{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2021:Q4WFWOYYUGJB7HMZKRFFJKF3GZ","short_pith_number":"pith:Q4WFWOYY","canonical_record":{"source":{"id":"2109.05472","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2021-09-12T09:40:18Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"b4b836c046bdd95ca74269a38dbf39aa1904f6511e1dd3e396adde6dc655c756","abstract_canon_sha256":"7df66bbf740885e908a4d2768755b168a4d679afe4bacc671cfc2090739b7499"},"schema_version":"1.0"},"canonical_sha256":"872c5b3b18a1921f9d99544a54a8bb3654a9513160d5ce6fc2dd8e601e19820c","source":{"kind":"arxiv","id":"2109.05472","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2109.05472","created_at":"2026-07-05T05:55:56Z"},{"alias_kind":"arxiv_version","alias_value":"2109.05472v2","created_at":"2026-07-05T05:55:56Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2109.05472","created_at":"2026-07-05T05:55:56Z"},{"alias_kind":"pith_short_12","alias_value":"Q4WFWOYYUGJB","created_at":"2026-07-05T05:55:56Z"},{"alias_kind":"pith_short_16","alias_value":"Q4WFWOYYUGJB7HMZ","created_at":"2026-07-05T05:55:56Z"},{"alias_kind":"pith_short_8","alias_value":"Q4WFWOYY","created_at":"2026-07-05T05:55:56Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2021:Q4WFWOYYUGJB7HMZKRFFJKF3GZ","target":"record","payload":{"canonical_record":{"source":{"id":"2109.05472","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2021-09-12T09:40:18Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"b4b836c046bdd95ca74269a38dbf39aa1904f6511e1dd3e396adde6dc655c756","abstract_canon_sha256":"7df66bbf740885e908a4d2768755b168a4d679afe4bacc671cfc2090739b7499"},"schema_version":"1.0"},"canonical_sha256":"872c5b3b18a1921f9d99544a54a8bb3654a9513160d5ce6fc2dd8e601e19820c","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:55:56.080004Z","signature_b64":"Ms8KC1QsUSaGNJrbqHiZH7G5/1+8TWkhNfl0GCc/YSzeUKJSw4JaV7EGj+LZ0Eb86uJyE95MG9qcbOlFeLSuBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"872c5b3b18a1921f9d99544a54a8bb3654a9513160d5ce6fc2dd8e601e19820c","last_reissued_at":"2026-07-05T05:55:56.079662Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:55:56.079662Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2109.05472","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T05:55:56Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"bbb/bN5tghu20RiEzFR78rYiX16BHNrhr5CqHyHHZVVTG8NBq8xBRQqAC5QNqexoDECYOU1nIxIxWP42thPABw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T15:42:15.717820Z"},"content_sha256":"547ee26fc2369185ebfa72201160ca8bebd32eac9baeacc37982c9e83c41c638","schema_version":"1.0","event_id":"sha256:547ee26fc2369185ebfa72201160ca8bebd32eac9baeacc37982c9e83c41c638"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2021:Q4WFWOYYUGJB7HMZKRFFJKF3GZ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Compute and Energy Consumption Trends in Deep Learning Inference","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.LG","authors_text":"Fernando Mart\\'inez-Plumed, Jos\\'e Hern\\'andez-Orallo, Radosvet Desislavov","submitted_at":"2021-09-12T09:40:18Z","abstract_excerpt":"The progress of some AI paradigms such as deep learning is said to be linked to an exponential growth in the number of parameters. There are many studies corroborating these trends, but does this translate into an exponential increase in energy consumption? In order to answer this question we focus on inference costs rather than training costs, as the former account for most of the computing effort, solely because of the multiplicative factors. Also, apart from algorithmic innovations, we account for more specific and powerful hardware (leading to higher FLOPS) that is usually accompanied with"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2109.05472","kind":"arxiv","version":2},"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/2109.05472/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":"2026-07-05T05:55:56Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"UyGDoSr7WNWyZzyo+jGqc8XK4ALCQ6/YW1u7nQ2apdSMch42UQ51b+/8MhdyQPHJGv1CBVjQzJeoVKcWQWd1Dw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T15:42:15.718289Z"},"content_sha256":"f070c2d0f3cfcfcba5a416d0fc3df4cdf3bc562c284683aa578cdca09747f10a","schema_version":"1.0","event_id":"sha256:f070c2d0f3cfcfcba5a416d0fc3df4cdf3bc562c284683aa578cdca09747f10a"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/Q4WFWOYYUGJB7HMZKRFFJKF3GZ/bundle.json","state_url":"https://