{
  "schemaVersion": 1,
  "lessonId": "welcome-03",
  "contentHash": "c635ba5492b7276fae2ed1af1cbef264ceb432ae40c49d9b40291f8eb84821ac",
  "rendererHash": "a1bd5b648f4731ae5d5f0a24811c2540d1a0a132149ce589d17c4113509cbedf",
  "kind": "executed",
  "generatedAt": "2026-10-20T10:45:06.987466+00:00",
  "provenance": "recorded_cpu_computation",
  "environment": {
    "backend": "cpu",
    "deviceCount": 1,
    "jax": "0.9.2",
    "numpy": "2.4.4",
    "matplotlib": "3.10.8"
  },
  "stdout": "{\n  \"expected\": \"cpu\",\n  \"output_devices\": [\n    \"TFRT_CPU_0\"\n  ],\n  \"platform\": \"cpu\",\n  \"jax\": \"0.9.2\",\n  \"python\": \"3.14.3\",\n  \"shape\": [\n    8\n  ],\n  \"dtype\": \"float32\",\n  \"max_absolute_error\": 0.0,\n  \"process_index\": 0,\n  \"process_count\": 1\n}\nCompleted prediction: [0.34375, 0.8125, 1.28125, 1.75, 2.21875, 2.6875, 3.15625, 3.625]\n",
  "data": {
    "kind": "line",
    "x": [
      0,
      1,
      2,
      3,
      4,
      5,
      6,
      7
    ],
    "xlabel": "observation row",
    "ylabel": "prediction",
    "series": [
      {
        "label": "JAX: cpu",
        "y": [
          0.34375,
          0.8125,
          1.28125,
          1.75,
          2.21875,
          2.6875,
          3.15625,
          3.625
        ]
      },
      {
        "label": "NumPy reference",
        "y": [
          0.34375,
          0.8125,
          1.28125,
          1.75,
          2.21875,
          2.6875,
          3.15625,
          3.625
        ]
      }
    ]
  }
}