Facebook CEO Mark Zuckerberg says machine learning-fuelled artificial intelligence will help to match and surpass human capacities in the field of computer vision and speech recognition within nearly five to ten years. Most of the huge companies like Facebook uses machine learning to analyze their huge data and provide better services to their client. Here the algorithm works in the background to recommend new connections to Facebook users that match the user’s interest and to block spam.
Nowadays organizations are beginning to use machine learning for further advanced applications such as for facial recognition on pictures presented on the website and also identify individual photography, the new moment’s application can recommend to the user that she/he shares with that particular individual.
Recent research where a group of researchers from different German companies and colleges highlighted the difficulties of using deep learning in the processing of visual data. In their paper “ The Notorious the difficulties of comparing human and machine perception “showed the issues in the current method that compared neural networks and the human visual system. This study showed a series of examinations that dig underneath the surface of deep learning results and it compares it with the operations of the human visual framework.
Making machines that can think and act like humans have been evolved like film fiction to real-world facts. Bots, humanoids, robots, and digital people facilitate with us in so many ways. Looking at the AI-driven applications has a higher speed of execution, have higher operational capacity and precision while it has disadvantage such as in exceptionally critical in dull and monotonous job comparing the humans. Human intelligence doesn’t depend upon pre-fed data like the AI, they relate to adaptive learning and experience. Even though AI is being an important device and intelligent work process will also be the labor-saving process within a few years.
Deep learning which is a subset of AI uses the idea of neural networks just like the nervous system present in the human brains. Human intelligence lies in adaptive learning and how to apply the real-world situation whereas deep learning copy the ability of the human brains to learn in various stages. Comparing neural networks to human perceptions is a great challenge. Deep learning frameworks have complex functions that additionally intensify the issues and deep neural networks work in a twisted way that mostly confuses the maker.
Since AI is in the advancement stage the future generally lies in how people govern AI applications with the goal that they maintain the human values and security measures. When the AI framework becomes more intricate it must be tested with a more complex method. The main challenge in comparing human and machine in studies is by all means the strong internal human interpretation bias. Hence care must be taken when comparing human and machine perception.