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Audio-Powered Robots: A New Frontier in AI Development

Unite.AI

Audio integration in robotics marks a significant advancement in Artificial Intelligence (AI). Imagine robots that can navigate and interact with their surroundings by both seeing and hearing. Audio-powered robots are making this possible, enhancing their ability to perform tasks more efficiently and intuitively.

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New Neural Model Enables AI-to-AI Linguistic Communication

Unite.AI

This development opens up unprecedented possibilities in AI, particularly in the realm of human-AI interaction and robotics, where effective communication is crucial. Central to this advancement in NLP is the development of artificial neural networks, which draw inspiration from the biological neurons in the human brain.

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Harvard Neuroscientists and Google DeepMind Create Artificial Brain in Virtual Rat

Unite.AI

Graduate student Diego Aldarondo collaborated with DeepMind researchers to train an artificial neural network (ANN) , which serves as the virtual brain, using the powerful machine learning technique deep reinforcement learning. This breakthrough could also pave the way for engineering more advanced robotic control systems.

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Understanding the Artificial Neural Networks ANNs

Marktechpost

Artificial Neural Networks (ANNs) have become one of the most transformative technologies in the field of artificial intelligence (AI). Artificial Neural Networks are computational systems inspired by the human brain’s structure and functionality. How Do Artificial Neural Networks Work?

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An Overview of Three Prominent Systems for Graph Neural Network-based Motion Planning

Marktechpost

Graph Neural Network (GNN)–based motion planning has emerged as a promising approach in robotic systems for its efficiency in pathfinding and navigation tasks. Experiments: 2D Maze to 14D Dual KUKA Robotic Arm: GraphMP significantly improved path quality and planning speed over existing planners.

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Enhancing AI-Powered Computer Vision Through Physics-Awareness

Unite.AI

The study, published in Nature Machine Intelligence , proposes a groundbreaking hybrid methodology aimed at refining how AI-based machinery senses, interacts, and reacts to its environment in real-time—critical for autonomous vehicles and precision-action robots.

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Revolutionizing Robotic Surgery with Neural Networks: Overcoming Catastrophic Forgetting through Privacy-Preserving Continual Learning in Semantic Segmentation

Marktechpost

Deep Neural Networks (DNNs) excel in enhancing surgical precision through semantic segmentation and accurately identifying robotic instruments and tissues. This limitation underscores the need for innovative solutions to ensure continual learning and data management in robot-assisted surgery.