What are Some of the Best Practices of Cloud Computing?

December 29, 2020

In simple terms, Cloud Computing is defined as the process of providing software solutions or products to the customers through computing servers over the internet.

In this system, files do not get stored on any local devices. Files are stored on cloud-based storage services like a data center that Google Cloud, Microsoft Azure, and Amazon Web Services(AWS), E2E Cloud use to supply their solutions to their customers on an online basis. These storage devices have access to the internet. Thus, any device which gets connected to the internet can have access to the cloud data, speaking from the customer’s point of view. These cloud-based solutions mainly help to provide efficient and cost-effective services to the majority. Most of these cloud services are subscription-based solutions.

Some vital and eye-catching facts you didn’t know about Cloud Computing:

  1. 90% of companies worldwide have shifted to cloud-computing. source
  2. In 2021, 94% of the computational processes will be done on cloud servers.
  3. The global computing market will exceed 620 million dollars by 2023.
  4. Public cloud services account for almost 41% of the Cloud market share.
  5. An average developer uses around 36 cloud-based services regularly.

Cloud computing emphasizes the remote accessibility of data that it provides to the user. It means that the user is not required to be present in any particular place to get access to the data. The user should possess an active connection to the internet to acquire the data from anywhere in the world.

The most noteworthy feature of the cloud is that the maximum heavy computational tasks are completed by the more powerful and efficient servers and not by the less efficient and less powerful user devices.

From the user’s perspective, these cloud servers can be called virtual machines (VM) since these services provide shared CPU and GPU to process and compute user requests and data. For this reason, both the software development company and the user opt for cloud-based solutions to increase their overall business throughput. The approach towards cloud computing helps to deliver IT resources over the internet with much less cost and power consumption.

Benefits of Cloud Computing

The number of connected devices is increasing in an exponential order day-by-day. More users are being connected over the internet, and similar is the case for growing businesses too. Expected reports claim that by the end of 2020, 67% of industrial infrastructure will work on cloud systems. For such use cases, cloud Computing delivers the most effective solution for growth.

  • Strategic production

A movement under a specific plan makes the journey more easily doable. Unlike some companies, a clear and clarified cloud strategy can work as a valuable practice. Establishing achievable goals, budget with a specific deadline makes it much more convenient. Hence, cutting unnecessary expenses comes from a much easier perspective. So, a preview of the goal can increase productivity up to quite a long extent.

  • Reducing avoidable costs

With the involvement of cloud computing, the cost for maintenance and management of a software system reduces to quite an extent. This is because most of the resources are shared across many devices and are not bound to a single one of them. Energy consumption cost is reduced, and hardware/software upgrades are affordable.

  • The best teacher is the last mistake

A good way to learn about running on the cloud can be the previous examples. The standalone approaches that have been taken before were much economical, as availability was abundant.

  • Autonomous architecture

Implementing cloud architecture with a minimized impression of maintenance resources and development allows focusing on the core business more. The integration of applications requires professional development and understanding of underlying architecture.

  • Concerns about security

Security becomes the primary concern when vast amounts of data are being exchanged globally among developers and users. Around 75% of executives in the industry claim this as the highest concerned issue in Cloud Infrastructure. When any user uploads any file or document in their cloud storage, they are always concerned about the security of the same. Cloud Computing uses real-time encryption of data that is being transmitted and received. With the advent of cloud computing, 94% of businesses claim to have increased security standards.

  • Workload

Cloud architecture involves a rigorous procedure with an expensive economy. Hence, a slow start always seems appreciable. So, despite the lucrative framework, it is good to start with a single workload or single function.

  • Performance

The most important benefits of Cloud Computing services are its performance and accessibility. You have to find out the required integration architecture to design the cloud system. You have to make sure the cloud computing service remains intact irrespective of server fault and other issues.

  • Perspective of connectivity

Cloud Computing had been the source of services for almost everything in the web industry, including SaaS, PaaS, and 2.0 APIs (Google Docs, Twitter, and LinkedIn). According to some research news, the connectivity perspective is the way forward in various applications, databases, and Web 2.0 APIs.

E2E Networks Services

E2E networks is far better in terms of their performance, accessibility, and is a lot cheaper when it comes to the cost of it. Therefore, they have set a benchmark as far as low-cost cloud providing is concerned. They are creating a strong reputation from the end-users because of their scalability, affordability, trustworthiness, and improved and enhanced privacy features.

E2E networks avail very high-performance cloud infrastructure. Their GPU Cloud is appropriate for various applications including Computer Vision, AI, Scientific Research, Computational Finance, and Big Data. It has led E2E to become a World-Class Cloud Computing Service.

Wrapping Up

It is clear that cloud computing is the future, and will, without any uncertainty, remain the leader in nearly all expanse of technology. In this article, you get to know about the best possible practices of cloud computing in India. We have also discussed the benefits of the cloud computing service.

