According to IBM India, Cloud Computing is the process of delivering on-demand computing services over the internet via online infrastructure. In recent years, cloud computing has become the norm of delivering IT services, largely thanks to the increasing demand for speed, agility, flexibility, and security. Businesses are ready to “pay for what they use” to Cloud providers even as they cut down on Cloud Management and supervision teams that would have cost them millions of rupees in hiring and salaries.
Deep Learning has come to be closely associated with the tremendous volume of innovation and development that has happened in the Cloud business. Led by the global Cloud service providers such as Amazon Web Services (AWS), IBM, SAP, Red Hat, and Microsoft Azure, Cloud Computing is helping businesses extract greater value from their data — text, files, sound, video, voice, and so on.
Changing Computing Objectives
According to AWS, Deep Learning is the scientific application of using machines to simulate human brain activities to create an artificial ‘neural network’. A collection of these neural networks can be used to process and extract analytics and insights for relevant actions by binding them through relationships and patterns based on data. Deep Learning training in Cloud computing has the potential to super-accelerate the rate of adoption and deployment of various IT systems, which directly result in lowering the cost of computing, storage, and security overheads.
Deep Learning tools such as Apache, TensorFlow, Keras, and Caffe are used extensively in Cloud Computing DevOps. These tools are ideally suited to the growing number of applications arising from the hotbeds of innovation in Artificial Intelligence, Machine Learning, Robotic Process Automation, Cybersecurity, Data Mining, and Crypto-based Encryption techniques.
How Fast is the Deep Learning Tactic Changing?
At a supersonic pace…!
In the last 5 years, every internet-based business has either adopted a Cloud platform or is planning to do it in the next 6 months to ensure the scalability and sustainability of its various operations. Increased demand for customer data management, call analytics from contact centers, and customer support expansion has put immense pressure on the existing IT infrastructures, most failing to reach their potential due to lack of internet accessibility. With Cloud Computing, all services and processes have moved to the internet– the safest place to work provided the security framework is in place.
That’s where concepts like Deep Learning and Embedded Analytics come to picture– securing the IT components and Internet Business processes under rules of governance, compliance, and access management.
If the first half of Deep Learning Cloud computing pair was about developing and integrating IaaS, DaaS, PaaS, and SaaS, the next half would be about letting AI and Machine Ops take over the on-demand and self-service automation systems.