According to Statista, the U.S. cloud computing industry generated about $206 billion in revenue in 2022. Expand that globally, and the industry has a value of $483.98 billion. Growth is on the horizon, too, with Grand View Research stating that the various types of cloud computing will achieve a compound annual growth rate (CAGR) of 14.1% between 2023 and 2030.

The simple message is that cloud computing applications are big business.

But that won’t mean much to you if you don’t understand the basics of cloud computing infrastructure and how it all works. This article digs into the cloud computing basics so you can better understand what it means to deliver services via the cloud.

The Cloud Computing Definition

Let’s answer the key question immediately – what is cloud computing?

Microsoft defines cloud computing as the delivery of any form of computing services, such as storage or software, over the internet. Taking software as an example, cloud computing allows you to use a company’s software online rather than having to buy it as a standalone package that you install locally on your computer.

For the super dry definition, cloud computing is a model of computing that provides shared computer processing resources and data to computers and other devices on demand over the internet.

Cloud Computing Meaning

Though the cloud computing basics are pretty easy to grasp – you get services over the internet – what it means in a practical context is less clear.

In the past, businesses and individuals needed to buy and install software locally on their computers or servers. This is the typical ownership model. You hand over your money for a physical product, which you can use as you see fit.

You don’t purchase a physical product when using software via the cloud. You also don’t install that product, whatever it may be, physically on your computer. Instead, you receive the services managed directly by the provider, be they storage, software, analytics, or networking, over the internet. You (and your team) usually install a client that connects to the vendor’s servers, which contain all the necessary computational, processing, and storage power.

What Is Cloud Computing With Examples?

Perhaps a better way to understand the concept is with some cloud computing examples. These should give you an idea of what cloud computing looks like in practice:

  • Google Drive – By integrating the Google Docs suite and its collaborative tools, Google Drive lets you create, save, edit, and share files remotely via the internet.
  • Dropbox – The biggest name in cloud storage offers a pay-as-you-use service that enables you to increase your available storage space (or decrease it) depending on your needs.
  • Amazon Web Services (AWS) – Built specifically for coders and programmers, AWS offers access to off-site remote servers.
  • Microsoft Azure – Microsoft markets Azure as the only “consistent hybrid cloud.” This means Azure allows a company to digitize and modernize their existing infrastructure and make it available over the cloud.
  • IBM Cloud – This service incorporates over 170 services, ranging from simple databases to the cloud servers needed to run AI programs.
  • Salesforce – As the biggest name in the customer relationship management space, Salesforce is one of the biggest cloud computing companies. At the most basic level, it lets you maintain databases filled with details about your customers.

Common Cloud Computing Applications

Knowing what cloud computing is won’t help you much if you don’t understand its use cases. Here are a few ways you could use the cloud to enhance your work or personal life:

  • Host websites without needing to keep on-site servers.
  • Store files and data remotely, as you would with Dropbox or Salesforce. Most of these providers also provide backup services for disaster recovery.
  • Recover lost data with off-site storage facilities that update themselves in real-time.
  • Manage a product’s entire development cycle across one workflow, leading to easier bug tracking and fixing alongside quality assurance testing.
  • Collaborate easily using platforms like Google Drive and Dropbox, which allow workers to combine forces on projects as long as they maintain an internet connection.
  • Stream media, especially high-definition video, with cloud setups that provide the resources that an individual may not have built into a single device.

The Basics of Cloud Computing

With the general introduction to cloud computing and its applications out of the way, let’s get down to the technical side. The basics of cloud computing are split into five categories:

  • Infrastructure
  • Services
  • Benefits
  • Types
  • Challenges

Cloud Infrastructure

The interesting thing about cloud infrastructure is that it simulates a physical build. You’re still using the same hardware and applications. Servers are in play, as is networking. But you don’t have the physical hardware at your location because it’s all off-site and stored, maintained, and updated by the cloud provider. You get access to the hardware, and the services it provides, via your internet connection.

