{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2020:W3SABKWQUOR5HI3FX3PMZFZAUN","short_pith_number":"pith:W3SABKWQ","schema_version":"1.0","canonical_sha256":"b6e400aad0a3a3d3a365bedecc9720a352fad268eb0583c939e9fec01ddc2f82","source":{"kind":"arxiv","id":"2009.06489","version":2},"attestation_state":"computed","paper":{"title":"The Hardware Lottery","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.AR","cs.LG"],"primary_cat":"cs.CY","authors_text":"Sara Hooker","submitted_at":"2020-09-14T14:49:10Z","abstract_excerpt":"Hardware, systems and algorithms research communities have historically had different incentive structures and fluctuating motivation to engage with each other explicitly. This historical treatment is odd given that hardware and software have frequently determined which research ideas succeed (and fail). This essay introduces the term hardware lottery to describe when a research idea wins because it is suited to the available software and hardware and not because the idea is superior to alternative research directions. Examples from early computer science history illustrate how hardware lotter"},"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":"2009.06489","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CY","submitted_at":"2020-09-14T14:49:10Z","cross_cats_sorted":["cs.AI","cs.AR","cs.LG"],"title_canon_sha256":"415acfa4d521ca2672b1735c447ad0b3e9485cae85b892bae758f25f9f8689d8","abstract_canon_sha256":"f8e83bd5d2af0a25f44c0178e4756da4c748bf45d0861f64c735a89f9c43024c"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T01:37:15.543426Z","signature_b64":"VZE1CETkKg0jgUttrx8hq919i9aCQ9Pw+XjxnWjeX9oeR/SFA4o1wts5OhYMtBjuwn/ucRycxtgZg2FOJwQnCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b6e400aad0a3a3d3a365bedecc9720a352fad268eb0583c939e9fec01ddc2f82","last_reissued_at":"2026-07-05T01:37:15.542950Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T01:37:15.542950Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"The Hardware Lottery","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.AR","cs.LG"],"primary_cat":"cs.CY","authors_text":"Sara Hooker","submitted_at":"2020-09-14T14:49:10Z","abstract_excerpt":"Hardware, systems and algorithms research communities have historically had different incentive structures and fluctuating motivation to engage with each other explicitly. This historical treatment is odd given that hardware and software have frequently determined which research ideas succeed (and fail). This essay introduces the term hardware lottery to describe when a research idea wins because it is suited to the available software and hardware and not because the idea is superior to alternative research directions. Examples from early computer science history illustrate how hardware lotter"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2009.06489","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/2009.06489/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":"2009.06489","created_at":"2026-07-05T01:37:15.543012+00:00"},{"alias_kind":"arxiv_version","alias_value":"2009.06489v2","created_at":"2026-07-05T01:37:15.543012+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2009.06489","created_at":"2026-07-05T01:37:15.543012+00:00"},{"alias_kind":"pith_short_12","alias_value":"W3SABKWQUOR5","created_at":"2026-07-05T01:37:15.543012+00:00"},{"alias_kind":"pith_short_16","alias_value":"W3SABKWQUOR5HI3F","created_at":"2026-07-05T01:37:15.543012+00:00"},{"alias_kind":"pith_short_8","alias_value":"W3SABKWQ","created_at":"2026-07-05T01:37:15.543012+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":6,"internal_anchor_count":0,"sample":[{"citing_arxiv_id":"2506.08332","citing_title":"ORFS-agent: Tool-Using Agents for Chip Design Optimization","ref_index":17,"is_internal_anchor":false},{"citing_arxiv_id":"2602.01651","citing_title":"On the Spatiotemporal Dynamics of Generalization in Neural Networks","ref_index":31,"is_internal_anchor":false},{"citing_arxiv_id":"2101.03961","citing_title":"Switch Transformers: Scaling to Trillion Parameter Models with Simple and Efficient Sparsity","ref_index":15,"is_internal_anchor":false},{"citing_arxiv_id":"2202.08906","citing_title":"ST-MoE: Designing Stable and Transferable Sparse Expert Models","ref_index":52,"is_internal_anchor":false},{"citing_arxiv_id":"2205.14135","citing_title":"FlashAttention: Fast and Memory-Efficient Exact Attention with IO-Awareness","ref_index":41,"is_internal_anchor":false},{"citing_arxiv_id":"2604.07935","citing_title":"The Hyperscale Lottery: How State-Space Models Have Sacrificed Edge Efficiency","ref_index":8,"is_internal_anchor":false}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/W3SABKWQUOR5HI3FX3PMZFZAUN","json":"https://pith.science/pith/W3SABKWQUOR5HI3FX3PMZFZAUN.json","graph_json":"https://pith.science/api/pith-number/W3SABKWQUOR5HI3FX3PMZFZAUN/graph.json","events_json":"https://pith.science/api/pith-number/W3SABKWQUOR5HI3FX3PMZFZAUN/events.json","paper":"https://pith.science/paper/W3SABKWQ"},"agent_actions":{"view_html":"https://pith.science/pith/W3SABKWQUOR5HI3FX3PMZFZAUN","download_json":"https://pith.science/pith/W3SABKWQUOR5HI3FX3PMZFZAUN.json","view_paper":"https://pith.science/paper/W3SABKWQ","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2009.06489&json=true","fetch_graph":"https://pith.science/api/pith-number/W3SABKWQUOR5HI3FX3PMZFZAUN/graph.json","fetch_events":"https://pith.science/api/pith-number/W3SABKWQUOR5HI3FX3PMZFZAUN/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/W3SABKWQUOR5HI3FX3PMZFZAUN/action/timestamp_anchor","attest_storage":"https://pith.science/pith/W3SABKWQUOR5HI3FX3PMZFZAUN/action/storage_attestation","attest_author":"https://pith.science/pith/W3SABKWQUOR5HI3FX3PMZFZAUN/action/author_attestation","sign_citation":"https://pith.science/pith/W3SABKWQUOR5HI3FX3PMZFZAUN/action/citation_signature","submit_replication":"https://pith.science/pith/W3SABKWQUOR5HI3FX3PMZFZAUN/action/replication_record"}},"created_at":"2026-07-05T01:37:15.543012+00:00","updated_at":"2026-07-05T01:37:15.543012+00:00"}