Alan S. Chen

Array ( [id] => 19205128 [patent_doc_number] => 20240177027 [patent_country] => US [patent_kind] => A1 [patent_issue_date] => 2024-05-30 [patent_title] => SYSTEM AND METHOD FOR MANAGING INFERENCE MODEL PERFORMANCE THROUGH PROACTIVE COMMUNICATION SYSTEM ANALYSIS [patent_app_type] => utility [patent_app_number] => 18/060122 [patent_app_country] => US [patent_app_date] => 2022-11-30 [patent_effective_date] => 0000-00-00 [patent_drawing_sheets_cnt] => 0 [patent_figures_cnt] => 0 [patent_no_of_words] => 11539 [patent_no_of_claims] => 0 [patent_no_of_ind_claims] => -17 [patent_words_short_claim] => 114 [patent_maintenance] => 1 [patent_no_of_assignments] => 0 [patent_current_assignee] =>[type] => publication [pdf_file] =>[firstpage_image] =>[orig_patent_app_number] => 18060122 [rel_patent_id] =>[rel_patent_doc_number] =>)

Array ( [id] => 18286953 [patent_doc_number] => 20230102425 [patent_country] => US [patent_kind] => A1 [patent_issue_date] => 2023-03-30 [patent_title] => SYSTEMS AND METHODS FOR CREATING AND SELECTING MODELS FOR PREDICTING MEDICAL CONDITIONS [patent_app_type] => utility [patent_app_number] => 18/057824 [patent_app_country] => US [patent_app_date] => 2022-11-22 [patent_effective_date] => 0000-00-00 [patent_drawing_sheets_cnt] => 0 [patent_figures_cnt] => 0 [patent_no_of_words] => 8176 [patent_no_of_claims] => 0 [patent_no_of_ind_claims] => -17 [patent_words_short_claim] => 2 [patent_maintenance] => 1 [patent_no_of_assignments] => 0 [patent_current_assignee] =>[type] => publication [pdf_file] =>[firstpage_image] =>[orig_patent_app_number] => 18057824 [rel_patent_id] =>[rel_patent_doc_number] =>)

Array ( [id] => 18438819 [patent_doc_number] => 20230186114 [patent_country] => US [patent_kind] => A1 [patent_issue_date] => 2023-06-15 [patent_title] => METHODS FOR AUTOMATED THERAPY AND BIOACTIVE DISCOVERY AND FOR AUTOMATED THERAPY AND BIOACTIVE DELIVERY [patent_app_type] => utility [patent_app_number] => 17/987535 [patent_app_country] => US [patent_app_date] => 2022-11-15 [patent_effective_date] => 0000-00-00 [patent_drawing_sheets_cnt] => 0 [patent_figures_cnt] => 0 [patent_no_of_words] => 14564 [patent_no_of_claims] => 0 [patent_no_of_ind_claims] => -17 [patent_words_short_claim] => 243 [patent_maintenance] => 1 [patent_no_of_assignments] => 0 [patent_current_assignee] =>[type] => publication [pdf_file] =>[firstpage_image] =>[orig_patent_app_number] => 17987535 [rel_patent_id] =>[rel_patent_doc_number] =>)

Array ( [id] => 18438819 [patent_doc_number] => 20230186114 [patent_country] => US [patent_kind] => A1 [patent_issue_date] => 2023-06-15 [patent_title] => METHODS FOR AUTOMATED THERAPY AND BIOACTIVE DISCOVERY AND FOR AUTOMATED THERAPY AND BIOACTIVE DELIVERY [patent_app_type] => utility [patent_app_number] => 17/987535 [patent_app_country] => US [patent_app_date] => 2022-11-15 [patent_effective_date] => 0000-00-00 [patent_drawing_sheets_cnt] => 0 [patent_figures_cnt] => 0 [patent_no_of_words] => 14564 [patent_no_of_claims] => 0 [patent_no_of_ind_claims] => -17 [patent_words_short_claim] => 243 [patent_maintenance] => 1 [patent_no_of_assignments] => 0 [patent_current_assignee] =>[type] => publication [pdf_file] =>[firstpage_image] =>[orig_patent_app_number] => 17987535 [rel_patent_id] =>[rel_patent_doc_number] =>)