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June 29, 2022

Project Management for AI-ML-DL Projects

Managing a project properly is one of the factors behind its completion and subsequent success. The same can be said for any artificial intelligence (AI)/machine learning (ML)/deep learning (DL) project. Moreover, efficient management in this segment holds even more prominence as it requires continuous testing before delivering the final product.

An efficient project manager will ensure that there is ample time from the concept to the final product so that a client’s requirements are met without any delays and issues.

How is Project Management Done For AI, ML or DL Projects?

As already established, efficient project management is of great importance in AI/ML/DL projects. So, if you are planning to move into this field as a professional, here are some tips –

  • Identifying the problem-

The first step toward managing an AI project is the identification of the problem. What are we trying to solve or what outcome do we desire? AI is a means to receive the outcome that we desire. Multiple solutions are chosen on which AI solutions are built.

  • Testing whether the solution matches the problem-

After the problem has been identified, then testing the solution is done. We try to find out whether we have chosen the right solution for the problem. At this stage, we can ideally understand how to begin with an artificial intelligence or machine learning or deep learning project. We also need to understand whether customers will pay for this solution to the problem.

AI and ML engineers test this problem-solution fit through various techniques such as the traditional lean approach or the product design sprint. These techniques help us by analysing the solution within the deadline easily.

  • Preparing the data and managing it-

If you have a stable customer base for your AI, ML or DL solutions, then begin the project by collecting data and managing it. We begin by segregating the available data into unstructured and structured forms. It is easy to do the division of data in small and medium companies. It is because the amount of data is less. However, other players who own big businesses have large amounts of data to work on. Data engineers use all the tools and techniques to organise and clean up the data.

  • Choosing the algorithm for the problem-

To keep the blog simple, we will try not to mention the technical side of AI algorithms in the content here. There are different types of algorithms which depend on the type of machine learning technique we employ. If it is the supervised learning model, then the classification helps us in labelling the project and the regression helps us predict the quantity. A data engineer can choose from any of the popular algorithms like the Naïve Bayes classification or the random forest algorithm. If the unsupervised learning model is used, then clustering algorithms are used.

  • Training the algorithm-

For training algorithms, one needs to use various AI techniques, which are done through software developed by programmers. While most of the job is done in Python, nowadays, JavaScript, Java, C++ and Julia are also used. So, a developmental team is set up at this stage. These developers make a minimum threshold that is able to generate the necessary statistics to train the algorithm.  

  • Deployment of the project-

After the project is completed, then we come to its deployment. It can either be deployed on a local server or the Cloud. So, data engineers see if the local GPU or the Cloud GPU are in order. And, then they deploy the code along with the required dashboard to view the analytics.

Final Words-

To sum it up, this is a generic overview of how a project management system should work for AI/ML/DL projects. However, a point to keep in mind here is that this is not a universal process. The particulars will alter according to a specific project. 

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June 29, 2022

Top 7 AI & ML start-ups in Telecom Industry in India

With the multiple technological advancements witnessed by India as a country in the last few years, deep learning, machine learning and artificial intelligence have come across as futuristic technologies that will lead to the improved management of data hungry workloads.


The availability of artificial intelligence and machine learning in almost all industries today, including the telecom industry in India, has helped change the way of operational management for many existing businesses and startups that are the exclusive service providers in India.


In addition to that, the awareness and popularity of cloud GPU servers or other GPU cloud computing mediums have encouraged AI and ML startups in the telecom industry in India to take up their efficiency a notch higher by combining these technologies with cloud computing GPU. Let us look into the 7 AI and ML startups in the telecom industry in India 2022 below.


Top AI and ML Startups in Telecom Industry 

With 5G being the top priority for the majority of companies in the telecom industry in India, the importance of providing network affordability for everyone around the country has become the sole mission. Technologies like artificial intelligence and machine learning are the key digital transformation techniques that can change the way networks rotates in the country. The top startups include the following:


Founded in 2021, Wiom is a telecom startup using various technologies like deep learning and artificial intelligence to create a blockchain-based working model for internet delivery. It is an affordable scalable model that might incorporate GPU cloud servers in the future when data flow increases. 


As one of the companies that are strongly driven by data and unique state-of-the-art solutions for revenue generation and cost optimization, TechVantage is a startup in the telecom industry that betters the user experiences for leading telecom heroes with improved media generation and reach, using GPU cloud online


As one of the strongest performers is the customer analytics solutions, Manthan is a supporting startup in India in the telecom industry. It is an almost business assistant that can help with leveraging deep analytics for improved efficiency. For denser database management, NVIDIA A100 80 GB is one of their top choices. 


Just as NVIDIA is known as a top GPU cloud provider, NetraDyne can be named as a telecom startup, even if not directly. It aims to use artificial intelligence and machine learning to increase road safety which is also a key concern for the telecom providers, for their field team. It assists with fleet management. 

