Method, control unit, central entity, system and data processing program for providing recipes for cooking
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Solution Overview
Problem
Existing cooking devices lack an efficient method to provide users with a diverse and creative range of recipes, often relying on limited downloadable options from the internet or social networks.
Innovation Solution
A method utilizing a trained recipe generator, which can be implemented in a cooking device or a central entity, to generate new recipes based on user triggers, preferences, and cooking device capabilities, using generative artificial intelligence and language models.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If recipes are downloaded from the internet or social networks, then a certain number of recipes are available, but the number of available recipes is limited
Solution Approach 1:
The system enables the cooking device to generate recipes autonomously using an integrated recipe generator based on artificial intelligence. The device can create new recipes without external input, transforming from a passive downloader to an active creator of culinary content.
Solution Approach 2:
The patent extracts the recipe generation capability from external sources (internet, social networks) and embeds it directly into the cooking device through a dedicated recipe generator component, eliminating dependency on external downloads.
2Adaptability or versatility
If a recipe generator is integrated into the cooking device, then recipe diversity and creativity are improved, but device complexity increases
Solution Approach 1:
The recipe generator is designed as a multi-functional component that can adapt to different cooking devices, cuisines, ingredients, and user preferences. It serves multiple purposes: generating recipes, adapting to device capabilities, and learning from user feedback, thereby justifying its integration despite increased complexity.
3Reliability
If the recipe generator is trained with extensive data, then recipe quality and suitability are improved, but training time and computational resources increase
Solution Approach 1:
The recipe generator undergoes preliminary training with extensive culinary data before deployment, establishing a robust foundation of culinary knowledge. This pre-training ensures high recipe quality from the start, reducing the need for extensive ongoing training and adjustments.
Solution Approach 2:
The system implements continuous feedback loops where user responses to generated recipes are used to refine and improve the recipe generator's performance over time, gradually enhancing recipe quality without requiring repeated extensive training cycles.
Data Source
AI summary
A method for providing recipes for cooking to a user of a cooking device includes providing a trained recipe generator and/or training a recipe generator, receiving a trigger, especially a request, a query or a prompt, from the user of the cooking device, generating, based on the trigger, a new recipe using the recipe generator, and providing the new recipe to the user. A related data processing program product, a control unit of the cooking device, a related central entity and a system, are also provided.