{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2024:I2MAJTGIPZ2K2Y6HYF6A5Z5MHO","short_pith_number":"pith:I2MAJTGI","schema_version":"1.0","canonical_sha256":"469804ccc87e74ad63c7c17c0ee7ac3b819d1ddbc0d74618fbe65a7a15142636","source":{"kind":"arxiv","id":"2405.13231","version":1},"attestation_state":"computed","paper":{"title":"Multiple Realizability and the Rise of Deep Learning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.AI","authors_text":"Jacob Russin, Sam Whitman McGrath","submitted_at":"2024-05-21T22:36:49Z","abstract_excerpt":"The multiple realizability thesis holds that psychological states may be implemented in a diversity of physical systems. The deep learning revolution seems to be bringing this possibility to life, offering the most plausible examples of man-made realizations of sophisticated cognitive functions to date. This paper explores the implications of deep learning models for the multiple realizability thesis. Among other things, it challenges the widely held view that multiple realizability entails that the study of the mind can and must be pursued independently of the study of its implementation in t"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2405.13231","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2024-05-21T22:36:49Z","cross_cats_sorted":[],"title_canon_sha256":"68de6cd81ca53cff259d7d0582c3de996f913d03feb27ef4ff0ca94fbb933861","abstract_canon_sha256":"7fc024493aa2ff57d2c3e300c3d86f051d5cd0a0221f326b62fbf78837e9f673"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:22:00.164444Z","signature_b64":"X737tYDbtVvHSETzDnL6toWqzyrWM9ooq/bsoMKIvm38RjJ765i/e9QiOsH/tmIEl1vryrJLRbtEA9tlZ2I7Bg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"469804ccc87e74ad63c7c17c0ee7ac3b819d1ddbc0d74618fbe65a7a15142636","last_reissued_at":"2026-07-05T08:22:00.164040Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:22:00.164040Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Multiple Realizability and the Rise of Deep Learning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.AI","authors_text":"Jacob Russin, Sam Whitman McGrath","submitted_at":"2024-05-21T22:36:49Z","abstract_excerpt":"The multiple realizability thesis holds that psychological states may be implemented in a diversity of physical systems. The deep learning revolution seems to be bringing this possibility to life, offering the most plausible examples of man-made realizations of sophisticated cognitive functions to date. This paper explores the implications of deep learning models for the multiple realizability thesis. Among other things, it challenges the widely held view that multiple realizability entails that the study of the mind can and must be pursued independently of the study of its implementation in t"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2405.13231","kind":"arxiv","version":1},"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/2405.13231/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2405.13231","created_at":"2026-07-05T08:22:00.164101+00:00"},{"alias_kind":"arxiv_version","alias_value":"2405.13231v1","created_at":"2026-07-05T08:22:00.164101+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2405.13231","created_at":"2026-07-05T08:22:00.164101+00:00"},{"alias_kind":"pith_short_12","alias_value":"I2MAJTGIPZ2K","created_at":"2026-07-05T08:22:00.164101+00:00"},{"alias_kind":"pith_short_16","alias_value":"I2MAJTGIPZ2K2Y6H","created_at":"2026-07-05T08:22:00.164101+00:00"},{"alias_kind":"pith_short_8","alias_value":"I2MAJTGI","created_at":"2026-07-05T08:22:00.164101+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/I2MAJTGIPZ2K2Y6HYF6A5Z5MHO","json":"https://pith.science/pith/I2MAJTGIPZ2K2Y6HYF6A5Z5MHO.json","graph_json":"https://pith.science/api/pith-number/I2MAJTGIPZ2K2Y6HYF6A5Z5MHO/graph.json","events_json":"https://pith.science/api/pith-number/I2MAJTGIPZ2K2Y6HYF6A5Z5MHO/events.json","paper":"https://pith.science/paper/I2MAJTGI"},"agent_actions":{"view_html":"https://pith.science/pith/I2MAJTGIPZ2K2Y6HYF6A5Z5MHO","download_json":"https://pith.science/pith/I2MAJTGIPZ2K2Y6HYF6A5Z5MHO.json","view_paper":"https://pith.science/paper/I2MAJTGI","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2405.13231&json=true","fetch_graph":"https://pith.science/api/pith-number/I2MAJTGIPZ2K2Y6HYF6A5Z5MHO/graph.json","fetch_events":"https://pith.science/api/pith-number/I2MAJTGIPZ2K2Y6HYF6A5Z5MHO/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/I2MAJTGIPZ2K2Y6HYF6A5Z5MHO/action/timestamp_anchor","attest_storage":"https://pith.science/pith/I2MAJTGIPZ2K2Y6HYF6A5Z5MHO/action/storage_attestation","attest_author":"https://pith.science/pith/I2MAJTGIPZ2K2Y6HYF6A5Z5MHO/action/author_attestation","sign_citation":"https://pith.science/pith/I2MAJTGIPZ2K2Y6HYF6A5Z5MHO/action/citation_signature","submit_replication":"https://pith.science/pith/I2MAJTGIPZ2K2Y6HYF6A5Z5MHO/action/replication_record"}},"created_at":"2026-07-05T08:22:00.164101+00:00","updated_at":"2026-07-05T08:22:00.164101+00:00"}