Article | February 28, 2020
Think of a time, when you have used a map to find a café for your family dinner. Or perhaps, you used it to look for a newly opened fashion store in your neighborhood. Working with location technology day in and out, I am fascinated by the journey of maps- from paper to a tap on the phone. I have never been more energized by the growth of these location technologies having an impact on our daily lives, the way we work and interact. The beauty of maps, however, is that they can be used in a variety of forms, beyond just navigating roads and finding landmark buildings. Location mapping and technologies, as companies are now finding out, is helping businesses small and large across the world, to combine geography with business intelligence, thus enabling them to make faster and efficient business decisions.
Article | June 7, 2021
The way we architect and build applications has changed over the last decade or so. Where monoliths (or single, large codebases) used to be the standard, modern applications are now built using a combination of new architecture patterns, operational models, and software delivery services. By shifting to a microservices architecture, teams can more easily update, replace, and innovate on small, modular codebases—driving faster business innovation while reducing risk, time to market, and total cost of ownership.
This modular microservices approach has spurred the use of containers as a lightweight, portable solution to the infrastructure needs garnered by these loosely coupled services. As such, containers have largely become the centerpiece of automation and DevOps in the enterprise. This gives teams the ability to capitalize on the flexibility and scalability offered by the use of containers, but it also means more moving parts and more perimeters to manage. Kubernetes has emerged as the gold standard for handling container orchestration.
Article | September 8, 2021
We live in the modern era of Artificial Intelligence (AI), where machines replicate human behavior. As a result, it is capable of performing many functions that are attributed to humans. According to Statista, the global AI market would reach USD 89 billion annually by 2025. The credit of the overall growth goes to the integration of cloud computing in artificial intelligence.
The customized merger of these two modern technology domains has enhanced the lives of millions. In fact, in our daily life, we often use artificial intelligence when we command cloud-based digital assistants such as Siri, or Alexa, ask for directions on our phones, or get real-time traffic alerts on our GPS.
Cloud Computing and Artificial Intelligence- An Overview
With such an impactful collaboration, businesses are set to achieve rapid digital transformation to live up to the competitive edge. But before we ponder upon the business benefits of cloud computing and artificial intelligence integration, let us have a generic synopsis of both technologies.
Cloud computing provides computing services for system resources (servers), cloud storage, databases, networking, applications, analytics, and intelligence, as and when required by the user. It assists you to share the resources, accelerate innovation, manage your infrastructure efficiently, scale with your business demands and optimize your capital expense by paying only for cloud services that you use.
Artificial Intelligence, widely known as AI, is the induced virtual intelligence in machines to make them capable with intellectual powers similar to humans. The AI technology enables machines to think logically, learn from past activities, ascertain the meaning, and simplify actions. Artificial Intelligence has several applications such as text analytics, expert systems, machine language translation, speech recognition, natural language processing, sentiment analysis, and many more.
How Does the Collaboration of Cloud Computing and Artificial Intelligence Help a Business?
According to a study by McKinsey, across 19 different business domains and above 400 use cases, AI could create USD 3.5 trillion and USD 5.8 trillion per year in value. In addition, AI teaming up with the cloud computing environment makes organizations efficient, tactical, and insight-driven.
Following are the vital four advantages of cloud computing and AI collaboration.
Performs Data Mining and Analytics
Cloud stores disparate data, which needs sorting and analysis to derive their hidden narratives. Artificial intelligence runs analytics to process the data, identify the pattern and determine the predictive algorithm to extract useful information. This process is known as data mining. Further, AI helps you to manage core workflows by leveraging cloud efficiency to ease out transactional processes. The integration of cloud computing with artificial intelligence supports your business in data management, determine actionable insights, deliver customer services, and augment workflows. Moreover, it equips you with accurate insights as there is no scope for human-interceded errors.
Cloud Security in Real-Time
Cloud Security in itself is a vast topic that engages expert’s bandwidth. However, its link with the role of AI in cloud computing recognizes its capability to detect anomalies while processing the large amount of data stored in the cloud. It can instantaneously provide an alert in real-time. Additionally, AI can also identify unauthorized attempts to access any network and helps you to block them promptly.
Allows Unhindered Data Access and Improves Decision-Making Capabilities
The merger of AI in cloud computing can help you avert complications related to data inaccessibility and boost your overall performance. Further, the combination helps you to mitigate potential risks in your cloud environment well in advance. As a result, it enables you to make the right decision for your business. Further, AI can facilitate seamless data transfer between on-prem and cloud environments.
Maintains Cost-effectiveness and Improves Productivity
The combination of cloud computing and AI intends to reduce overall costs. The merger helps you control the cost of implementing Artificial Intelligence in your business ecosystem because you don’t have to set up a separate data center. As a result, AI applications can significantly save capital expense concerning expenditure on arrangements for infrastructure. Further, it reduces the cost incurred due to manual operations and saves time to enhance your business productivity.
According to a recent conversation with Media 7, James Lee, Managing Director and Head of Financial Services, Analytics and Cloud Transformation at PwC, said, “A secure cloud data platform is fundamental to every successful digital transformation.” In the present competitive era, businesses are constantly looking for innovative solutions to secure their data, ensure their overall development. Cloud computing and artificial intelligence are advanced combinations to capture market attention and make a global presence. It helps you automate your processes, secure your operational data and network, control cost, boost your productivity and get accurate insights for better decision-making.
Frequently Asked Questions
What is the Use of AI in Cloud Computing?
Businesses use AI-driven cloud computing to perform efficiently, plan effectively to extract data-driven insights. AI helps to simplify complex and redundant operations to improve productivity, perform analytics without any manual effort.
Which are the Best Cloud Platforms for AI?
Some of the best cloud platforms for AI are as follows:
Google Cloud Machine Learning Engine
Amazon ML platform services
INTEL Nervana Platform
Salesforce Einstein suite
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"text": "Businesses use AI-driven cloud computing to perform efficiently, plan effectively to extract data-driven insights. AI helps to simplify complex and redundant operations to improve productivity, perform analytics without any manual effort."
"name": "Which are the Best Cloud Platforms for AI?",
"text": "Some of the best cloud platforms for AI are as follows:
Google Cloud Machine Learning Engine
Amazon ML platform services
INTEL Nervana Platform
Salesforce Einstein suite"
Article | April 7, 2020
New capabilities include the ability to define and apply cybersecurity policies to continuous integration (CI) and continuous delivery (CD) workflows and scanning tools for discovering misconfigurations in cloud infrastructure templates, which is the most common source of cloud security issues.Palo Alto Networks has also added the ability to scan virtual machines native to the Amazon Web Services (AWS) before they are deployed as well as an ability to apply policies to workloads running on the AWS Lambda serverless computing framework via a single click. That capability eliminates the need to manually install wrappers in application code running on the AWS Lambda framework.