So, you have no physical hardware to worry about besides the device you’ll use to access the cloud service.

Off-site servers handle storage, database management, and more. You’ll also have middleware in play, facilitating communication between your device and the cloud provider’s servers. That middleware checks your internet connection and access rights. Think of it like a bridge that connects seemingly disparate pieces of software so they can function seamlessly on a system.

Services

Cloud services are split into three categories:

Infrastructure as a Service (IaaS)

In a traditional IT setup, you have computers, servers, data centers, and networking hardware all combined to keep the front-end systems (i.e., your computers) running. Buying and maintaining that hardware is a huge cost burden for a business.

IaaS offers access to IT infrastructure, with scalability being a critical component, without forcing an IT department to invest in costly hardware. Instead, you can access it all via an internet connection, allowing you to virtualize traditionally physical setups.

Platform as a Service (PaaS)

Imagine having access to an entire IT infrastructure without worrying about all the little tasks that come with it, such as maintenance and software patching. After all, those small tasks build up, which is why the average small business spends an average of 6.9% of its revenue on dealing with IT systems each year.

PaaS reduces those costs significantly by giving you access to cloud services that manage maintenance and patching via the internet. On the simplest level, this may involve automating software updates so you don’t have to manually check when software is out of date.

Software as a Service (SaaS)

If you have a rudimentary understanding of cloud computing, the SaaS model is the one you are likely to understand the most. A cloud provider builds software and makes it available over the internet, with the user paying for access to that software in the form of a subscription. As long as you keep paying your monthly dues, you get access to the software and any updates or patches the service provider implements.

It’s with SaaS that we see the most obvious evolution of the traditional IT model. In the past, you’d pay a one-time fee to buy a piece of software off the shelf, which you then install and maintain yourself. SaaS gives you constant access to the software, its updates, and any new versions as long as you keep paying your subscription. Compare the standalone versions of Microsoft Office with Microsoft Office 365, especially in their range of options, tools, and overall costs.

Benefits of Cloud Computing

The traditional model of buying a thing and owning it worked for years. So, you may wonder why cloud computing services have overtaken traditional models, particularly on the software side of things. The reason is that cloud computing offers several advantages over the old ways of doing things:

  • Cost savings – Cloud models allow companies to spread their spending over the course of a year. It’s the difference between spending $100 on a piece of software versus spending $10 per month to access it. Sure, the one-off fee ends up being less, but paying $10 per month doesn’t sting your bank balance as much.
  • Scalability – Linking directly to cost savings, you don’t need to buy every element of a software to access the features you need when using cloud services. You pay for what you use and increase the money you spend as your business scales and you need deeper access.
  • Mobility – Cloud computing allows you to access documents and services anywhere. Where before, you were tied to your computer desk if you wanted to check or edit a document, you can now access that document on almost any device.
  • Flexibility – Tied closely to mobility, the flexibility that comes from cloud computing is great for users. Employees can head out into the field, access the services they need to serve customers, and send information back to in-house workers or a customer relationship management (CRM) system.
  • Reliability – Owning physical hardware means having to deal with the many problems that can affect that hardware. Malfunctions, viruses, and human error can all compromise a network. Cloud service providers offer reliability based on in-depth expertise and more resources dedicated to their hardware setups.
  • Security – The done-for-you aspect of cloud computing, particularly concerning maintenance and updates, means one less thing for a business to worry about. It also absorbs some of the costs of hardware and IT maintenance personnel.

Types of Cloud Computing

The types of cloud computing are as follows:

  • Public Cloud – The cloud provider manages all hardware and software related to the service it provides to users.
  • Private Cloud – An organization develops its suite of services, all managed via the cloud but only accessible to group members.
  • Hybrid Cloud – Combines a public cloud with on-premises infrastructure, allowing applications to move between each.
  • Community Cloud – While the community cloud has many similarities to a public cloud, it’s restricted to only servicing a limited number of users. For example, a banking service may only get offered to the banking community.