Array ( [id] => 18378612 [patent_doc_number] => 20230153700 [patent_country] => US [patent_kind] => A1 [patent_issue_date] => 2023-05-18 [patent_title] => Efficient Training of Embedding Models Using Negative Cache [patent_app_type] => utility [patent_app_number] => 17/983130 [patent_app_country] => US [patent_app_date] => 2022-11-08 [patent_effective_date] => 0000-00-00 [patent_drawing_sheets_cnt] => 0 [patent_figures_cnt] => 0 [patent_no_of_words] => 10186 [patent_no_of_claims] => 0 [patent_no_of_ind_claims] => -17 [patent_words_short_claim] => 258 [patent_maintenance] => 1 [patent_no_of_assignments] => 0 [patent_current_assignee] =>[type] => publication [pdf_file] =>[firstpage_image] =>[orig_patent_app_number] => 17983130 [rel_patent_id] =>[rel_patent_doc_number] =>)

Array ( [id] => 18348828 [patent_doc_number] => 20230136939 [patent_country] => US [patent_kind] => A1 [patent_issue_date] => 2023-05-04 [patent_title] => USER EXPERIENCE MODELING SYSTEM [patent_app_type] => utility [patent_app_number] => 17/979566 [patent_app_country] => US [patent_app_date] => 2022-11-02 [patent_effective_date] => 0000-00-00 [patent_drawing_sheets_cnt] => 0 [patent_figures_cnt] => 0 [patent_no_of_words] => 14404 [patent_no_of_claims] => 0 [patent_no_of_ind_claims] => -17 [patent_words_short_claim] => 206 [patent_maintenance] => 1 [patent_no_of_assignments] => 0 [patent_current_assignee] =>[type] => publication [pdf_file] =>[firstpage_image] =>[orig_patent_app_number] => 17979566 [rel_patent_id] =>[rel_patent_doc_number] =>)

Array ( [id] => 18124530 [patent_doc_number] => 20230010142 [patent_country] => US [patent_kind] => A1 [patent_issue_date] => 2023-01-12 [patent_title] => Generating Pretrained Sparse Student Model for Transfer Learning [patent_app_type] => utility [patent_app_number] => 17/934276 [patent_app_country] => US [patent_app_date] => 2022-09-22 [patent_effective_date] => 0000-00-00 [patent_drawing_sheets_cnt] => 0 [patent_figures_cnt] => 0 [patent_no_of_words] => 16311 [patent_no_of_claims] => 0 [patent_no_of_ind_claims] => -22 [patent_words_short_claim] => 119 [patent_maintenance] => 1 [patent_no_of_assignments] => 0 [patent_current_assignee] =>[type] => publication [pdf_file] =>[firstpage_image] =>[orig_patent_app_number] => 17934276 [rel_patent_id] =>[rel_patent_doc_number] =>)

Array ( [id] => 18111933 [patent_doc_number] => 20230004813 [patent_country] => US [patent_kind] => A1 [patent_issue_date] => 2023-01-05 [patent_title] => JOINTLY PRUNING AND QUANTIZING DEEP NEURAL NETWORKS [patent_app_type] => utility [patent_app_number] => 17/943176 [patent_app_country] => US [patent_app_date] => 2022-09-12 [patent_effective_date] => 0000-00-00 [patent_drawing_sheets_cnt] => 0 [patent_figures_cnt] => 0 [patent_no_of_words] => 6034 [patent_no_of_claims] => 0 [patent_no_of_ind_claims] => -17 [patent_words_short_claim] => 60 [patent_maintenance] => 1 [patent_no_of_assignments] => 0 [patent_current_assignee] =>[type] => publication [pdf_file] =>[firstpage_image] =>[orig_patent_app_number] => 17943176 [rel_patent_id] =>[rel_patent_doc_number] =>)

