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Liquid Neural Networks: Definition, Applications, & Challenges

Unite.AI

A neural network (NN) is a machine learning algorithm that imitates the human brain's structure and operational capabilities to recognize patterns from training data. Despite being a powerful AI tool, neural networks have certain limitations, such as: They require a substantial amount of labeled training data.

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Inductive biases of neural network modularity in spatial navigation

ML @ CMU

Motivation Despite the tremendous success of AI in recent years, it remains true that even when trained on the same data, the brain outperforms AI in many tasks, particularly in terms of fast in-distribution learning and zero-shot generalization to unseen data. In the emerging field of neuroAI ( Zador et al.,

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Why Do Neural Networks Hallucinate (And What Are Experts Doing About It)?

Towards AI

Last Updated on November 11, 2024 by Editorial Team Author(s): Vitaly Kukharenko Originally published on Towards AI. AI hallucinations are a strange and sometimes worrying phenomenon. They happen when an AI, like ChatGPT, generates responses that sound real but are actually wrong or misleading. Image by Freepik Premium.

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XElemNet: A Machine Learning Framework that Applies a Suite of Explainable AI (XAI) for Deep Neural Networks in Materials Science

Marktechpost

However, explainability is an issue as they are ‘black boxes,’ so to say, hiding their inner working. It elicits the need to design models that allow researchers to understand how AI predictions are achieved so they can trust them in decisions involving materials discovery. Check out the Paper.

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Bayesian State-Space Neural Networks (BSSNN): A Novel Framework for Interpretable and Probabilistic Neural Models

Towards AI

Last Updated on January 20, 2025 by Editorial Team Author(s): Shenggang Li Originally published on Towards AI. Integrating Bayesian Theory, State-Space Dynamics, and Neural Network Structures for Enhanced Probabilistic Forecasting This member-only story is on us. Join thousands of data leaders on the AI newsletter.

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MIT’s AI Agents Pioneer Interpretability in AI Research

Analytics Vidhya

In a groundbreaking development, researchers from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) have introduced a novel method leveraging artificial intelligence (AI) agents to automate the explanation of intricate neural networks.

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Ericsson launches Cognitive Labs to pioneer telecoms AI research

AI News

Ericsson has launched Cognitive Labs, a research-driven initiative dedicated to advancing AI for telecoms. Operating virtually rather than from a single physical base, Cognitive Labs will explore AI technologies such as Graph Neural Networks (GNNs), Active Learning, and Large-Scale Language Models (LLMs).