Generative AI, Explainable AI, and Symbolic AI
Among the many branches of AI, Generative AI, Explainable AI, and Symbolic AI each play distinct roles, offering different capabilities and addressing various challenges.
Among the many branches of AI, Generative AI, Explainable AI, and Symbolic AI each play distinct roles, offering different capabilities and addressing various challenges.
Industry 4.0 has become a central theme in modern industrial transformation, becoming a driver of innovation and business growth.
In AI field, you’ll often come across terms like ANN, CNN, and RNN. These acronyms refer to different types of neural networks, each designed for specific kinds of data and tasks
Deep Neural Networks (DNNs) are a subset of artificial neural networks characterized by multiple layers between input and output.
Edge Federated Learning (EFL) addresses the data silo problem by effectively utilizing the vast data generated on end-user devices, all while preserving user privacy.
Federated Learning (FL) has emerged as a powerful and privacy-conscious method for leveraging distributed computing resources to collaboratively train machine learning models.
As research evolve, several types of artificial neural network architectures have emerged, each tailored to specific types of problems and data structures.
Artificial Neural Networks (ANNs) have revolutionized the field of artificial intelligence by mimicking the information processing mechanisms of the human brain. Over the decades,
Artificial Neural Networks (ANNs) have been a prominent area of research in artificial intelligence since the 1980s. Inspired by the structure and function of the human brain, ANNs
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