Mitsubishi Electric Research Laboratories’ Post

The words ‘what if?’ can prompt thoughts about a seemingly infinite spectrum of possibilities 💡 Known as counterfactual reasoning, this process is innate to humans — but what if we could teach AI systems to do this too? Scientists at the Institute for Infocomm Research (I²R) and the Centre for Frontier AI Research (CFAR) have built a new framework using structural causal models (SCM), which enables AI to predict how things would have evolved differently if certain conditions or events differed from what actually happened. “This new formulation not only quantifies relevance and dissimilarity in counterfactual reasoning but also lays the groundwork for integrating such reasoning into deep neural networks,” explained first author and A*STAR Scientist Yanzhu Liu. See their research in action by checking out the article linked below ⬇️ --- #scicomm #science #technology #STEM #research #innovation #ASTAR #SNDE #CFAR #I2R #neuralnetwork #machinelearning #artificialintelligence #computerscience #reasoning

🚀 Exciting News Alert! 🚀 🌟 Introducing the revolutionary Quantum Neural Network! 🌟 🔍 In today's ever-evolving technological landscape, staying ahead means embracing innovation. That's why I'm thrilled to share the latest breakthrough in artificial intelligence: the Quantum Neural Network (QNN)! 🔹 What is the Quantum Neural Network? It's not just a product; it's a paradigm shift in AI architecture. By harnessing the power of quantum computing and neural networks, QNN unlocks unparalleled processing capabilities and unlocks new frontiers in machine learning. 🔹 Why does it matter? QNN isn't just about pushing the boundaries of AI; it's about solving complex problems faster and more efficiently than ever before. From data analysis to pattern recognition, QNN empowers organizations to make smarter decisions and drive innovation. 🔹 How can you get involved? Stay tuned for upcoming workshops, seminars, and opportunities to explore QNN's potential firsthand. Whether you're in finance, healthcare, or manufacturing, QNN has the potential to revolutionize your industry. Are you ready to embrace the future of AI? Let's connect and explore how Quantum Neural Network can elevate your organization's capabilities! 💼✨ #Innovation #AI #QuantumComputing #isamm #développement

This video introduces Temporal Event-based Neural Networks (TENNs) — lightweight, energy-efficient neural networks that excel at processing spatiotemporal data. TENNs work in tandem with BrainChip Akida platform to process multidimensional events and perform compute-heavy tasks on devices with limited memory, battery, and computational resources. Learn more: https://wevlv.co/3Rd7kIZ #engineering #technology #neuralnetworks #brainchip #ai #artificialintelligence

🔬 Summary: A lightweight neural network model called GMSNet is proposed for intelligent mesh smoothing. GMSNet uses graph neural networks to extract features of node neighbors and output optimal node positions. It addresses the challenge of smoothing mesh nodes with varying degrees and eliminates the need for high-quality meshes through a novel loss function called MetricLoss. Experimental results demonstrate that GMSNet outperforms traditional mesh smoothing methods with significantly fewer parameters and faster processing. 🔑 Takeaway: GMSNet offers a more efficient and effective approach to mesh smoothing in Computational Fluid Dynamics (CFD), achieving exceptional performance with fewer parameters and faster processing. This can lead to high-precision numerical simulations in various applications. #AI #MachineLearning #DeepLearning #ComputerVision #CFD #GMSNet [Note: The hashtags can be tailored further depending on your specific focus and target audience.]

The world of Artificial Intelligence (AI) is developing rapidly, and the mathematical foundations, applications, and implications need to be closely monitored. Nadav Cohen, assistant professor of computer sciences at Tel Aviv University, research director at the university’s foundation of Deep Learning Lab, and chief scientist and co-founder of Imubit delves into the current developments and challenges of AI. 🔗 Episode linked in the comments. #TAU #AI #theglobalconnectionpodcast

...Yoshua Bengio...et al. Scientific discovery in the age of artificial intelligence, Nature 620, 47–60 (2023). Authors mentioned key applications of AI...like battery design optimization, planning chemical synthesis pathway, high-throughput virtual screening, etc. A must-read article. #AI #MachineLearning #Battery

Quantum computing and AI are set to have major impacts on science and society: https://ow.ly/Wc0550QWyh6 Stephen Wolfram, the innovator behind Mathematica, Wolfram|Alpha, and the Wolfram Language, says AI and machine learning tools are useful to apply to research and will open up new areas to explore, but won't "solve science." What else does Wolfram see for the future of research? Find out in this #DiscoverOptica blog! Pictured: Stephen Wolfram (right) with Optica President Gerd Leuchs (left) and Optica Fellow Luis L. Sanchez (center). #quantum #ai #machinelearning

Please join our Chief Scientific Officer, Muhammad Firmansyah Kasim, in Vienna from May 7th - 11th at the Twelfth International Conference on Learning Representations. This premier gathering of professionals is dedicated to the advancement of the branch of artificial intelligence called representation learning. On May 10th, Muhammad will present new research in parallelizing recurrent neural network (RNN). In this latest research, it's shown that RNN can be efficiently parallelized in a GPU, achieving up to 1000x speed up over a traditionally sequential method. If you would like to know more about parallelizing RNN or other work in general, visit our booth at poster session 8. Register here: https://iclr.cc/ ICLR #MachineLearning #AI #SequentialModels #NeuralNetworks #DeepLearning

Scientists have found a way to use artificial intelligence and WiFi signals to recognize people in a building, just like James Bond. A team at Carnegie Mellon University created a deep neural network that can map human bodies using WiFi signals. The researchers developed this technology to overcome the limitations of current 2D and 3D computer vision tools. In a study, they explained that their model can accurately estimate the positions of multiple people using only WiFi signals. They hope that this breakthrough will lead to affordable, widely available, and privacy-friendly algorithms for detecting humans. #ai #innovation #withoutlimits #businessbulls.in