Array ( [id] => 18338029 [patent_doc_number] => 20230129978 [patent_country] => US [patent_kind] => A1 [patent_issue_date] => 2023-04-27 [patent_title] => METHOD FOR CAUSAL INFERENCE BASED ON COLLECTIVE MOVEMENTS OF ACTIVE GROUP [patent_app_type] => utility [patent_app_number] => 17/888547 [patent_app_country] => US [patent_app_date] => 2022-08-16 [patent_effective_date] => 0000-00-00 [patent_drawing_sheets_cnt] => 0 [patent_figures_cnt] => 0 [patent_no_of_words] => 4641 [patent_no_of_claims] => 0 [patent_no_of_ind_claims] => -8 [patent_words_short_claim] => 195 [patent_maintenance] => 1 [patent_no_of_assignments] => 0 [patent_current_assignee] =>[type] => publication [pdf_file] =>[firstpage_image] =>[orig_patent_app_number] => 17888547 [rel_patent_id] =>[rel_patent_doc_number] =>)

Array ( [id] => 18430822 [patent_doc_number] => 11676044 [patent_country] => US [patent_kind] => B1 [patent_issue_date] => 2023-06-13 [patent_title] => Systems and methods for generating a chatbot [patent_app_type] => utility [patent_app_number] => 17/889186 [patent_app_country] => US [patent_app_date] => 2022-08-16 [patent_effective_date] => 0000-00-00 [patent_drawing_sheets_cnt] => 9 [patent_figures_cnt] => 10 [patent_no_of_words] => 8374 [patent_no_of_claims] => 21 [patent_no_of_ind_claims] => 2 [patent_words_short_claim] => 120 [patent_maintenance] => 1 [patent_no_of_assignments] => 0 [patent_current_assignee] =>[type] => patent [pdf_file] =>[firstpage_image] =>[orig_patent_app_number] => 17889186 [rel_patent_id] =>[rel_patent_doc_number] =>)

Array ( [id] => 18060593 [patent_doc_number] => 20220391679 [patent_country] => US [patent_kind] => A1 [patent_issue_date] => 2022-12-08 [patent_title] => SPECIALIZED FIXED FUNCTION HARDWARE FOR EFFICIENT CONVOLUTION [patent_app_type] => utility [patent_app_number] => 17/886055 [patent_app_country] => US [patent_app_date] => 2022-08-11 [patent_effective_date] => 0000-00-00 [patent_drawing_sheets_cnt] => 0 [patent_figures_cnt] => 0 [patent_no_of_words] => 33704 [patent_no_of_claims] => 0 [patent_no_of_ind_claims] => -22 [patent_words_short_claim] => 117 [patent_maintenance] => 1 [patent_no_of_assignments] => 0 [patent_current_assignee] =>[type] => publication [pdf_file] =>[firstpage_image] =>[orig_patent_app_number] => 17886055 [rel_patent_id] =>[rel_patent_doc_number] =>)

Array ( [id] => 18912264 [patent_doc_number] => 11875244 [patent_country] => US [patent_kind] => B2 [patent_issue_date] => 2024-01-16 [patent_title] => Enhanced dynamic random access memory (eDRAM)-based computing-in-memory (CIM) convolutional neural network (CNN) accelerator [patent_app_type] => utility [patent_app_number] => 18/009341 [patent_app_country] => US [patent_app_date] => 2022-08-05 [patent_effective_date] => 0000-00-00 [patent_drawing_sheets_cnt] => 16 [patent_figures_cnt] => 19 [patent_no_of_words] => 5282 [patent_no_of_claims] => 5 [patent_no_of_ind_claims] => 1 [patent_words_short_claim] => 895 [patent_maintenance] => 1 [patent_no_of_assignments] => 0 [patent_current_assignee] =>[type] => patent [pdf_file] =>[firstpage_image] =>[orig_patent_app_number] => 18009341 [rel_patent_id] =>[rel_patent_doc_number] =>)