KeyPoint Tech

This AI- and ML-driven startup is all set to combine various technologies to provide improved technology solutions for all devices and platforms. At present, they do not use any available cloud GPU servers but expect to experiment with GPU cloud computing in the future when data inflow increases.



Actively known to resolve customer communication, it is also considered to be a startup in the telecom industry as it facilitates better communication among customers for increased engagement and satisfaction. 


An AI startup in Chennai, Facilio is a facility operation and maintenance solution that aims to improve the machine efficiency needed for network tower management, buildings, machines, etc.


In conclusion, the telecom industry in India is actively looking to improve the services provided to customers to ensure maximum customer satisfaction. From top-class networking solutions to better management of increasing databases using GPU cloud or other GPU online services to manage data hungry workloads efficiently, AI and MI-enabled solutions have taken the telecom industry by storm. Moreover, with the introduction of artificial intelligence and machine learning in this industry, the scope of innovation and improvement is higher than ever before.






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June 29, 2022

Top 7 AI Startups in Education Industry

The evolution of the global education system is an interesting thing to watch. The way this whole sector has transformed in the past decade can make a great case study on how modern technology like artificial intelligence (AI) makes a tangible difference in human life. 

In this evolution, edtech startups have played a pivotal role. And, in this write-up, you will get a chance to learn about some of them. So, read on to explore more.

Top AI Startups in the Education Industry-

Following is a list of education startups that are making a difference in the way this sector is transforming –

  1. Miko

Miko started its operations in 2015 in Mumbai, Maharashtra. Miko has made a companion for children. This companion is a bot which is powered by AI technology. The bot is able to perform an array of functions like talking, responding, educating, providing entertainment, and also understanding a child’s requirements. Additionally, the bot can answer what the child asks. It can also carry out a guided discussion for clarifying any topic to the child. Miko bots are integrated with a companion app which allows parents to control them through their Android and iOS devices. 

  1. iNurture

iNurture was founded in 2005 in Bengaluru, Karnataka. It provides universities assistance with job-oriented UG and PG courses. It offers courses in IT, innovation, marketing leadership, business analytics, financial services, design and new media, and design. One of its popular products is KRACKiN. It is an AI-powered platform which engages students and provides employment with career guidance. 

  1. Verzeo

Verzeo started its operations in 2018 in Bengaluru, Karnataka. It is a platform based on AI and ML. It provides academic programmes involving multi-disciplinary learning that can later culminate in getting an internship. These programmes are in subjects like artificial intelligence, machine learning, digital marketing and robotics.

  1. EnglishEdge 

EnglishEdge was founded in Noida in 2012. EnglishEdge provides courses driven by AI for getting skilled in English. There are several programmes to polish your English skills through courses provided online like professional edge, conversation edge, grammar edge and professional edge. There is also a portable lab for schools using smart classes for teaching the language. 

  1. CollPoll

CollPoll was founded in 2013 in Bengaluru, Karnataka. The platform is mobile- and web-based. CollPoll helps in managing educational institutions. It helps in the management of admission, curriculum, timetable, placement, fees and other features. College or university administrators, faculty and students can share opinions, ideas and information on a central server from their Android and iOS phones.

  1. Thinkster

Thinkster was founded in 2010 in Bengaluru, Karnataka. Thinkster is a program for learning mathematics and it is based on AI. The program is specifically focused on teaching mathematics to K-12 students. Students get a personalised experience as classes are conducted in a one-on-one session with the tutors of mathematics. Teachers can give scores for daily worksheets along with personalised comments for the improvement of students. The platform uses AI to analyse students’ performance. You can access the app through Android and iOS devices.

  1. ByteLearn 

ByteLearn was founded in Noida in 2020. ByteLean is an assistant driven by artificial intelligence which helps mathematics teachers and other coaches to tutor students on its platform. It provides students attention in one-on-one sessions. ByteLearn also helps students with personalised practice sessions.

Key Highlights

  • High demand for AI-powered personalised education, adaptive learning and task automation is steering the market.
  • Several AI segments such as speech and image recognition, machine learning algorithms and natural language processing can radically enhance the learning system with automatic performance assessment, 24x7 tutoring and support and personalised lessons.
  • As per the market reports of P&S Intelligence, the worldwide AI in the education industry has a valuation of $1.1 billion as of 2019.
  • In 2030, it is projected to attain $25.7 billion, indicating a 32.9% CAGR from 2020 to 2030.

Bottom Line

Rising reliability on smart devices, huge spending on AI technologies and edtech and highly developed learning infrastructure are the primary contributors to the growth education sector has witnessed recently. Notably, artificial intelligence in the education sector will expand drastically. However, certain unmapped areas require innovations.

With experienced well-coordinated teams and engaging ideas, AI education startups can achieve great success.

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