Currently, Artificial Intelligence (AI) penetrates faster in the tech industry since it has increased the volume of new products and services in an efficient way and the structure of development, production, and delivery seem suitable to the implementation of this cutting-edge technology.
Still, plenty of other businesses and industries have yet to take advantage of the advances in this relatively novel application field. In medicine, energy or manufacturing sector, a more intensive and comprehensive application of AI could dramatically transform these fields while boosting the economic productivity.
Not only AI enters a particular sector, high-tech, also within it only a few major organizations make use of it to create expansion through volume and efficiency at unbelievable higher speed.
Companies like Google, Amazon, Microsoft, Baidu and some startups engage AI in their matrix since it may be acceptable price-wise, while for the most part and all the rest of our economy, this novel technology proves difficult to implement and extremely costly.
Therefore, companies like Amazon, Microsoft, and Google aim to create cloud-based AI to make the technology cheaper to be implemented and used effortlessly. This leading-edge cloud-based AI is available now and by expanding it to lots of organizations it could trigger more economic development. The solution is to bring AI and cloud-based machine-learning tools to large audiences.
In this pursuit, Microsoft has Azure, its own cloud platform and by cooperating with Amazon they are working to offer an open-source machine learning library called Gluon. This is created to engage in building neural nets to become a core AI technology to copy and apply the processes of learning exposed by the human brain.
Although at this time, Amazon dominates cloud machine learning with AWS, Google is following suit with an open-source AI library named TensorFlow. This library proves powerful since it can develop and build further machine-learning software.
Also, on the designers’ table a priority represents the simpler use and implementation of AI, and the recent Google pre-trained system suit Cloud AutoML, promises to do just that. Both organizations start preparing consulting services to cover the shortage of cloud-based AI specialists who can spread the knowledge of the leading-edge AI.
The future will tell who is going to spread more and what quality of AI. It certainly represents a huge business opportunity for those involved. The cloud-based AI technology has great chances to expand and comprehend various sectors untouched so far. We can only realize the true benefits… and the downsides of AI once the cloud-based is ready to roll and found at almost everyone’s fingertips.
Author: Cory Popescu