Here’s why your business needs to migrate to the cloud

March 22, 2021

Introduction

Over recent years many businesses have embraced cloud computing solutions. We can relate to cloud computing technology as a computer service over the internet. In today's corporate world there is higher adoption of cloud solutions.

Why your business needs to migrate to the cloud

For better operations and fast performance, an organisation spends massive amounts of money to develop and install the software to the cloud. There are various cloud software providers, for example, Microsoft Azure, Amazon AWS cloud, Google cloud, E2E Cloud which provide enormous results to the organisation in terms of scalability, time-saving results with the help of the modern data centres. It has a safe way to store and share data. Cloud computing allows your business to obtain the software on the internet as a service (SaaS).

An employee can access the cloud service from any other place and at any time to perform their jobs. Cloud computing services come in three important sections:

  1. Platform as a Service (PaaS), 
  2. Infrastructure as a Service (IaaS)
  3. Software as a Service (SaaS).

Benefits of cloud service solution for the enterprise

Flexibility

  1. It is one of the main benefits of cloud computing, which has the capability of mobility.
  2. It provides the flexibility to work from any worldwide location.
  3. An organisation can also reduce the number of workstations and allow employees to work remotely.
  4. It has the capability of monitoring the operations of the work activities with real-time updates of the business user.

Scalability

  1. It has the capability of scalability that enables additional memory space and storage features.
  2. Whenever we require, we can upgrade our package within a small amount of time.

 Data security

With the data security feature, an organisation can store data on the cloud with the help of in-built cloud security features.

  1. This is one of the most important benefits of cloud computing. It secures the data from the data breach, which is intimidating in today's time.
  2. Organisations can store their confidential and relevant data with the cloud security models.
  3. Using the authorisation feature security model, it can authorise the individual user level access.

Improved collaboration and productive results

  1. Cloud computing provides the best collaborations between team members with the help of real-time data and updates in the form of interactive dashboards, which can connect them from different locations.
  2. Improve efficiency, enhance productivity, and maintain costs.

Innovation

  1. Cloud computing enables various levels of innovative ideas to the business operation.
  2. The cloud services provider can recommend innovative developments in the business system applying the cloud technique idea and retain the business available for future improvements. Multi-Cloud and CRM cloud solutions are the best examples of cloud computing.

Bring Automation

The purpose of cloud computing is to bring automation into the business rules.

  1. Using the auto-scaling and automatic resources, interactive real-time updates dashboard, automatic scheduler features from the IoT, AR, and AI automation technologies.
  2. These features can save plenty of time and money for the organisation.

Capital-Expenditure Free

  1. Cloud computing reduces the high cost of hardware.
  2. Using the pay as you go with the type of subscription model.

Competitiveness

  1. Shifting to the cloud provides access to the users with enterprise-level technology. 
  2. It allows smaller businesses to perform quicker than big ones.

Capability to scale quickly

  1. Elasticity is the ability to scale up instantly in cloud computing to keep up with the market. 
  2. If an application encounters large amounts of traffic, using additional servers, it automatically handles such situations. 

Data monitoring

  1. Data is essential to smart businesses. By migrating to the cloud, we can easily monitor the data. 
  2. With the Running report, the business user can access and monitor the important sales figures.

Simple implementation process

Cloud computing provides simple actions to be followed:

  1. Cloud solution provides the best solution, and available technical teams.
  2. Cloud movement can be manageable and simple to use.

Easy recovery

  1. Migrating to the cloud provides an easy way to take data backup and recovery.
  2. Cloud computing has numerous solutions designed to preserve and improve your data.
  3. It has disaster recovery resolutions, without any concern about extra expenses. These resolutions are intended for all kinds and extents of businesses.
  4. With this unique characteristic, a company can secure its information without any concern from the data stolen, damaged, misplaced, or any device failure.

Cloud services save time

One of the most numerous advantages to migrating your business to the cloud today is how well assigned modern data centres and software can ease the process of transferring your data to the cloud.

  1. By signing up with a particular platform, businesses can get the best advice and assistance through the directions from the service teams at any time. 
  2. Salesforce data shows if the business is integrated with the cloud solution, 51% of employees have discovered that developing technologies like cloud computing accumulate both time and effort.

E2E Network's cloud service

E2E Network is the cloud provider. It can provide a robust solution to the business .Below are the few benefits:

  1. Higher UpTime
  2. Intel Processors including Intel Xeon Gold processors
  3. Pure SSD with the RAID setup
  4. Indian Datacenters
  5. Pay-As-You-Go
  6. Affordable Pricing
  7. Cloud Agnostic
  8. Scalable

Image source: https://www.e2enetworks.com/ 

For more information reach out here: https://bit.ly/3mFerJn
E: huma.firdaus@e2enetworks.com M: 8448793014

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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. 

Reference Links:

https://www.datacamp.com/blog/how-to-manage-ai-projects-effectively

https://appinventiv.com/blog/ai-project-management/#:~:text=There%20are%20six%20steps%20that,product%20on%20the%20right%20platform.

https://www.datascience-pm.com/manage-ai-projects/

https://community.pmi.org/blog-post/70065/how-can-i-manage-complex-ai-projects-#_=_

This is a decorative image for Top 7 AI & ML start-ups in Telecom Industry in India
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:

Wiom

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. 

TechVantage

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

Manthan

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. 

NetraDyne

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.

 

Helpshift

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. 

Facilio

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.

 

 

References

https://www.inventiva.co.in/trends/telecom-startup-funding-inr-30-crore/

https://www.mygreatlearning.com/blog/top-ai-startups-in-india/

This is a decorative image for Top 7 AI Startups in Education Industry
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.

Reference Links:

https://belitsoft.com/custom-elearning-development/ai-in-education/ai-in-edtech

https://www.emergenresearch.com/blog/top-10-leading-companies-in-the-artificial-intelligence-in-education-sector-market

https://xenoss.io/blog/ai-edtech-startups

https://riiid.com/en/about

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