公开(公告)号：US20220406417A1

公开(公告)日：2022-12-22

申请号：US17713390

申请日：2022-04-05

申请人： NotCo Delaware, LLC

发明人： Kyohei Kaneko ,  Nathan O'Hara ,  Isadora Nun ,  Aadit Patel ,  Kavitakumari Solanki ,  Karim Pichara

IPC分类号： G16C20/70 ,  G16B99/00 ,  G06N3/08 ,  G16C20/20 ,  G06N3/04 ,  G16C20/50 ,  G16B40/00 ,  G16C20/40

摘要： Techniques to suggest alternative chemical compounds that can be used to recreate or mimic a target flavor using artificial intelligence are disclosed. A neural network based model is trained on source chemical compounds and their corresponding flavors and odors. The neural network-based model learns compound embeddings of the source chemical compounds and a target chemical compound of a food item. From the compound embeddings, one or more chemical compounds that are closest to the target chemical compound may be determined by a distance metric. Each suggested chemical compound is an alternative that can be used to recreate functional features of the target chemical compound.

公开(公告)号：US11164478B2

公开(公告)日：2021-11-02

申请号：US16416095

申请日：2019-05-17

申请人： NotCo Delaware, LLC

发明人： Karim Pichara ,  Pablo Zamora ,  Matías Muchnick ,  Orlando Vásquez

IPC分类号： G09B19/00 ,  G06N3/04 ,  G01N33/02 ,  G01N33/12 ,  G06F16/9035

摘要： Systems and methods to mimic a target food item using artificial intelligence are disclosed. The system can learn from open source and proprietary databases. A prediction model can be trained using features of the source ingredients to match those of the given target food item. A formula comprising a combination of most relevant source ingredients and their proportions can be determined using the trained prediction model. A set of existing recipes can be used as a dataset to train a recurrent neural network (RNN) and/or other suitable models. The RNN can be used to determine a recipe to mimic the target food item. The recipe may comprise a cooking process for the set of ingredients in the formula and can be cooked by a chef. The recipe may be further modified as necessary based on human feedback on sensorial descriptors.

公开(公告)号：US11644416B2

公开(公告)日：2023-05-09

申请号：US17180599

申请日：2021-02-19

申请人： NOTCO DELAWARE, LLC

发明人： Nathan O'Hara ,  Adil Yusuf ,  Julia Christin Berning ,  Francisca Villanueva ,  Rodrigo Contreras ,  Isadora Nun ,  Aadit Patel ,  Karim Pichara

IPC分类号： G01N21/35 ,  G06N5/04 ,  G06N20/00 ,  G06Q30/0201

CPC分类号： G01N21/35 ,  G06N5/04 ,  G06N20/00 ,  G01N2021/3595 ,  G06Q30/0201

摘要： An artificial intelligence model receives a FTIR spectrum of a given ingredient to predict its protein secondary structure. The model includes three artificial modules, which generate three predicted values corresponding to structural categories (e.g., α-helix, β-sheet, and other) of the predicted secondary structure. Proteins may be compared for similarity based on predicted values corresponding to the structural categories of the predicted secondary structure.

公开(公告)号：US11631034B2

公开(公告)日：2023-04-18

申请号：US17221129

申请日：2021-04-02

申请人： NOTCO DELAWARE, LLC

发明人： Karim Pichara ,  Pablo Zamora ,  Matias Muchnick ,  Antonia Larranaga

IPC分类号： G06N20/00 ,  A23L27/20 ,  G06F18/2431 ,  G06V10/764

摘要： Techniques to generate a flavor profile using artificial intelligence are disclosed. A flavor classifier classifies flavors for a given set of ingredients of a recipe from a set of possible classes of flavors. The flavor classifier may use different deep learning models to allow for different granularity levels corresponding to each flavor based on desired preciseness with classification of a particular flavor. A respective flavor predictor may or may not be used for each granularity level based on output of a certainty level classifier used for determining a preceding level of granularity.

公开(公告)号：US10957424B1

公开(公告)日：2021-03-23

申请号：US16989413

申请日：2020-08-10

申请人： NotCo Delaware, LLC

发明人： Yoav Navon ,  Karim Pichara ,  Aadit Patel ,  Ofer Philip Korsunsky ,  Richard Hausman

IPC分类号： G16C20/30 ,  G16C20/10 ,  G06K9/62 ,  G06N3/08 ,  G16C20/70

摘要： Techniques to mimic a target food item using artificial intelligence are disclosed. A formula generator is trained using combinations of ingredients. A training set may include, for each combination of ingredients, proportions, and features of the ingredients in a respective combination of ingredients. Given a target food item, the formula generator determines a predicted formula that matches the given target food item. The predicted formula includes a set ingredients and a respective proportion of each ingredient in the set of ingredient.