Challenges of Cloud Computing

Many a detractor of cloud computing notes that it isn’t as issue-proof as it may seem. The challenges of cloud computing may outweigh its benefits for some:

  • Security issues related to cloud computing include data privacy, with cloud providers obtaining access to any sensitive information you store on their servers.
  • As more services switch over to the cloud, managing the costs related to every subscription you have can feel like trying to navigate a spider’s web of software.
  • Just because you’re using a cloud-based service, that doesn’t mean said service handles compliance for you.
  • If you don’t perfectly follow a vendor’s terms of service, they can restrict your access to their cloud services remotely. You don’t own anything.
  • You can’t do anything if a service provider’s servers go down. You have to wait for them to fix the issue, leaving you stuck without access to the software for which you’re paying.
  • You can’t call a third party to resolve an issue your systems encounter with the cloud service because the provider is the only one responsible for their product.
  • Changing cloud providers and migrating data can be challenging, so even if one provider doesn’t work well, companies may hesitate to look for other options due to sunk costs.

Cloud Computing Is the Present and Future

For all of the challenges inherent in the cloud computing model, it’s clear that it isn’t going anywhere. Techjury tells us that about 57% of companies moved, or were in the process of moving, their workloads to cloud services in 2022.

That number will only increase as cloud computing grows and develops.

So, let’s leave you with a short note on cloud computing. It’s the latest step in the constant evolution of how tech companies offer their services to users. Questions of ownership aside, it’s a model that students, entrepreneurs, and everyday people must understand.

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Sage: The ethics of AI: how to ensure your firm is fair and transparent
OPIT - Open Institute of Technology
OPIT - Open Institute of Technology
Mar 7, 2025 3 min read

Source:


By Chris Torney

Artificial intelligence (AI) and machine learning have the potential to offer significant benefits and opportunities to businesses, from greater efficiency and productivity to transformational insights into customer behaviour and business performance. But it is vital that firms take into account a number of ethical considerations when incorporating this technology into their business operations. 

The adoption of AI is still in its infancy and, in many countries, there are few clear rules governing how companies should utilise the technology. However, experts say that firms of all sizes, from small and medium-sized businesses (SMBs) to international corporations, need to ensure their implementation of AI-based solutions is as fair and transparent as possible. Failure to do so can harm relationships with customers and employees, and risks causing serious reputational damage as well as loss of trust.

What are the main ethical considerations around AI?

According to Pierluigi Casale, professor in AI at the Open Institute of Technology, the adoption of AI brings serious ethical considerations that have the potential to affect employees, customers and suppliers. “Fairness, transparency, privacy, accountability, and workforce impact are at the core of these challenges,” Casale explains. “Bias remains one of AI’s biggest risks: models trained on historical data can reinforce discrimination, and this can influence hiring, lending and decision-making.”

Part of the problem, he adds, is that many AI systems operate as ‘black boxes’, which makes their decision-making process hard to understand or interpret. “Without clear explanations, customers may struggle to trust AI-driven services; for example, employees may feel unfairly assessed when AI is used for performance reviews.”

Casale points out that data privacy is another major concern. “AI relies on vast datasets, increasing the risk of breaches or misuse,” he says. “All companies operating in Europe must comply with regulations such as GDPR and the AI Act, ensuring responsible data handling to protect customers and employees.”

A third significant ethical consideration is the potential impact of AI and automation on current workforces. Businesses may need to think about their responsibilities in terms of employees who are displaced by technology, for example by introducing training programmes that will help them make the transition into new roles.

Olivia Gambelin, an AI ethicist and the founder of advisory network Ethical Intelligence, says the AI-related ethical considerations are likely to be specific to each business and the way it plans to use the technology. “It really does depend on the context,” she explains. “You’re not going to find a magical checklist of five things to consider on Google: you actually have to do the work, to understand what you are building.”

