1. The analogy between Artificial neural networks and the Human Brain is resulting in the rise of new technologies -
The analogy between Artificial neural networks and the human brain has been a controversial topic ever since. Some neuroscientists and engineers believe that the analogy exists while many don't. And the reason why some think that it doesn't is that our brain neurons are relatively more complex in structure and functioning than a deep neural network. To date, it has not been confirmed that it works the same, but again we invent what we imagine. Our receptors sense the surrounding information and send it to the neurons, the neurons process it, and then our Brain knows what message was. A neuron in the Deep Neural Network works similarly; it takes inputs, the process of computation takes place, there is an activation function, and thus, a single output is generated, taking into consideration multiple inputs. Though the debate exists, the analogy is important because we humans always try to do the impossible. Recently it was in the news all over the world that Microsoft has invested 1 billion dollars in Elon musk's OpenAI, where they are trying to duplicate the Human Brain. This has given rise to many emerging technologies like Computational Neuroscience, Brain Pathway Duplication, Convolutional Neural Networks, Robotics, and the list goes on. Open AI's Brain duplication itself is a new Emerging Technology.
2. Analogy Between philosophy and History with machine learning -
A research scholar of Stanford University, Adrienne Mayor, has written about ancient Robots and the use of Artificial Intelligence in her book 'Gods and Robots: Myths, Machines, and Ancient Dreams of Technology.' Many scientists like her believe that Artificial Intelligence and Machine Learning were always a part of our ancient culture. It was believed that Leonardo da Vinci was centuries ahead of his time concerning technology. Emerging Technologies being discovered today have already been discovered by our people back in History. If one analyzes Human History with reasonable accuracy, it will prove that human intelligence and artificial intelligence are more alike than we think.
Moreover, Deep learning technology has been used to read and translate ancient manuscripts, which would take years for human resources to do the same. In simple words, philosophy is our idea, and it's what human intelligence can think and imagine. Humans have this tendency to give life to something they imagine and believe in. This new Emerging Technology called the Philosophy of Artificial Intelligence is something to ponder. If one trains a machine learning model with philosophies of great Humans in History, the machine can itself create some new philosophy of his own.
3. Applications of Deep Learning and Image Processing in Archaeology and Oceanography-
Deep Learning for Archaeological Object Detection in Airborne Laser Scanning Data is an Emerging Technology that uses a pre-trained VGG16 algorithm, a deep convolutional neural network for object recognition. Archaeological objects can be easily detected by this method with a simple two-step approach. A computer scientist named Iris Kramer has explained that if Deep Learning Technology can be used for self-driven cars, it can be used for Archaeology. Today Archaeological sites are discovered easily with the help of Artificial Intelligence and remote sensing technology. Moreover, tremendous progress has been made in underwater image processing Technology. Underwater image processing is quite tricky for obvious reasons, including light transmission, which degrades the image quality. Today with advancements in Deep learning, underwater image processing has become a whole new Emerging Technology. Machine Learning has also helped extensively in the advancement of Oceanography. Oil spill mapping and detection, Satellite image processing for land use, Retrieve ocean surface chlorophyll concentration, Habitat modelling these all problems are solved by a simple Support Vector Machine(SVM) algorithm. Quickly detect hazardous weather and detection of whale acoustics are done with the help of Reinforcement Learning. Deep learning has also dramatically helped wave modelling, Coastal water monitoring, and prediction of coastal morphologic properties.