Array ( [id] => 18942280 [patent_doc_number] => 20240037419 [patent_country] => US [patent_kind] => A1 [patent_issue_date] => 2024-02-01 [patent_title] => ACCURACY OF MULTIVARIATE APPROACH FOR TIME-SERIES BASED FORECASTING [patent_app_type] => utility [patent_app_number] => 17/878514 [patent_app_country] => US [patent_app_date] => 2022-08-01 [patent_effective_date] => 0000-00-00 [patent_drawing_sheets_cnt] => 0 [patent_figures_cnt] => 0 [patent_no_of_words] => 11433 [patent_no_of_claims] => 0 [patent_no_of_ind_claims] => -17 [patent_words_short_claim] => 99 [patent_maintenance] => 1 [patent_no_of_assignments] => 0 [patent_current_assignee] =>[type] => publication [pdf_file] =>[firstpage_image] =>[orig_patent_app_number] => 17878514 [rel_patent_id] =>[rel_patent_doc_number] =>)

Array ( [id] => 18942280 [patent_doc_number] => 20240037419 [patent_country] => US [patent_kind] => A1 [patent_issue_date] => 2024-02-01 [patent_title] => ACCURACY OF MULTIVARIATE APPROACH FOR TIME-SERIES BASED FORECASTING [patent_app_type] => utility [patent_app_number] => 17/878514 [patent_app_country] => US [patent_app_date] => 2022-08-01 [patent_effective_date] => 0000-00-00 [patent_drawing_sheets_cnt] => 0 [patent_figures_cnt] => 0 [patent_no_of_words] => 11433 [patent_no_of_claims] => 0 [patent_no_of_ind_claims] => -17 [patent_words_short_claim] => 99 [patent_maintenance] => 1 [patent_no_of_assignments] => 0 [patent_current_assignee] =>[type] => publication [pdf_file] =>[firstpage_image] =>[orig_patent_app_number] => 17878514 [rel_patent_id] =>[rel_patent_doc_number] =>)

Array ( [id] => 18007489 [patent_doc_number] => 20220366255 [patent_country] => US [patent_kind] => A1 [patent_issue_date] => 2022-11-17 [patent_title] => Neural Network Processor [patent_app_type] => utility [patent_app_number] => 17/874573 [patent_app_country] => US [patent_app_date] => 2022-07-27 [patent_effective_date] => 0000-00-00 [patent_drawing_sheets_cnt] => 0 [patent_figures_cnt] => 0 [patent_no_of_words] => 6256 [patent_no_of_claims] => 0 [patent_no_of_ind_claims] => -17 [patent_words_short_claim] => 116 [patent_maintenance] => 1 [patent_no_of_assignments] => 0 [patent_current_assignee] =>[type] => publication [pdf_file] =>[firstpage_image] =>[orig_patent_app_number] => 17874573 [rel_patent_id] =>[rel_patent_doc_number] =>)

Array ( [id] => 18007489 [patent_doc_number] => 20220366255 [patent_country] => US [patent_kind] => A1 [patent_issue_date] => 2022-11-17 [patent_title] => Neural Network Processor [patent_app_type] => utility [patent_app_number] => 17/874573 [patent_app_country] => US [patent_app_date] => 2022-07-27 [patent_effective_date] => 0000-00-00 [patent_drawing_sheets_cnt] => 0 [patent_figures_cnt] => 0 [patent_no_of_words] => 6256 [patent_no_of_claims] => 0 [patent_no_of_ind_claims] => -17 [patent_words_short_claim] => 116 [patent_maintenance] => 1 [patent_no_of_assignments] => 0 [patent_current_assignee] =>[type] => publication [pdf_file] =>[firstpage_image] =>[orig_patent_app_number] => 17874573 [rel_patent_id] =>[rel_patent_doc_number] =>)

