WO2025093915 - REDUCING CARBON FOOTPRINT OF MACHINE LEARNING MODELS
National phase entry is expected:
Publication Number
WO/2025/093915
Publication Date
08.05.2025
International Application No.
PCT/IB2024/000582
International Filing Date
30.10.2024
Title **
[English]
REDUCING CARBON FOOTPRINT OF MACHINE LEARNING MODELS
[French]
RÉDUCTION DE L'EMPREINTE CARBONE DE MODÈLES D'APPRENTISSAGE AUTOMATIQUE
Applicants **
MIND FOUNDRY LTD
Inventors
TOSI, Alessandra
BELL, Robert
KORDA, Nathaniel
CROWN, Joanna
ZILLI, Davide
MULLINS, Brian
OSBORNE, Michael
ROBERTS, Stephen
GARFOOT, Alistair
Priority Data
18/497,400
30.10.2023
US
Application details
| Total Number of Claims/PCT | * |
| Number of Independent Claims | * |
| Number of Priorities | * |
| Number of Multi-Dependent Claims | * |
| Number of Drawings | * |
| Pages for Publication | * |
| Number of Pages with Drawings | * |
| Pages of Specification | * |
| * | |
| Number of Office Actions | * |
| * | |
International Searching Authority |
EPO
* |
| Recordal of a Change of the Applicant's Name/Address |
Change of Applicant's Name and Address
* |
| Type of Assignment |
The Standard Agent's Assignment
* |
| Applicant's Legal Status |
Legal Entity
* |
| * | |
| * | |
| * | |
| * | |
| * | |
| Entry into National Phase under |
Chapter I
* |
| Patent Delivery |
Send the Letters Patent by Courier
* |
| 译文 |
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* The data is based on automatic recognition. Please verify and amend if necessary.
** IP-Coster compiles data from publicly available sources. If this data includes your personal information, you can contact us to request its removal.
Quotation for National Phase entry
| Country | Stages | Total | |
|---|---|---|---|
| China | Filing, Examination, Granting | 2400 | |
| EPO | Filing, Examination, Granting | 12156 | |
| Japan | Filing, Examination, Granting | 2372 | |
| South Korea | Filing, Examination, Granting | 2549 | |
| USA | Filing, Examination, Granting | 4740 |
Total:
24,217
The term for entry into the National Phase has expired. This quotation is for informational purposes only
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Abstract[English]
A machine learning platform operating at a server is described. The machine learning platform accesses a dataset from a datastore. A task that identifies a target of a machine learning algorithm from the machine learning platform is defined. The machine learning algorithm forms a machine learning model based on the dataset and the task. The machine learning platform deploys the machine learning model and monitors a performance of the machine learning model after deployment. The machine learning platform updates the machine learning model based on the monitoring.[French]
Ine plateforme d'apprentissage automatique fonctionnant au niveau d'un serveur est décrite. La plateforme d'apprentissage automatique accède à un ensemble de données d'une mémoire de données. Une tâche qui identifie une cible d'un algorithme d'apprentissage automatique à partir de la plateforme d'apprentissage automatique est définie. L'algorithme d'apprentissage automatique forme un modèle d'apprentissage automatique sur la base de l'ensemble de données et de la tâche. La plateforme d'apprentissage automatique déploie le modèle d'apprentissage automatique et surveille une performance du modèle d'apprentissage automatique après le déploiement. La plateforme d'apprentissage automatique met à jour le modèle d'apprentissage automatique sur la base de la surveillance.