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How AI is changing enterprise applications?
AI applications have changed the way we use computing services and every aspect of our computing behavior has been influenced by machine-learning algorithms that remember everything from our choices in music subscription services, to our desired merchandise in online shopping. Businesses can also leverage AI to predict system failures by recognizing the patterns in which they occur through AI-based business intelligence software. This type of application can be an AI program that monitors business activities and alerts businesses when and where a problem arises.
Similar use cases are also applicable in online security, where firewalls and intruder detection systems have been enhanced by machine learning and the pattern recognition capabilities of AI-based firewalls.
AI-based technologies are gaining mindshare among corporate enterprises around the world.Incorporating AI and machine learning capabilities in enterprise software automates employees’ everyday tasks and enables them to invest their time performing higher value assignments.
AI continues to push enterprise computing to achieve superhuman capabilities. The processing of large amounts of data in parallel computing, while using big data for pattern recognition or performing real-time tasks, requires on-demand communications between AI systems and data. And as more data is being produced, enterprises are accessing AI-based cloud computing systems that are capable of processing data in larger amounts, needing greater interconnection between the data, analytics and AI systems
The role of integrated interconnection in AI, machine learning and the IoT
By applying the analytic capabilities of AI to data collected by the IoT, companies can identify and understand patterns and make more informed business decisions. This leads to a variety of benefits for both companies and their customers such as proactive intervention, intelligent automation and highly personalized shopping experiences. It also enables us to find ways for connected devices to work better together and make these systems easier to use.
While IoT is impressive, it doesn’t amount to much without a good AI system and on-demand access to it. Both AI and IoT technologies need to reach the same level of development and a higher level of private interconnection in order to function as perfectly as possible. Integrating AI into IoT networks is becoming a prerequisite for success in today’s IoT-based digital ecosystems. So businesses must move rapidly to identify how they’ll drive value from combining AI, IoT and interconnection—or face playing catch-up in years to come.
At GpsyPro , we believe that the ability to directly and securely interconnect companies and privately exchange data is the way of the future for all businesses. This especially pertains to those companies that need to leverage AI, ML and the IoT to be viable in today’s global digital economy.
In the future, we expect that the AI/ML trend will continue in all industries as more companies collaborate and leverage integrated interconnection hubs and colocation data centers as a unifying, worldwide platform for innovation. GpsyPro and its Global Solutions Architects support the development of current- and future-state AI/machine learning-based IoT architectures, business processes and data procurement.