Array ( [id] => 18158386 [patent_doc_number] => 20230024977 [patent_country] => US [patent_kind] => A1 [patent_issue_date] => 2023-01-26 [patent_title] => METHOD OF PROCESSING DATA, DATA PROCESSING DEVICE, DATA PROCESSING PROGRAM, AND METHOD OF GENERATING NEURAL NETWORK MODEL [patent_app_type] => utility [patent_app_number] => 17/814292 [patent_app_country] => US [patent_app_date] => 2022-07-22 [patent_effective_date] => 0000-00-00 [patent_drawing_sheets_cnt] => 0 [patent_figures_cnt] => 0 [patent_no_of_words] => 10347 [patent_no_of_claims] => 0 [patent_no_of_ind_claims] => -18 [patent_words_short_claim] => 75 [patent_maintenance] => 1 [patent_no_of_assignments] => 0 [patent_current_assignee] =>[type] => publication [pdf_file] =>[firstpage_image] =>[orig_patent_app_number] => 17814292 [rel_patent_id] =>[rel_patent_doc_number] =>)

Array ( [id] => 18897557 [patent_doc_number] => 20240013042 [patent_country] => US [patent_kind] => A1 [patent_issue_date] => 2024-01-11 [patent_title] => SYSTEM AND METHODS FOR PIPLINED HETEROGENEOUS DATAFLOW FOR ARTIFICIAL INTELLIGENCE ACCELERATORS [patent_app_type] => utility [patent_app_number] => 17/859721 [patent_app_country] => US [patent_app_date] => 2022-07-07 [patent_effective_date] => 0000-00-00 [patent_drawing_sheets_cnt] => 0 [patent_figures_cnt] => 0 [patent_no_of_words] => 7247 [patent_no_of_claims] => 0 [patent_no_of_ind_claims] => -17 [patent_words_short_claim] => 107 [patent_maintenance] => 1 [patent_no_of_assignments] => 0 [patent_current_assignee] =>[type] => publication [pdf_file] =>[firstpage_image] =>[orig_patent_app_number] => 17859721 [rel_patent_id] =>[rel_patent_doc_number] =>)

Array ( [id] => 18897557 [patent_doc_number] => 20240013042 [patent_country] => US [patent_kind] => A1 [patent_issue_date] => 2024-01-11 [patent_title] => SYSTEM AND METHODS FOR PIPLINED HETEROGENEOUS DATAFLOW FOR ARTIFICIAL INTELLIGENCE ACCELERATORS [patent_app_type] => utility [patent_app_number] => 17/859721 [patent_app_country] => US [patent_app_date] => 2022-07-07 [patent_effective_date] => 0000-00-00 [patent_drawing_sheets_cnt] => 0 [patent_figures_cnt] => 0 [patent_no_of_words] => 7247 [patent_no_of_claims] => 0 [patent_no_of_ind_claims] => -17 [patent_words_short_claim] => 107 [patent_maintenance] => 1 [patent_no_of_assignments] => 0 [patent_current_assignee] =>[type] => publication [pdf_file] =>[firstpage_image] =>[orig_patent_app_number] => 17859721 [rel_patent_id] =>[rel_patent_doc_number] =>)

Array ( [id] => 18897557 [patent_doc_number] => 20240013042 [patent_country] => US [patent_kind] => A1 [patent_issue_date] => 2024-01-11 [patent_title] => SYSTEM AND METHODS FOR PIPLINED HETEROGENEOUS DATAFLOW FOR ARTIFICIAL INTELLIGENCE ACCELERATORS [patent_app_type] => utility [patent_app_number] => 17/859721 [patent_app_country] => US [patent_app_date] => 2022-07-07 [patent_effective_date] => 0000-00-00 [patent_drawing_sheets_cnt] => 0 [patent_figures_cnt] => 0 [patent_no_of_words] => 7247 [patent_no_of_claims] => 0 [patent_no_of_ind_claims] => -17 [patent_words_short_claim] => 107 [patent_maintenance] => 1 [patent_no_of_assignments] => 0 [patent_current_assignee] =>[type] => publication [pdf_file] =>[firstpage_image] =>[orig_patent_app_number] => 17859721 [rel_patent_id] =>[rel_patent_doc_number] =>)