🔥The 9th Round of Easy Loan, Earn $40 Reward is in progress❗️ ⏰ Promotion Period: January 15th - Feburary 15th, 2025 👉 Register now and check more details at gate.io/campaigns/358

Item response theory in AI: Analysing machine learning classifiers at ... sciencedirect.com/science/articl…

This person took ~1700 pages of notes in mathematics lectures using LaTeX and Vim, and documented the workflow: castel.dev/post/lecture-n…

📡Happy to announce that our paper "Automated Data Transformation with Inductive Programming and Dynamic Background Knowledge" has been accepted at ECML PKDD #ECMLPKDD2019 👏😄👩‍💻 👨‍💻Nando Cèsar Ferri Universitat Politècnica de València #VRAIN #VRAINUPV #DataScience

Seeking paper submissions for the 1st Evaluating Progress in AI workshop at ECAI20. Experimental and theoretical papers on developing benchmarks, indicators, measuring progress, forecasting societal impacts of AI advances. Submission deadline March 20th! dmip.webs.upv.es/EPAI2020/

What do we mean when we refer to #ArtificialIntelligence? We review existing definitions and work towards an operational definition of AI #AIWatch #humaint EU_ScienceHub ec.europa.eu/jrc/en/publica…

🚨 UPDATE: In the light of the #COVID19 situation and having the health and safety of all the community as top priority, #ECAI2020 has been rescheduled to August 29-September 2. ➡️ Complete statement is at: ecai2020.eu/covid-awarenes… We look forward to seeing you next August!

Today we are happy to announce #DigitalECAI2020! A digital conference of the highest scientific level which will offer to the #AI community lots of possibilities to meet, debate and interact. Read our statement at: digital.ecai2020.eu/release-from-o… Join us at digital.ecai2020.eu!

Happy that the #humaint project and team are mentioned by Stephen Quest on his summary of EU_ScienceHub activities Songül Tolan Vicky Charisi Marius Miron Nando

🎉🎉🎉 I'm excited to introduce "a ggplot2 grammar guide". Here is part of the **visual table of contents** (viztoc). You can click through to get at-your-own-pace guidance from *flipbooks* showing code-output plot evolution! More in 🧵 1/ evamaerey.github.io/ggplot2_gramma…

Futures of artificial intelligence through technology readiness levels. New publication with Nando and José Hernández-Orallo doi.org/10.1016/j.tele… #humaint #AI #AIWatch EU_ScienceHub

Proud to see some #humaint work on the social and ethical impact of AI reflected in this very interesting report #AI #jobs #healtchare #AIethics Songül Tolan Nando #EU

Artificial Intelligence is a fantastic opportunity for Europe. And citizens deserve technologies they can trust. Today we present new rules for trustworthy AI. They set high standards based on the different levels of risk.

Our paper "Training on the Test Set: Mapping the System-Problem Space in AI" (aaai.org/AAAI22Papers/S…) is the runner up for the Blue Sky Awards in AAAI 2022!

📐Our Evaluation Beyond Metrics workshop at IJCAI got accepted... so prepare your cool papers! 💻sites.google.com/view/ebem2022 With @LucyCheke, DanajaRutar, John Burden, Ryan Burnell, Tomer Ullman and twitterless Josh Tenenbaum, José Hernández-Orallo and Fernando Martínez-Plumed

Is it time to rethink how we perform system evaluations in AI? In our new Science Magazine paper, we show that over-reliance on aggregate metrics and a lack of transparency in reporting threatens public understanding and hinders progress in the field. 1/8 doi.org/10.1126/scienc…

Científicos señalan los efectos catastróficos que puede causar la IA eldiario.es/1_9a63ef?utm_c… via elDiario.es

New and shiny AI systems have superseded the ones we reference (it took a while to publish), but our perspectives and suggestions for evaluating them have only become more relevant. Go have a read! 👽👽

1/ New paper nature! Discrepancy between human expectations of task difficulty and LLM errors harms reliability. In 2022, Ilya Sutskever Ilya Sutskever predicted: "perhaps over time that discrepancy will diminish" (youtu.be/W-F7chPE9nU, min 61-64). We show this is *not* the case!

New Paper: We unlock AI Evaluation with explanatory and predictive power through general ability scales! -Explains what common benchmarks really measure -Extracts explainable ability profiles of AI systems -Predicts performance for new task instances, in & out-of-distribution 🧵