Raspberry Pi Foundation’s Post

Penn Engineers have studied the intricate workings of neural networks, shedding light on why today's AI systems excel. Their groundbreaking study unveils a surprising pattern in how these networks learn. With this newfound understanding, there's incredible potential for hyper-efficient AI training algorithms that demand fewer computational resources. By leveraging information geometry, the researchers leveled the playing field, allowing for a deeper comparison of different networks. Their findings reveal striking similarities in learning strategies, paving the way for more discoveries. Imagine the possibilities! #AI #neuralnetworks #learning https://lnkd.in/gE95P8d9

AI Research at Ohio State University and CMU Explores Implicit Reasoning in Transformers and Achieving Generalization Through Grokking In recent research, scientists from Ohio University and Carnegie Mellon University have investigated the potential of deep learning models, specifically transformers, to engage in implicit reasoning over parametric data. The study delves into the challenges faced by these models, including their struggle to apply and integrate internalized facts accurately, even with awareness of the entities involved. https://is.gd/2L4bs5 #ai #aitechnology #artificialintelligence #grokkingai #llm #machinelearning

I am honored that my paper was accepted! This is the second thesis of my master's research career, but also the first conference paper. I will post a link to my paper. #Deeplearning #AI #ConferencePaper #DomainGeneraliztion #NCKU

Just reviewed a manuscript for Social Science Research (Elsevier) with explicit instructions not to use generative AI, and not too long ago I submitted a manuscript that requires disclosure of any use of AI. I appreciate the attention to this issue in the publication process! #socialscience #academia #academicpublishing #science #research #ai

'Domain Adaptation Speech-to-Text for Low-Resource European Portuguese Using Deep Learning'. Our research explores deep learning techniques in AI, to address language barriers. Read more: [https://lnkd.in/dt8aZQtU] #VISTALab #AI #Research #SpeechRecognition"

Thrilled to share that my PhD student, Omid Davoodi, has successfully defended his doctoral thesis! 🌟 Titled On the Interpretability and Explainability of Prototype-based Methods and Reinforcement Learning, his research delves into crucial aspects of AI transparency and trust, paving the way for more interpretable and explainable AI systems. Congratulations, Omid! 🎉 #AI #Interpretability #Explainability

📢 Exciting news! 🚀 Check out this groundbreaking blog post on Diagonal Linear Networks! 🧠💡 It delves into the incredible potential for incremental learning in DLNs. 📚🔍 The paper, authored by Raphaël Berthier, explores how DLNs, simplified artificial neural networks, leverage quadratic reparametrization of linear regression for sparse implicit regularization. 🤯🔬 Discover how the study demonstrates that incremental learning takes place in DLNs as the coordinates become activated, leading to the loss function minimizer among the active coordinates. 📈✨ The research also showcases that the sparse implicit regularization of DLNs diminishes over time, but with a focus on the underparametrized regime with anti-correlated features due to technical limitations. 📉⌛ Want to unravel the full details? 📚 Dive into the post here: [link](https://ift.tt/G9l3fQH) 🔬 Stay ahead of the curve with the latest insights from InstaDataHelp AI News! 🌐💡 #AI #MachineLearning #DataScience #DLN #IncrementalLearning #Research

Recently, I had a conversation with a philosopher about AI. He was curious about why the most successful AI algorithms are those that model the neural networks of biological brains. Why is that, really? The answer of “the most successful AI algorithm” was the following. The success of neural network algorithms in AI, inspired by the structure of biological brains, can be attributed to their ability to learn and adapt from data in a way that mimics human learning processes. These algorithms excel in recognizing patterns, making decisions, and learning from experience without being explicitly programmed for specific tasks. This bio-inspired approach leverages the complexity and efficiency of biological neural networks, offering a powerful model for developing AI systems capable of handling diverse and complex tasks with remarkable efficiency. #MachineLearning #AI #ArtificialIntelligence #AIAlgorithms #NeuralNetworks #BioInspiredAI #BiologicalInspiration #BeyondArtificial #IntelligenceEvolution #NewEraOfAI #AIPhilosophy

I'm happy to unveil the first milestone in my PhD journey, which began in September of last year: an advancement in Explainable AI (XAI) with our latest research. Our work focuses on enhancing local and model-agnostic explanations for complex neural networks, critical for understanding and trust in AI systems – closely aligned with the motivation of the AI Act by the EU. 🚀 Highlights of Our Research:  - Innovation Through Integration: Leveraging Foundation Models, specifically SAM (Segment Anything), to generate features that align with human cognition. - Hierarchical Approach: Treating segments hierarchically to mirror human reasoning more closely, allowing for concept-relational explanation. - Customizable Explanations: Empower end-users with the ability to define the level of granularity in explanations, making it easier to grasp human-known concepts. 🏆 Key Achievement: Our proposed method, DSEG-LIME, sets a new benchmark in the LIME field by outperforming existing techniques both quantitatively and qualitatively on the ImageNet dataset. This advancement is a leap toward making AI more interpretable and accessible. 📝 Preprint: https://lnkd.in/evBa_Shb 💻 GitHub Repo: https://lnkd.in/e6yhXFvB #AI #PhDJourney #AIAct #ML

Take a look at this week's episode of the Boring AI Show where we talk about the impact of AI on higher education. Emily J. Bailey, Ph.D., Tally Aumiller, and Tim Kulp will discuss this highly debated topic on the next Boring AI Show! We'll explore what Dr. Bailey finds in higher education and some best practices for AI in learning. Friday, March 22 at 11am Click to learn more: https://lnkd.in/eb9wxJjn #TheBoringAIShow #AI #artificialintelligence #highereducation