It has always been an area of challenge for humans to create machines in order to outperform human capabilities in terms of workload, effectiveness, precision, endurance, strength, repetitiveness etc. It is a way to transcend the existence and to give more sense to life which is precious. The common denominator of all these creations was that they were meant to replace, enhance or go beyond the mechanical capabilities of human body. This path of evolution is smooth and predictable. This story takes a different shift or another bifurcation to be more precise when Alan Turing introduced the concept of a machine that could achieve human level performance in thinking. This point of view was reinforced by Norbert Wiener who introduced the feedback. But the revolution began with the computational model for neural networks with Warren McCulloch and Walter Pitts and this time the evolution is unpredictable. In mathematical terms, the network forms a directed, weight graph. Artificial Neural Network started at first level as an attempt to exploit the architecture of the human brain to perform tasks that conventional algorithms had little success with. Artificial intelligence is the term used to describe the use of computers and technology to simulate intelligent behavior and critical thinking comparable to a human being. John McCarthy first described the term AI as the science and engineering of making intelligent machines. Ng and Dean created a network that learned to recognize higher-level concepts. Unsupervised pre-training and increased computing power from GPUs and distributed computing allowed the use of larger and deeper networks, particularly in image and visual recognition problems, which became known as deep learning. And now at high level research we use deep neural networks with TPUs. Now-days the most representative area of thinking machines evolution has been the world of strategy board games. Board games, such as chess, shogi or go, are considered an expression of human intellect at the highest level but Deep Neural Networks as AlphaGo, AlphaGo Master, AlphaGo Zero mastered all those sharp games. The 3D models of proteins that AlphaFold generates are far more accurate than any that have come before marking significant progress on one of the core challenges in biology. ANNs have been used to diagnose cancers, including lung cancer, prostate cancer, colorectal cancer and to distinguish highly invasive cancer cell lines from less invasive lines using only cell shape information. More generally AI was used for diseases diagnosis, drug development, personalized treatment, improved gene editing.