公开(公告)号：US20230099733A1

公开(公告)日：2023-03-30

申请号：US17994822

申请日：2022-11-28

申请人： NotCo Delaware, LLC

发明人： Nathan O'Hara ,  Adil Yusuf ,  Julia Christin Berning ,  Francisca Villanueva ,  Rodrigo Contreras ,  Isadora Nun ,  Aadit Patel ,  Karim Pichara

IPC分类号： G01N21/35 ,  G06N5/04 ,  G06N20/00

摘要： An artificial intelligence model receives a FTIR spectrum of a given ingredient to predict its protein secondary structure. The model includes three artificial modules, which generate three predicted values corresponding to structural categories (e.g., α-helix, β-sheet, and other) of the predicted secondary structure. Proteins may be compared for similarity based on predicted values corresponding to the structural categories of the predicted secondary structure.

公开(公告)号：US20210219583A1

公开(公告)日：2021-07-22

申请号：US17221129

申请日：2021-04-02

申请人： NOTCO DELAWARE, LLC

发明人： Karim Pichara ,  Pablo Zamora ,  Matias Muchnick ,  Antonia Larranaga

IPC分类号： A23L27/20 ,  G06N20/00 ,  G06K9/62

摘要： Techniques to generate a flavor profile using artificial intelligence are disclosed. A flavor classifier classifies flavors for a given set of ingredients of a recipe from a set of possible classes of flavors. The flavor classifier may use different deep learning models to allow for different granularity levels corresponding to each flavor based on desired preciseness with classification of a particular flavor. A respective flavor predictor may or may not be used for each granularity level based on output of a certainty level classifier used for determining a preceding level of granularity.

公开(公告)号：US10962473B1

公开(公告)日：2021-03-30

申请号：US17090014

申请日：2020-11-05

申请人： NotCo Delaware, LLC

发明人： Nathan O'Hara ,  Adil Yusuf ,  Julia Christin Berning ,  Francisca Villanueva ,  Rodrigo Contreras ,  Isadora Nun ,  Aadit Patel ,  Karim Pichara

IPC分类号： G01N21/35 ,  G06N5/04 ,  G06N20/00 ,  G06Q30/02

摘要： An artificial intelligence model receives a FTIR spectrum of a given ingredient to predict its protein secondary structure. The model includes three artificial modules, which generate three predicted values corresponding to structural categories (e.g., α-helix, β-sheet, and other) of the predicted secondary structure. Proteins may be compared for similarity based on predicted values corresponding to the structural categories of the predicted secondary structure.

公开(公告)号：US20220005376A1

公开(公告)日：2022-01-06

申请号：US17479770

申请日：2021-09-20

申请人： NotCo Delaware, LLC

发明人： Karim Pichara ,  Pablo Zamora ,  Matias Muchnick ,  Orlando Vasquez

IPC分类号： G09B19/00 ,  G06N3/04 ,  G01N33/02 ,  G01N33/12 ,  G06F16/9035

摘要： Systems and methods to mimic a target food item using artificial intelligence are disclosed. The system can learn from open source and proprietary databases. A prediction model can be trained using features of the source ingredients to match those of the given target food item. A formula comprising a combination of most relevant source ingredients and their proportions can be determined using the trained prediction model. A set of existing recipes can be used as a dataset to train a recurrent neural network (RNN) and/or other suitable models. The RNN can be used to determine a recipe to mimic the target food item. The recipe may comprise a cooking process for the set of ingredients in the formula and can be cooked by a chef. The recipe may be further modified as necessary based on human feedback on sensorial descriptors.

公开(公告)号：US11164069B1

公开(公告)日：2021-11-02

申请号：US17167981

申请日：2021-02-04

申请人： NOTCO DELAWARE, LLC

发明人： Ofer Philip Korsunsky ,  Yoav Navon ,  Aadit Patel ,  Carolina Carriel ,  Catalina Donoso ,  Karim Pichara ,  Paula Pesse Delpiano

IPC分类号： G06N3/04 ,  G06N3/08

摘要： Techniques to mimic a target food item using artificial intelligence are disclosed. A formula generator learns from open source and proprietary databases of ingredients and recipes. The formula generator is trained using features of the ingredients and using recipes. Given a target food item, the formula generator determines a formula that matches the given target food item and a score for the formula. The formula generator may generate, based on user-provided control definitions, numerous formulas that match the given target food item and may select an optimal formula from the generated formulas based on score.