This means business leaders need to work out how their organisation’s use of AI is going to impact the people – the customers and employees – that come into contact with it, Gambelin says. “Being an AI-enabled company means nothing if your employees are unhappy and fearful of their jobs, and being an AI-enabled service provider means nothing if it’s not actually connecting with your customers.”

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Reuters: EFG Watch: DeepSeek poses deep questions about how AI will develop
OPIT - Open Institute of Technology
OPIT - Open Institute of Technology
Feb 10, 2025 4 min read

Source:

  • Reuters, Published on February 10th, 2025.

By Mike Scott

Summary

  • DeepSeek challenges assumptions about AI market and raises new ESG and investment risks
  • Efficiency gains significant – similar results being achieved with less computing power
  • Disruption fuels doubts over Big Tech’s long-term AI leadership and market valuations
  • China’s lean AI model also casts doubt on costly U.S.-backed Stargate project
  • Analysts see DeepSeek as a counter to U.S. tariffs, intensifying geopolitical tensions

February 10 – The launch by Chinese company DeepSeek, opens new tab of its R1 reasoning model last month caused chaos in U.S. markets. At the same time, it shone a spotlight on a host of new risks and challenged market assumptions about how AI will develop.

The shock has since been overshadowed by President Trump’s tariff wars, opens new tab, but DeepSeek is set to have lasting and significant implications, observers say. It is also a timely reminder of why companies and investors need to consider ESG risks, and other factors such as geopolitics, in their investment strategies.

“The DeepSeek saga is a fascinating inflection point in AI’s trajectory, raising ESG questions that extend beyond energy and market concentration,” Peter Huang, co-founder of Openware AI, said in an emailed response to questions.

DeepSeek put the cat among the pigeons by announcing that it had developed its model for around $6 million, a thousandth of the cost of some other AI models, while also using far fewer chips and much less energy.

Camden Woollven, group head of AI product marketing at IT governance and compliance group GRC International, said in an email that “smaller companies and developers who couldn’t compete before can now get in the game …. It’s like we’re seeing a democratisation of AI development. And the efficiency gains are significant as they’re achieving similar results with much less computing power, which has huge implications for both costs and environmental impact.”

The impact on AI stocks and companies associated with the sector was severe. Chipmaker Nvidia lost almost $600 billion in market capitalisation after the DeepSeek announcement on fears that demand for its chips would be lower, but there was also a 20-30% drop in some energy stocks, said Stephen Deadman, UK associate partner at consultancy Sia.

As Reuters reported, power producers were among the biggest winners in the S&P 500 last year, buoyed by expectations of ballooning demand from data centres to scale artificial intelligence technologies, yet they saw the biggest-ever one-day drops after the DeepSeek announcement.

One reason for the massive sell-off was the timing – no-one was expecting such a breakthrough, nor for it to come from China. But DeepSeek also upended the prevailing narrative of how AI would develop, and who the winners would be.

Tom Vazdar, professor of cybersecurity and AI at Open Institute of Technology (OPIT), pointed out in an email that it called into question the premise behind the Stargate Project,, opens new tab a $500 billion joint venture by OpenAI, SoftBank and Oracle to build AI infrastructure in the U.S., which was announced with great fanfare by Donald Trump just days before DeepSeek’s announcement.

“Stargate has been premised on the notion that breakthroughs in AI require massive compute and expensive, proprietary infrastructure,” Vazdar said in an email.

There are also dangers in markets being dominated by such a small group of tech companies. As Abbie Llewellyn-Waters, Investment manager at Jupiter Asset Management, pointed out in a research note, the “Magnificent Seven” tech stocks had accounted for nearly 60% of the index’s gains over the previous two years. The group of mega-caps comprised more than a third of the S&P 500’s total value in December 2024.

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