SMBs And The Cloud: Complexity, Migration, And Choice

October 12, 2021
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Introduction

The business models used by small and medium-sized companies have a common target, i.e., to minimize the cost. But with the increased size of data, storage becomes a big problem. Cloud offers the business framework and IT infrastructure that can benefit SMBs by providing security, accessibility, energy, time, cost-saving, gaining an edge over competitors, and disaster management. Cloud services can achieve cost reduction. Not just cost, it can also make things easy for non-technical people, providing automation support. Read further to know more about the benefits and challenges offered by cloud services to SMBs.

Benefits of using Cloud services for SMBs

Cloud services are very beneficial for small and medium-sized businesses. Below are some benefits:

  • Choice: Businesses have several options to explore the different cloud services in accounting, messaging, CRM, collaboration, etc., and they are equally easy to explore. As compared to on-premise technology, the cloud can offer a lot at reduced costs.
  • Cost: Cost-saving is another benefit of using cloud services for SMBs. The lesser price is due to the pay-as-you-go offered by cloud services. The on-demand service provided by the Cloud saves businesses from the cost of resources not required.
  • Speed: With the help of cloud services, the time required to make the applications available and set up the services gets reduced. Also, upgrades and system patches occur in the background without any impact on the user.
  • Access: SMBs usually need access to the applications 24x7 to make the businesses available on mobile devices. The applications running on cloud are available 24x7 with the help of the internet.
  • Scalability: It is another benefit offered by the cloud. The usage-based price plans offered by the Cloud make it flexible and scalable that can adapt to the ever-changing IT environment.
  • Performance: Most cloud vendors share the service level agreements that include the performance, availability, migration, and data center uptime.
  • Security: Cloud applications are always secured unless they are maintained continuously. Cloud vendors also invest enough for security, redundancy, and best practices.

What are the types of cloud migration strategies?

There are three significant patterns of cloud migration.

Lift & shift (Rehosting):

Lift & shift is a way of cloud migration in which the copy of existing data and application is copied and moved to the cloud without any modification or redesign. In simple words, it is rehosting the current application to the cloud infrastructure. It does not need in-depth knowledge of the cloud. If you have made a Lift & Shift rapidly, applications can rework and optimize with ease while performing using the cloud. It is one of the best parts of it.

Replatforming or move & improve:

Replatforming to migration comprises making a couple of the latest updates to the application, such as presenting automation or scaling without discarding the entire process.

  • Rip & replace:

Rip & replace, also known as refactoring, denotes recreating the workload from the beginning to be cloud-native. It requires investment in developing new skills and time. It indeed pays back the topmost advantages when using the cloud.

Things to consider

Ideally, a business should not migrate its entire business to a cloud in a rush. However, there are many benefits of migrating to the cloud.

Below are the points that small and mid-size companies should consider before moving to the Cloud:

  • Set objectives: Before moving to the cloud, companies should be clear about the objectives they want to achieve by migration. They should sign an agreement that states the implementation scope, phases, expected results, and project timing.
  • Decide on whether to integrate existing data and when: Businesses usually prefer cloud systems because of the speed and simplicity, especially for the legacy system. But before doing that, consider the various risks involved with current data and core system migration to the cloud. Focus on new projects for cloud migration at the initial stages.
  • Research online solutions for a free start: Most companies try to find online solutions before contacting any vendor providing cloud services. Most cloud providers have a free trial period to assess them before deciding the best solution for their business.
  • Take care of the entire cost and not only the initial cost: Before you decide on any product or vendor for cloud services, consider all the charges you need to pay, including total service cost, the cost to scale up, implementation cost, and other separate expenses.

Conclusion

The article was all about the SMBs and the Cloud and challenges concerning migration to the Cloud. Irrespective of the various benefits offered by the Cloud, it is necessary to take care of the challenges when migrating to the Cloud. But with the tips shared in this article, one can easily migrate without facing many issues.

References/Links

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Project Management for AI-ML-DL Projects

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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 –

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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.

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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.

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

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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 

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Wiom

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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
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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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