Neuro-Symbolic AI Summer School 2025 - Day 1 | Centaur AI Institute

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💻 GitHub: 💬 Discord: 🤝 LinkedIn: Agenda: Day 1: Frameworks and Foundations | AUG 14 0:00 Lobby 12:02 Alexander Gray, Centaur AI Institute | Neuro-Symbolic AI and NSSS4 50:36 Arvind Narayanan, Princeton | Assessing the Current State of AI 1:34:56 Leilani Gilpin, UC Santa Cruz | Neuro-Symbolic AI for Safer Autonomous Vehicles 2:27:20 Mateo Zarlenga and Pietro Barbiero, Cambridge | Foundations of Interpretable Models 3:21:50 Parisa Kordjamshidi, Michigan State | Compositional Learning in Language and Vision 4:18:43 Parikshit Ram, IBM Research | How to Measure Compositionality, and Why it Leads to Better Generalization 5:08:16 Peihao Wang, UT Austin | Why Neural Network Can Discover Symbolic Structures 6:01:12 Changlong Wu, Purdue | Why Current Models Will Always Hallucinate (and a Path Forward) Tired of the same old AI ideas and looking for something new? Or wondering if there are any deep alternatives to models that hallucinate, elude human debuggability, and have only limited ability to reason, plan, or do math? 📢 Please join us for the 4th Neuro-Symbolic AI Summer School (NSSS), a free, fully-remote meeting to be held Aug 14-15, 2025 - where you can learn how to be part of this exciting area at the most forward-looking cutting edge of AI. This year's theme is "AI for Precise Computation: Mathematics, Reasoning, and Planning".🎤 Speakers:Alexander Gray, Centaur AI InstituteAnkit Anand, DeepMindArtur Garcez, City Univ London  Arvind Narayanan, Princeton  Bin Yu, UC Berkeley  Bowen Li, Carnegie Mellon    Changlong Wu, Purdue  Felix Petersen, Stanford Leilani Gilpin, UC Santa Cruz  Mateo Zarlenga and Pietro Barbiero, Cambridge  Olga Vileskaia and Kevin O'Connor, Centaur AI Institute  Parikshit Ram, IBM Research  Parisa Kordjamshidi, Michigan State  Peihao Wang, UT AustinPranava Madhyastha, City Univ LondonSoroush Saghafian, Harvard  Sridhar Mahadevan, Adobe Research and UMass Amherst  Yong Lin, Princeton  🌐 NSSS ‘25 is the latest in a series of research and educational events that aim to accelerate progress in the fast-emerging area of neuro-symbolic AI by teaching graduate students, data scientists, and researchers principles from the side of AI they may be less familiar with, as well as presenting a curation of emerging research ideas at the intersection. 🎯 The focus of the event is on techniques, in particular those which augment neural network/ML ideas with symbolic AI ideas, to address at least three main open problems of AI: 1) human interpretability/controllability, 2) learning with less data/computation (e.g. via knowledge), and 3) out-of-distribution generalization (e.g. via reasoning). #AI #NeuroSymbolic #FutureOfAI