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Digging into the Surface of Artificial Intelligence
- Artificial Intelligence has become an improvising field after its initial development that started in mid-90s and gained fame in 2010.
- Machine Learning is a term used in AI that implies training machines to work autonomously in certain environments with minimum human intervention.
- To train Machine Learning models, a vast set of well-processed (structured) data are required. Machines are programmed to self-learn from their experience to get precise outcomes.
- Neural Networks use Networks to resemble the neuron network of a human brain to do complex tasks in an easier manner.
- Deep Learning uses various hidden layers to perform even more complex tasks in a much more efficient manner. The number of hidden layers represents the depth of Neural Networks.
- AI can be used in various technologies that are being used in our day-to-day lives, including facial recognition, virtual personal assistants, and fraud detection.
- Deep Learning models are more efficient in processing vast datasets than Machine Learning algorithms. However, certain tasks can be performed more efficiently by machine learning methodologies than deep learning models.
- In the future, advanced and well-trained Artificial Intelligence models will perform crucial tasks in constrained environments where humans cannot sustain normally, like space research and nuclear power plant works.
- Neurocomputing asserts that Artificial Intelligence without restriction surpasses human intelligence with probability one and Artificial Intelligence can reveal secrets of the brain.
- Machine Learning and Artificial Intelligence technology are evolving, making it possible to perform even more complex tasks where human negligence or minor errors can lead to catastrophic events.
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