{"id":"W4388760782","doi":"10.17760/d20581919","title":"Towards efficient deep neural network inference and training for ubiquitous AI","year":2023,"lang":"en","type":"dissertation","venue":"","topic":"Advanced Memory and Neural Computing","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Computer science; Crossbar switch; Resistive random-access memory; Artificial intelligence; Deep learning; Scalability; Computer architecture; Computer engineering; Distributed computing; Machine learning; Engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000086047,0.000245979,0.0002756256,0.00005986029,0.000128023,0.00004438471,0.00009723233,0.000145499,0.000007288409],"category_scores_gemma":[0.0000618039,0.0002418885,0.00006584466,0.0001509632,0.000008874096,0.00004085421,0.000017838,0.0002876377,0.000003656856],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002031601,"about_ca_system_score_gemma":0.0000142924,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002132585,"about_ca_topic_score_gemma":0.00007807092,"domain_scores_codex":[0.9990395,0.000008076137,0.0002310126,0.0002478969,0.00009535782,0.0003782102],"domain_scores_gemma":[0.999547,0.0002051797,0.00003814409,0.0001013049,0.00003796715,0.00007042082],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001922945,0.000001643256,0.00000215896,0.0002825998,0.00001608324,0.000004883076,0.001031604,0.8379929,0.0005532712,0.0002356235,0.00008373709,0.1597763],"study_design_scores_gemma":[0.0002184715,0.00006242055,0.0005856121,0.000151414,0.00003486063,0.000004217096,0.0008073592,0.9941291,0.002478293,0.0008683471,0.0002481191,0.0004117904],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9119543,0.0008350248,0.07721305,0.00002341128,0.00494993,0.00065013,0.000008058531,0.001586144,0.002779931],"genre_scores_gemma":[0.9964379,0.00003793988,0.00183174,0.00006940014,0.0005664399,0.00005737359,0.0001904801,0.00009252673,0.000716171],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1593645,"threshold_uncertainty_score":0.9863927,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03333344622705265,"score_gpt":0.3057634321185062,"score_spread":0.2724299858914535,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}