MIT Computer Science and Artificial Intelligence Laboratory (CSAIL)’s Post

💡 Curious about how Generative AI is reshaping industries? 💡 MIT xPRO is hosting a free webinar to introduce their latest six-week online course: Driving Innovation with Generative AI. Led by MIT's Antonio Torralba, this interactive session will give you an inside look at: 🔍 Who this course is for 💼 What you will learn 🤖 How it stands out from other AI programs 📅 How to enroll in the next cohort This webinar is your chance to: - Engage directly with an MIT expert - Get a sneak peek into one of the top AI courses available - Participate in a live Q&A If you're a professional looking to harness the power of AI for innovation, you don't want to miss this! 🔗 Register here: MIT Generative AI Webinar https://lnkd.in/dDhyzwZ9 P.S. If you know someone who would benefit from this, don’t forget to share! ♻️

Last week I visited the Design, Automation and Test in Europe Conference (DATE) conference, and of course I wrote some thoughts about it: what the most interesting (for me) papers and keynotes were, and which topics were covered in general. I published it at Towards AI, check it out if you are interested! #conference #ai #computerscience

Congrats Amir on winning the best poster award on Human-Centred AI systems at the AI PhD Poster Event 2024! Amir is conducting his PhD research at the AiBLE lab under the supervision of Catholijn Jonker, Tong Wang Ph.D. and myself. His research focuses on hybrid (human + AI) methods to assist moderators in facilitating reflective deliberation on societal challenges, such as the energy transition. Check out the video for more details!

Embark on a journey through the intricate world of Geometric Graph Neural Networks (GNNs) for 3D atomic systems with our opinionated paper! 🌐🔍 Authored by a team from Mila, University of Cambridge, Intel Labs, Qualcomm AI Research, and more, this work delves into recent advances in computational modeling of atomic systems. Explore how geometric graphs, representing molecules, proteins, and materials, leverage the inherent physical symmetries of 3D atomic systems. Discover the power of Geometric GNNs, driving applications from protein structure prediction to molecular simulations and material generation. 🧪🔬 In this comprehensive paper, we provide a self-contained overview, introducing a pedagogical taxonomy of Geometric GNN architectures, including invariant networks, equivariant networks in Cartesian and spherical basis, and unconstrained networks. 📚💡 Uncover key datasets, application areas, and future research directions, making this work a valuable resource for newcomers and practitioners alike. Join us in unraveling the complexities of this fascinating field! 🚀 #GeometricGNNs #AtomicSystems #ComputationalModeling #MachineLearning #Innovation #Research #Mila #UniversityofCambridge #IntelLabs #QualcommAIResearch More Contents: Woongsik Dr. Su, MBA

🚀 𝐑𝐞𝐯𝐨𝐥𝐮𝐭𝐢𝐨𝐧𝐢𝐳𝐢𝐧𝐠 𝐂𝐨𝐦𝐩𝐮𝐭𝐢𝐧𝐠 𝐰𝐢𝐭𝐡 𝐍𝐞𝐮𝐫𝐨𝐦𝐨𝐫𝐩𝐡𝐢𝐜 𝐓𝐞𝐜𝐡𝐧𝐨𝐥𝐨𝐠𝐲! 🧠💻 Exciting developments from researchers at the University of Limerick have led to innovative molecules that mimic human brain processes, promising to transform computing. Their findings, published in Nature, reveal a new architecture achieving unprecedented computational speed and energy efficiency. Discover how these breakthroughs could reshape the landscape of AI and digital technology! https://lnkd.in/eScZcRyc 🔗 Read more about this groundbreaking research! #Innovation #AI #NeuromorphicComputing #SustainableTech #Research

Why AI-generated audio is so hard to detect NBC News, February 4 Neil Zhang, a PhD student in the Department of Electrical and Computer Engineering at the University of Rochester, said it’s difficult to assess how well specific detection tools in the space work given the lack of existing benchmarks, but that the options out there are “better than nothing.” “There’s a huge disparity in funding between companies racing to make passable deepfakes versus those trying to detect them,” says Zhang. “It’s hard to get funding for detection, very easy to get funding for large-language models and generative AI.” #artificialintelligence #aitools #deepfakes #generativeai

LLMs ARE NICE, BUT WHAT UNDERLIES THEM? SCIENCE, ENGINEERING & CONTROL THEORY The engineering sciences are undergoing a revolution that is aided by machine learning and AI algorithms. Engineers, scientists and mathematicians are making big strides to integrate fundamental developments in AI with applications in critical and emerging technological applications.

We are thrilled to announce that Professor Nicola Marchetti will be delivering a series of IEEE IEEE Communications Society Distinguished Lectures at some of the most prestigious universities and venues across the United States this month. Professor Marchetti, a leading researcher in Complex Networks, Mathematics for Communications & Computing, Network Resource Allocation, and Signal Processing for Communications, will be sharing his insights and innovative research on topics such as Artificial Intelligence, Machine Learning, Future Mobile Networks and lots more. Lecture Schedule: - Wed 16 Oct, University of Massachusetts Amherst Talk "AI is more than Machine Learning - Alternative Computational Methods for Future Networks" - Fri 18 Oct, Virginia Tech at Arlington Talk "More is different: Complex Systems and AI inspiring Future Autonomous Networks and Industry 5.0" - Sat 19 Oct, Washington DC ComSoc chapter Talk "AI, Game Theoretical and Quantum Aspects of Future Networks" - Mon 21 Oct, Northeastern University at Boston Talk "AI is more than Machine Learning - Alternative Computational Methods for Future Networks" Find out more here: https://bit.ly/4dG94CW #Engineering #Innovation #FutureNetworks #AI #ElectronicEngineering

What an accumen; very unique AI application

MIT CSAIL researchers developed an AI-driven approach to “low-discrepancy sampling,” a method that improves simulation accuracy by distributing data points more uniformly across space. A key novelty lies in using graph neural networks (GNNs), which allow points to “communicate” and self-optimize for better uniformity. Their approach marks a pivotal enhancement for simulations in fields like robotics, finance, and computational science, particularly in handling complex, multidimensional problems critical for accurate simulations and numerical computations. Check out the full article here: https://lnkd.in/ezYK7yW9 Image/video credits: MIT Computer Science and Artificial Intelligence Laboratory (CSAIL)