{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:TSAWD2CTZ7AF5RNRCL7F3CRNFP","short_pith_number":"pith:TSAWD2CT","schema_version":"1.0","canonical_sha256":"9c8161e853cfc05ec5b112fe5d8a2d2bd2945942f1f5d80e2a2d930a5f054ab6","source":{"kind":"arxiv","id":"2606.28126","version":1},"attestation_state":"computed","paper":{"title":"AI-Driven Synthesis for High-Tech System Design: Automating Innovation","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":["cs.AR","cs.CE","cs.ET","cs.RO"],"primary_cat":"cs.AI","authors_text":"Luuk Oerlemans, Steven Westerhof, Theo Hofman","submitted_at":"2026-06-26T14:26:48Z","abstract_excerpt":"This article addresses the combinatorial complexity inherent in modern high-tech system design by presenting automation-in-design (AiD) as a transformative paradigm. We propose computational design synthesis (CDS), a framework utilising deep learning and generative AI to automate the creation of novel systems. Two case studies (e-drive system design and spatial dimensioning problem) serve as proof-points for this approach. The AI-driven methods used in the case studies represent a fundamental shift in engineering, advancing from simulation-based optimisation towards autonomous design with mini"},"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":"2606.28126","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.AI","submitted_at":"2026-06-26T14:26:48Z","cross_cats_sorted":["cs.AR","cs.CE","cs.ET","cs.RO"],"title_canon_sha256":"791b265a5fedc85ece032a3e7dd5aa9fa39269bf5399cf75f152114aee59335a","abstract_canon_sha256":"cd07550f11aeb04b0ceb5014d43eaaea048bd2a4666b3dc7c196e4c8edd67d0d"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-29T01:15:06.767635Z","signature_b64":"Cs9EFDhD4hAzamGORMr3s45go8Xlv8Gxuk8oJl3nAQu8UL63TI37W30ok83twxoPifXz7LEo5R3VyofV9lZqDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"9c8161e853cfc05ec5b112fe5d8a2d2bd2945942f1f5d80e2a2d930a5f054ab6","last_reissued_at":"2026-06-29T01:15:06.767228Z","signature_status":"signed_v1","first_computed_at":"2026-06-29T01:15:06.767228Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"AI-Driven Synthesis for High-Tech System Design: Automating Innovation","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":["cs.AR","cs.CE","cs.ET","cs.RO"],"primary_cat":"cs.AI","authors_text":"Luuk Oerlemans, Steven Westerhof, Theo Hofman","submitted_at":"2026-06-26T14:26:48Z","abstract_excerpt":"This article addresses the combinatorial complexity inherent in modern high-tech system design by presenting automation-in-design (AiD) as a transformative paradigm. We propose computational design synthesis (CDS), a framework utilising deep learning and generative AI to automate the creation of novel systems. Two case studies (e-drive system design and spatial dimensioning problem) serve as proof-points for this approach. The AI-driven methods used in the case studies represent a fundamental shift in engineering, advancing from simulation-based optimisation towards autonomous design with mini"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.28126","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/2606.28126/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":"2606.28126","created_at":"2026-06-29T01:15:06.767285+00:00"},{"alias_kind":"arxiv_version","alias_value":"2606.28126v1","created_at":"2026-06-29T01:15:06.767285+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.28126","created_at":"2026-06-29T01:15:06.767285+00:00"},{"alias_kind":"pith_short_12","alias_value":"TSAWD2CTZ7AF","created_at":"2026-06-29T01:15:06.767285+00:00"},{"alias_kind":"pith_short_16","alias_value":"TSAWD2CTZ7AF5RNR","created_at":"2026-06-29T01:15:06.767285+00:00"},{"alias_kind":"pith_short_8","alias_value":"TSAWD2CT","created_at":"2026-06-29T01:15:06.767285+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/TSAWD2CTZ7AF5RNRCL7F3CRNFP","json":"https://pith.science/pith/TSAWD2CTZ7AF5RNRCL7F3CRNFP.json","graph_json":"https://pith.science/api/pith-number/TSAWD2CTZ7AF5RNRCL7F3CRNFP/graph.json","events_json":"https://pith.science/api/pith-number/TSAWD2CTZ7AF5RNRCL7F3CRNFP/events.json","paper":"https://pith.science/paper/TSAWD2CT"},"agent_actions":{"view_html":"https://pith.science/pith/TSAWD2CTZ7AF5RNRCL7F3CRNFP","download_json":"https://pith.science/pith/TSAWD2CTZ7AF5RNRCL7F3CRNFP.json","view_paper":"https://pith.science/paper/TSAWD2CT","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2606.28126&json=true","fetch_graph":"https://pith.science/api/pith-number/TSAWD2CTZ7AF5RNRCL7F3CRNFP/graph.json","fetch_events":"https://pith.science/api/pith-number/TSAWD2CTZ7AF5RNRCL7F3CRNFP/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/TSAWD2CTZ7AF5RNRCL7F3CRNFP/action/timestamp_anchor","attest_storage":"https://pith.science/pith/TSAWD2CTZ7AF5RNRCL7F3CRNFP/action/storage_attestation","attest_author":"https://pith.science/pith/TSAWD2CTZ7AF5RNRCL7F3CRNFP/action/author_attestation","sign_citation":"https://pith.science/pith/TSAWD2CTZ7AF5RNRCL7F3CRNFP/action/citation_signature","submit_replication":"https://pith.science/pith/TSAWD2CTZ7AF5RNRCL7F3CRNFP/action/replication_record"}},"created_at":"2026-06-29T01:15:06.767285+00:00","updated_at":"2026-06-29T01:15:06.767285+00:00"}