Artificial intelligence has become a topic which has been gaining interest over the course of time as more and more scientists and physicists are taking an interest in it. Studies in the field require plenty of efforts and most of the time, the best computing platform for all this is the cloud. Cloud services are useful for conducting experiments into artificial intelligence and one of the main factors behind the rapid growth of cloud computing in conjunction with artificial intelligence. Neural networks, for instance, can be modeled and programmed to work on the abundant resources that are provided by the cloud computing platforms and this translates into better forecasts and more accurate predictions of the kind of information that works best and what algorithms are best and more time-saving for such computing endeavors.
With cloud services being the pillar upon which rest the field of artificial intelligence, scientists are finding in increasingly easier to make experiments that rely on huge sets of data and many hours of compute without having to worry about where all these resources will be coming from. Experiments that have been conducted with the use of cloud services have brought about results which have made the progress in this field much easier and the results more tangible. With a huge compute muscle to move the layers and predict the patterns that are generated in the learning networks, any scientist can easily make their venture into the field more profitable and with better results. It is both cheap and fast to get started with an experiment in the cloud and maintaining these efforts does not cost much on the end of the scientist. If the scientist needs to scale up their experiment to take up more compute resources, then they simply need to get more cloud resources allocated to the tasks that are demanding the attention of the cloud resources.
Storage of the results from the artificial intelligence endeavors and generations of source code and programs that are working and showing real progress of the field are stored on the cloud and can be accessed using credentials that are programmed into the application architecture to ensure that only the scientists that are working on the artificial intelligence programs and experiments can really get to gain access into the systems. It also cuts down on the time taken to get results from the programs that are written to run on the cloud and with this reduction in waiting time comes increasingly better versions of the applications and better results which means more tangible products are integrated with the artificial intelligence capabilities as the research goes on. The study of artificial intelligence is also supported by cloud computing in the sense that freedom and time is granted to the programmer to write as many different versions of the programs as possible and ensure that one of the results is applicable to an actual practical working scenario out in the field. The performance pressure of the programmer is eased when they have a working platform and nothing to drag down their performance or stagnate their programming efforts as they turn artificial intelligence into an assistive technology for all other programs.
