Artificial Intelligence: Difference between revisions
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* We can use AI and non-AI techniques together and blend them, so that when one of the technique fails for some reason, the other one can save the day. | * We can use AI and non-AI techniques together and blend them, so that when one of the technique fails for some reason, the other one can save the day. | ||
* Even if a model does not have perfect results, at Open Food Facts scale, it might save contribution time and increase food transparency. Furthermore, it's possible to leverage the community to validate guesses and improve the models over time. | * Even if a model does not have perfect results, at Open Food Facts scale, it might save contribution time and increase food transparency. Furthermore, it's possible to leverage the community to validate guesses and improve the models over time. | ||
= 📺 Presentation = | |||
* Watch Raphael explain (in French) how we use Artificial Intelligence at Open Food Facts: https://tube.numerique.gouv.fr/w/dEHLAbuchWu8zGzY5JgSgz | |||
= Projects = | = Projects = | ||
Revision as of 17:06, 16 August 2024
Machine learning models and "AI" are used in Open Food Facts to extract information from product images and to perform predictions, such as the product category.
Principles
- AI is there to help accelerate our transparency mission by augmenting Open Food Facts contributors, letting them focus on value-added tasks and increasing their personal impact.
- We can use AI and non-AI techniques together and blend them, so that when one of the technique fails for some reason, the other one can save the day.
- Even if a model does not have perfect results, at Open Food Facts scale, it might save contribution time and increase food transparency. Furthermore, it's possible to leverage the community to validate guesses and improve the models over time.
📺 Presentation
- Watch Raphael explain (in French) how we use Artificial Intelligence at Open Food Facts: https://tube.numerique.gouv.fr/w/dEHLAbuchWu8zGzY5JgSgz
Projects
🤖 Robotoff
Robotoff is Open Food Facts "AI" service: it takes care of calling the ML models and storing all predictions. Robotoff documentation describes in details how Robotoff works.
Depending on its confidence, each prediction is either applied automatically or require a manual validation. Hunger Games is our in-house validation tool.
All machine learning models used in production are stored on Github as releases, in the robotoff-models repository.
Issues opened in Robotoff repository are only related to Robotoff codebase improvements and bug tracking. To discuss machine learning projects or tasks, use the openfoodfacts-ai issue tracker. We also store research code in the openfoodfacts-ai repository.
Hunger Games
Hunger Games is our collaborative and playful annotation engine. It allows you to annotate in bulk logos and labels, to mass complete nutrition tables and ingredient lists, and to answer Robotoff questions in vast numbers.
How to contribute?
There are many ways to help:
- contribute to Robotoff, some issues are tagged as suitable for newcomers
- help to solve one of the issue listed in openfoodfacts-ai.
Most of our discussions happen on Slack. Depending on your interests, you can join the following channels: #robotoff and #hunger-games (robotoff and hunger games channels respectively).
📆 Weekly meeting
- You're also welcome to join the Robotoff weekly e-meeting that takes place every Tuesday at 11am CET (Paris time): https://meet.google.com/qvv-grzm-gzb
- For convenience, you can subscribe to the Community Calendar: Events to get a weekly reminder
Get in touch
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