[WiMLDS x MLOps Paris] How to make AI models faster, cheaper & greener.
Détails
⚠️⚠️⚠️ Mandatory registration on Eventbrite via this link ⚠️⚠️⚠️
The Women in Machine Learning & Data Science (WiMLDS) Meetup aims to inspire, educate, regardless of gender, and support women and gender minorities in the field.
We are back for an exclusive collaboration between Women in Machine Learning & Data Science Paris and MLOps Paris.
All genders may attend our meetups.
Agenda
18:45 arrival to Vestiaire Collective, 53 Rue de Châteaudun, 75009 Paris.
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19:00 - Launch of the evening by Paris WiMLDS, MLOps Paris and Vestiaire Collective.
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19:15 - How to make AI models faster, cheaper & greener, by Minette Kaunismäki**,** Developer Advocate at PrunaAI.
Abstract: AI models become more complex, the cost of inference—both in terms of computation and energy—continues to rise. In this talk, we will explore how combining compression techniques such as quantisation, pruning, caching, and distillation can significantly optimise model performance during inference. By applying these methods, combining compression enables reductions in model size and computational load while maintaining quality, thereby making AI more accessible and environmentally sustainable.
19:45 - Learning to Rank as a Search as a Service company: Expectation VS Reality, by Claire HELME-GUIZON, Machine Learning Engineer at Algolia
Abstract: A quick dive (so you don't make the same mistakes) on some of the struggles we faced building and shipping our LTR model, respecting theconstraints of a SaaS company.
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20:45 - Cocktail & Networking
The cocktail is sponsored by Vestiaire Collective.
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After the meet-up, a summary be available on our Medium page : https://wimlds-paris.medium.com/
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Code of Conduct
WiMLDS & MLOps are dedicated to providing a harassment-free experience for everyone. We do not tolerate harassment of participants in any form.
All communication should be appropriate for a professional audience including people of many different backgrounds. Sexual language and imagery is not appropriate.
Be kind to others. Do not insult or put down others. Behave professionally. Remember that harassment and sexist, racist, or exclusionary jokes are not appropriate.
Thank you for helping make this a welcoming, friendly community for all.
All attendees should read the full Code of Conduct before participating: https://github.com/WiMLDS/starter-kit/wiki/Code-of-conduct