pith.science/pith/Q4WFWOYYUGJB7HMZKRFFJKF3GZ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/Q4WFWOYYUGJB7HMZKRFFJKF3GZ/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":"2026-08-07T15:42:15Z","links":{"resolver":"https://pith.science/pith/Q4WFWOYYUGJB7HMZKRFFJKF3GZ","bundle":"https://pith.science/pith/Q4WFWOYYUGJB7HMZKRFFJKF3GZ/bundle.json","state":"https://pith.science/pith/Q4WFWOYYUGJB7HMZKRFFJKF3GZ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/Q4WFWOYYUGJB7HMZKRFFJKF3GZ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:Q4WFWOYYUGJB7HMZKRFFJKF3GZ","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":"7df66bbf740885e908a4d2768755b168a4d679afe4bacc671cfc2090739b7499","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2021-09-12T09:40:18Z","title_canon_sha256":"b4b836c046bdd95ca74269a38dbf39aa1904f6511e1dd3e396adde6dc655c756"},"schema_version":"1.0","source":{"id":"2109.05472","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2109.05472","created_at":"2026-07-05T05:55:56Z"},{"alias_kind":"arxiv_version","alias_value":"2109.05472v2","created_at":"2026-07-05T05:55:56Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2109.05472","created_at":"2026-07-05T05:55:56Z"},{"alias_kind":"pith_short_12","alias_value":"Q4WFWOYYUGJB","created_at":"2026-07-05T05:55:56Z"},{"alias_kind":"pith_short_16","alias_value":"Q4WFWOYYUGJB7HMZ","created_at":"2026-07-05T05:55:56Z"},{"alias_kind":"pith_short_8","alias_value":"Q4WFWOYY","created_at":"2026-07-05T05:55:56Z"}],"graph_snapshots":[{"event_id":"sha256:f070c2d0f3cfcfcba5a416d0fc3df4cdf3bc562c284683aa578cdca09747f10a","target":"graph","created_at":"2026-07-05T05:55:56Z","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/2109.05472/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The progress of some AI paradigms such as deep learning is said to be linked to an exponential growth in the number of parameters. There are many studies corroborating these trends, but does this translate into an exponential increase in energy consumption? In order to answer this question we focus on inference costs rather than training costs, as the former account for most of the computing effort, solely because of the multiplicative factors. Also, apart from algorithmic innovations, we account for more specific and powerful hardware (leading to higher FLOPS) that is usually accompanied with","authors_text":"Fernando Mart\\'inez-Plumed, Jos\\'e Hern\\'andez-Orallo, Radosvet Desislavov","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2021-09-12T09:40:18Z","title":"Compute and Energy Consumption Trends in Deep Learning Inference"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2109.05472","kind":"arxiv","version":2},"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":"sha256:547ee26fc2369185ebfa72201160ca8bebd32eac9baeacc37982c9e83c41c638","target":"record","created_at":"2026-07-05T05:55:56Z","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":"7df66bbf740885e908a4d2768755b168a4d679afe4bacc671cfc2090739b7499","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2021-09-12T09:40:18Z","title_canon_sha256":"b4b836c046bdd95ca74269a38dbf39aa1904f6511e1dd3e396adde6dc655c756"},"schema_version":"1.0","source":{"id":"2109.05472","kind":"arxiv","version":2}},"canonical_sha256":"872c5b3b18a1921f9d99544a54a8bb3654a9513160d5ce6fc2dd8e601e19820c","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"872c5b3b18a1921f9d99544a54a8bb3654a9513160d5ce6fc2dd8e601e19820c","first_computed_at":"2026-07-05T05:55:56.079662Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:55:56.079662Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Ms8KC1QsUSaGNJrbqHiZH7G5/1+8TWkhNfl0GCc/YSzeUKJSw4JaV7EGj+LZ0Eb86uJyE95MG9qcbOlFeLSuBg==","signature_status":"signed_v1","signed_at":"2026-07-05T05:55:56.080004Z","signed_message":"canonical_sha256_bytes"},"source_id":"2109.05472","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:547ee26fc2369185ebfa72201160ca8bebd32eac9baeacc37982c9e83c41c638","sha256:f070c2d0f3cfcfcba5a416d0fc3df4cdf3bc562c284683aa578cdca09747f10a"],"state_sha256":"669cbfa488d4ec4a109fdf815c88495231c10ddf3df4357afa51b10c603e933b"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"tC1DTQBFJIJKGdTGmDQjpCDgPpGPu+9zbgBDYSCRxVOeUYAYxUr9iCRxNu4o8dyF/JdTZZ1NIlREERazJ/OvAA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-07T15:42:15.722335Z","bundle_sha256":"8216a8f90ccbb963466a2077ef83a62df8d196d401e70f75aa70ec55170db0b0"}}