{"id":"W3128806918","doi":"10.36227/techrxiv.11925225.v1","title":"Photonic perceptron based on a Kerr microcomb for high-speed, scalable, optical neural networks","year":2020,"lang":"en","type":"article","venue":"","topic":"Neural Networks and Reservoir Computing","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"","keywords":"Computer science; Neuromorphic engineering; Scalability; Throughput; Benchmark (surveying); Artificial neural network; Multilayer perceptron; Matrix multiplication; Computer hardware; Photonics; Electronic engineering; Artificial intelligence; Optoelectronics; Physics; Engineering; Telecommunications; Quantum","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000249353,0.0002035446,0.0002101216,0.0002126411,0.0002297235,0.0004377536,0.0005917191,0.0004226859,0.001987958],"category_scores_gemma":[0.0005979354,0.0001668877,0.0001421229,0.0002180413,0.0004202582,0.0008859155,0.0003715161,0.0007137643,0.0003555447],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005051192,"about_ca_system_score_gemma":0.0003487234,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006012958,"about_ca_topic_score_gemma":0.001619707,"domain_scores_codex":[0.9998707,0.00002250263,0.000006175837,0.00002385767,0.0000608207,0.00001599712],"domain_scores_gemma":[0.9998453,0.00006131979,0.00002112313,0.00002511975,0.00003686361,0.000010288],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0004162842,0.0003648503,0.001590288,0.000398208,0.00009104931,0.0002976794,0.0001637168,0.09685206,0.6068699,0.1241568,0.008060355,0.1607387],"study_design_scores_gemma":[0.00003622051,0.0002489365,0.0007314299,0.00002500065,0.00002194169,0.0001463496,0.00001839693,0.8220894,0.1491384,0.01395343,0.01356039,0.00003017682],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3016042,0.001887465,0.6634988,0.002000595,0.0006502043,0.0001668168,0.0002091567,0.002667859,0.02731502],"genre_scores_gemma":[0.7791336,0.0004485472,0.2122056,0.0003351569,0.00006190804,0.0001132216,0.00008760458,0.00006965801,0.007544645],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001987958,"threshold_uncertainty_score":0.006650388,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01839200046634923,"score_gpt":0.2324929567701852,"score_spread":0.2141009563038359,"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."}}