{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:7MMDULLUGAW3ZX2LUHRBKQKB7Z","short_pith_number":"pith:7MMDULLU","canonical_record":{"source":{"id":"2311.16863","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2023-11-28T15:09:36Z","cross_cats_sorted":[],"title_canon_sha256":"2169d0f46acf07212fec10aef48061c0ddacd8dcb5a1778cc374a3df7c0c6f12","abstract_canon_sha256":"080b8be79f12cad7bb9b665fee137c5910efe2abb21004f45ed9eabadd15c7f8"},"schema_version":"1.0"},"canonical_sha256":"fb183a2d74302dbcdf4ba1e2154141fe79336cbaec445976ef114d9590eb4ad5","source":{"kind":"arxiv","id":"2311.16863","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2311.16863","created_at":"2026-07-05T09:21:01Z"},{"alias_kind":"arxiv_version","alias_value":"2311.16863v3","created_at":"2026-07-05T09:21:01Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2311.16863","created_at":"2026-07-05T09:21:01Z"},{"alias_kind":"pith_short_12","alias_value":"7MMDULLUGAW3","created_at":"2026-07-05T09:21:01Z"},{"alias_kind":"pith_short_16","alias_value":"7MMDULLUGAW3ZX2L","created_at":"2026-07-05T09:21:01Z"},{"alias_kind":"pith_short_8","alias_value":"7MMDULLU","created_at":"2026-07-05T09:21:01Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:7MMDULLUGAW3ZX2LUHRBKQKB7Z","target":"record","payload":{"canonical_record":{"source":{"id":"2311.16863","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2023-11-28T15:09:36Z","cross_cats_sorted":[],"title_canon_sha256":"2169d0f46acf07212fec10aef48061c0ddacd8dcb5a1778cc374a3df7c0c6f12","abstract_canon_sha256":"080b8be79f12cad7bb9b665fee137c5910efe2abb21004f45ed9eabadd15c7f8"},"schema_version":"1.0"},"canonical_sha256":"fb183a2d74302dbcdf4ba1e2154141fe79336cbaec445976ef114d9590eb4ad5","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:21:01.601629Z","signature_b64":"7DilPDYoywCkHEfzAcbtuFk3O4k112Mp0nF/VR+0aF+3dgpjtzFz9nnmlZX4eQFXFhNBXVNPsIGYQsxXRhfBBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"fb183a2d74302dbcdf4ba1e2154141fe79336cbaec445976ef114d9590eb4ad5","last_reissued_at":"2026-07-05T09:21:01.601043Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:21:01.601043Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2311.16863","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T09:21:01Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"liCPOtK75+umudOKEoklagyZeSEGcWwOP9qVuxDHsKvf2preUqx+Tg7fiPyCXYVBKjzZYj3xBBlGqb98POlqAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T17:13:57.219973Z"},"content_sha256":"8498a46799551cac3437e69e564c72b21f06dbbeba67f3f02dc60b9308add04a","schema_version":"1.0","event_id":"sha256:8498a46799551cac3437e69e564c72b21f06dbbeba67f3f02dc60b9308add04a"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:7MMDULLUGAW3ZX2LUHRBKQKB7Z","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Power Hungry Processing: Watts Driving the Cost of AI Deployment?","license":"http://creativecommons.org/licenses/by-sa/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Alexandra Sasha Luccioni, Emma Strubell, Yacine Jernite","submitted_at":"2023-11-28T15:09:36Z","abstract_excerpt":"Recent years have seen a surge in the popularity of commercial AI products based on generative, multi-purpose AI systems promising a unified approach to building machine learning (ML) models into technology. However, this ambition of ``generality'' comes at a steep cost to the environment, given the amount of energy these systems require and the amount of carbon that they emit. In this work, we propose the first systematic comparison of the ongoing inference cost of various categories of ML systems, covering both task-specific (i.e. finetuned models that carry out a single task) and `general-p"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2311.16863","kind":"arxiv","version":3},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2311.16863/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T09:21:01Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"dbHqt/Mm8YT/2+xNxkEE9zrBmV5FeFZ+NFZCZIlbDIiXibt7Psf6L/jiCtKmWSORLaON8D22zBA/183HoxT1AQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T17:13:57.220943Z"},"content_sha256":"b3710d7ac31ddfd1e5607a0111ac0f89233e55ca63db85f7be4d3707840add07","schema_version":"1.0","event_id":"sha256:b3710d7ac31ddfd1e5607a0111ac0f89233e55ca63db85f7be4d3707840add07"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/7MMDULLUGAW3ZX2LUHRBKQKB7Z/bundle.json","state_url":"https