、256 的读回。这里是受控关联记忆计算。"
    },
    {
      "pages": [
        "RG24"
      ],
      "states": [
        "b0",
        "b1",
        "b2"
      ],
      "targets": [
        {
          "notebook": "LAB02",
          "section": "V4"
        }
      ],
      "summary": "在 V4 选择 EVIDENCE_CASE=\"RG24\"，先写预测，再揭示原研究的近失配证据；本活动不重新测量模型激活。"
    },
    {
      "pages": [
        "RC-P1"
      ],
      "states": [
        "b0",
        "b1",
        "b2"
      ],
      "targets": [
        {
          "notebook": "LAB03",
          "section": "T1"
        }
      ],
      "summary": "从同一 A/B 记录生成多组前缀与目标，区分教学切分和真实 tokenizer。"
    },
    {
      "pages": [
        "RC-P2"
      ],
      "states": [
        "b0",
        "b1",
        "b2",
        "b3"
      ],
      "targets": [
        {
          "notebook": "LAB03",
          "section": "T1"
        }
      ],
      "summary": "检查 input、target、causal mask 及 BOS/EOS 对齐，说明各位置怎样使用同一组参数。"
    },
    {
      "pages": [
        "RC-P3"
      ],
      "states": [
        "b0",
        "b1",
        "b2"
      ],
      "targets": [
        {
          "notebook": "LAB03",
          "section": "T2"
        }
      ],
      "summary": "核对一次真实轻量 RNN 更新前后的参数、loss 和目标概率；不把教学计分预设为实测结果。"
    },
    {
      "pages": [
        "RC-P4"
      ],
      "states": [
        "b0",
        "b1",
        "b2",
        "b3"
      ],
      "targets": [
        {
          "notebook": "LAB03",
          "section": "T3"
        },
        {
          "notebook": "LAB04",
          "section": "I2"
        }
      ],
      "summary": "比较成对输入与实际输出；把教师参考答案、轻量训练和独立诊断分别看待。"
    },
    {
      "pages": [
        "RC-P5"
      ],
      "states": [
        "b0",
        "b1",
        "b2"
      ],
      "targets": [
        {
          "notebook": "LAB03",
          "section": "T3"
        },
        {
          "notebook": "LAB06",
          "section": "R1"
        }
      ],
      "summary": "区分材料库存、不同 token 和实际训练消费量，检查固定预算下材料提出的依赖。"
    },
    {
      "pages": [
        "RC-P6"
      ],
      "states": [
        "b0",
        "b1",
        "b2",
        "b3"
      ],
      "targets": [
        {
          "notebook": "LAB03",
          "section": "T3"
        }
      ],
      "summary": "分别阅读 GPT-1 原表和课堂轻量模型结果，说明它们各自支持怎样的迁移判断。"
    },
    {
      "pages": [
        "RC-A1"
      ],
      "states": [
        "b0",
        "b1",
        "b2"
      ],
      "targets": [
        {
          "notebook": "LAB04",
          "section": "I1"
        },
        {
          "notebook": "LAB04",
          "section": "I2"
        }
      ],
      "summary": "核对固定 checkpoint、输入和已保存输出。24 条真实 pilot、独立 6 条诊断与 192 条合成 fixture 分开。"
    },
    {
      "pages": [
        "RC-A2"
      ],
      "states": [
        "b0",
        "b1",
        "b2"
      ],
      "targets": [
        {
          "notebook": "LAB01",
          "section": "M4"
        },
        {
          "notebook": "LAB04",
          "section": "I1"
        }
      ],
      "summary": "比较参数不变时的内容变化；将关联记忆构造与固定真实模型的记录分开。"
    },
    {
      "pages": [
        "RC-A3"
      ],
      "states": [
        "b0",
        "b1",
        "b2"
      ],
      "targets": [
        {
          "notebook": "LAB04",
          "section": "I3"
        }
      ],
      "summary": "重算已有记录，检查分母和对照条件；D−C 不能单独代表示例的因果效应。"
    },
    {
      "pages": [
        "RC-A4",
        "RC-A5"
      ],
      "states": [
        "b0",
        "b1",
        "b2",
        "b3"
      ],
      "targets": [
        {
          "notebook": "LAB03",
          "section": "T4"
        }
      ],
      "summary": "分别指出可读取的输入和计分位置：只给回应计分，不等于看不到用户输入。"
    },
    {
      "pages": [
        "RC-A6"
      ],
      "states": [
        "b0",
        "b1",
        "b2"
      ],
      "targets": [
        {
          "notebook": "LAB03",
          "section": "T4"
        },
        {
          "notebook": "LAB04",
          "section": "I2"
        },
        {
          "notebook": "LAB04",
          "section": "I3"
        }
      ],
      "summary": "区分修改权重与修改上下文，分别核对已有记录和能够支持的结论。"
    },
    {
      "pages": [
        "CL03"
      ],
      "states": [
        "b0"
      ],
      "targets": [
        {
          "notebook": "LAB06",
          "section": "R5"
        }
      ],
      "summary": "使用 R5 账本说明当前为何选 A，以及改变哪个约束会改变选择。"
    }
  ],
  "topic_mappings": {
    "memory-capacity": [
      [
        "LAB01",
        "M1"
      ],
      [
        "LAB01",
        "M4"
      ]
    ],
    "goodfire-internals": [
      [
        "LAB02",
        "V4"
      ]
    ],
    "pretraining": [
      [
        "LAB03",
        "T1"
      ],
      [
        "LAB03",
        "T2"
      ],
      [
        "LAB03",
        "T3"
      ],
      [
        "LAB06",
        "R1"
      ]
    ],
    "context-memory": [
      [
        "LAB01",
        "M4"
      ],
      [
        "LAB04",
        "I1"
      ],
      [
        "LAB04",
        "I2"
      ],
      [
        "LAB04",
        "I3"
      ]
    ],
    "posttraining": [
      [
        "LAB03",
        "T4"
      ]
    ],
    "serving": [
      [
        "LAB06",
        "R4"
      ],
      [
        "LAB06",
        "R5"
      ]
    ]
  }
}