# ALTER hardware data Two independently selectable data bundles are included: | Bundle | Files | Bytes | Contents | | --- | ---: | ---: | --- | | hardware-demonstrations-data | 501 | 48,137,006,286 | Selected base demonstrations, paired demonstrations, and distilled replay | | hardware-training-data | 412 | 20,798,158,144 | Original `images.npy` / `trajectory.npz` for 206 prepared records | The model/metadata bundle provides the portable manifests and catalogs. There are 332 base-training and 32 base-validation records; the high-data adaptation set contains 69 paired demonstrations and 68 replay records. The low-data set uses 30 pairs and 30 replay records from the same cache pool. Shared data are stored once. Cardboard replay recordings were policy-generated, not human demonstrations. High-data sampling has 93,164 two-arm anchors and 44,224 replay anchors; low-data sampling has 37,319 and 19,921. Original timestamps, indices, phase labels, weights, action values, image bytes, normalization metadata, grouping and ordering are preserved. Cartesian xyz uses millimeters; rotations use radians; action rows are `[x, y, z, roll, pitch, yaw, gripper]`. These are recovered prepared inputs, not a complete raw hardware backup. Some original raw recordings and scored physical-trial evidence are absent. Some prepared records use retained-row ordinal time rather than physical timestamps; their original per-record provenance documents this. The current-frame training protocol is preserved rather than reinterpreted as a temporal dataset. Original data/cache bytes are unchanged; export receipts and checksum manifests record their identities. Path-bearing metadata is sanitized in independent copies. Representative inspection of 59 frames showed robot workspaces and task objects, with no obvious faces or private text in those samples. This was a representative review, not an exhaustive inspection of every frame. Published as hardware v1. See [USAGE.md](USAGE.md) and [release-manifest.json](release-manifest.json) for downloads pinned to immutable artifact revisions. Existing repository license files are unchanged by this addition. The simulation artifacts remain unchanged. Authors: Dayi Dong, Maulik Bhatt, Aayushi Shrivastava, Lasse Peters, Negar Mehr.