://pith.science/pith/7MMDULLUGAW3ZX2LUHRBKQKB7Z/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/7MMDULLUGAW3ZX2LUHRBKQKB7Z/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-09T17:13:57Z","links":{"resolver":"https://pith.science/pith/7MMDULLUGAW3ZX2LUHRBKQKB7Z","bundle":"https://pith.science/pith/7MMDULLUGAW3ZX2LUHRBKQKB7Z/bundle.json","state":"https://pith.science/pith/7MMDULLUGAW3ZX2LUHRBKQKB7Z/state.json","well_known_bundle":"https://pith.science/.well-known/pith/7MMDULLUGAW3ZX2LUHRBKQKB7Z/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:7MMDULLUGAW3ZX2LUHRBKQKB7Z","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"080b8be79f12cad7bb9b665fee137c5910efe2abb21004f45ed9eabadd15c7f8","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2023-11-28T15:09:36Z","title_canon_sha256":"2169d0f46acf07212fec10aef48061c0ddacd8dcb5a1778cc374a3df7c0c6f12"},"schema_version":"1.0","source":{"id":"2311.16863","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2311.16863","created_at":"2026-07-05T09:21:01Z"},{"alias_kind":"arxiv_version","alias_value":"2311.16863v3","created_at":"2026-07-05T09:21:01Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2311.16863","created_at":"2026-07-05T09:21:01Z"},{"alias_kind":"pith_short_12","alias_value":"7MMDULLUGAW3","created_at":"2026-07-05T09:21:01Z"},{"alias_kind":"pith_short_16","alias_value":"7MMDULLUGAW3ZX2L","created_at":"2026-07-05T09:21:01Z"},{"alias_kind":"pith_short_8","alias_value":"7MMDULLU","created_at":"2026-07-05T09:21:01Z"}],"graph_snapshots":[{"event_id":"sha256:b3710d7ac31ddfd1e5607a0111ac0f89233e55ca63db85f7be4d3707840add07","target":"graph","created_at":"2026-07-05T09:21:01Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2311.16863/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Recent years have seen a surge in the popularity of commercial AI products based on generative, multi-purpose AI systems promising a unified approach to building machine learning (ML) models into technology. However, this ambition of ``generality'' comes at a steep cost to the environment, given the amount of energy these systems require and the amount of carbon that they emit. In this work, we propose the first systematic comparison of the ongoing inference cost of various categories of ML systems, covering both task-specific (i.e. finetuned models that carry out a single task) and `general-p","authors_text":"Alexandra Sasha Luccioni, Emma Strubell, Yacine Jernite","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2023-11-28T15:09:36Z","title":"Power Hungry Processing: Watts Driving the Cost of AI Deployment?"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2311.16863","kind":"arxiv","version":3},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:8498a46799551cac3437e69e564c72b21f06dbbeba67f3f02dc60b9308add04a","target":"record","created_at":"2026-07-05T09:21:01Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"080b8be79f12cad7bb9b665fee137c5910efe2abb21004f45ed9eabadd15c7f8","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2023-11-28T15:09:36Z","title_canon_sha256":"2169d0f46acf07212fec10aef48061c0ddacd8dcb5a1778cc374a3df7c0c6f12"},"schema_version":"1.0","source":{"id":"2311.16863","kind":"arxiv","version":3}},"canonical_sha256":"fb183a2d74302dbcdf4ba1e2154141fe79336cbaec445976ef114d9590eb4ad5","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"fb183a2d74302dbcdf4ba1e2154141fe79336cbaec445976ef114d9590eb4ad5","first_computed_at":"2026-07-05T09:21:01.601043Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:21:01.601043Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"7DilPDYoywCkHEfzAcbtuFk3O4k112Mp0nF/VR+0aF+3dgpjtzFz9nnmlZX4eQFXFhNBXVNPsIGYQsxXRhfBBw==","signature_status":"signed_v1","signed_at":"2026-07-05T09:21:01.601629Z","signed_message":"canonical_sha256_bytes"},"source_id":"2311.16863","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:8498a46799551cac3437e69e564c72b21f06dbbeba67f3f02dc60b9308add04a","sha256:b3710d7ac31ddfd1e5607a0111ac0f89233e55ca63db85f7be4d3707840add07"],"state_sha256":"abed3218cb48ef91f1895cb5e9eee16abb554d3af4a13b867d96d08b294da978"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"WG1Tp8EiVAaDi6CBkhPLHnz27fG1FvE12y2mDqf+ayUenxJWLZGMG1VgoLLavCOxhuUDxGRAcvw583Vt7j3pCQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-09T17:13:57.227599Z","bundle_sha256":"d7ab15fd95b21c78a2db2519eccbbb455a423ddf749463fa5f76ca3ff34d0ff3"}}