Have you wondered how much CO2 your favourite recommender system emits? A interesting study entitled “Clicks to Carbon: The Environmental Toll of Recommender Systems” by Tobias Vente et al. aimed to address the issue. #recsys2024
Did you know that a 2023 RecSys algorithm emits 42x more CO2e than a 2013 RecSys algorithm? 📈🚨
If not, don't miss our presentation: "From Clicks to Carbon: The Environmental Toll of Recommender Systems" w/ @LWegmeth , @alansaid & @JoeranBeel in Session 11 at #RecSys2024! 🌍🌱
Excited to kick off #acm#RecSys2024 🚀! Looking forward to a week full of inspiring talks and engaging conversations!
This year, I contributed to 7 submissions, sharing the work with the community will be busy but fulfilling.
See you at #RecSys2024!
Big shoutout to my amazing co-authors for their hard work and collaboration!
I couldn't have done it without you. 🙌
@LWegmeth@alansaid@JoeranBeel, Zainil Mehta, Moritz Baumgart, Philipp Miester and Ardalan Arabzadeh
🌱Did you know a typical 2023 deep-learning #recsys paper generated as much CO2 as a flight from Melbourne to NY (~3,300 kg)? That's 42x more than a typical paper in 2013! More details at #recsys2024: "From Clicks to Carbon." #GreenRecSys#GreenML#GreenAutoML#DeepLearning
From digital clicks to environmental impact 🌎🌱
Our work (w/ @LWegmeth, @alansaid, and @JoeranBeel), "From Clicks to Carbon: The Environmental Toll of Recommender Systems" got accepted at the #recsys2024 reproducibility track 🎉
🛫 see you at the @ACMRecSys 2024 in Bari!!
BREAKING NEWS! 🚨
@LWegmeth and Tobias Vente arrived in #Antwerp for the #DBWRS2023!
They expect two exciting days full of #RecSys talks, posters and discussions.