It’s hard to find a person who uses the internet but doesn’t enjoy at least one cloud computing service. “Cloud computing” sounds complex, but it’s actually all around you. The term encompasses every tool, app, and service that’s delivered via the internet.


The two popular examples are Dropbox and Google Drive. These cloud-based storage spaces allow you to keep your files at arm’s reach and access them in a few clicks. Zoom is also a cloud-based service – it makes communication a breeze.


Cloud computing can be classified into four types: public, private, hybrid, and community. These four types belong to one of the three cloud computing service models: infrastructure as a service, platform as a service, or software as a service.


It’s time to don a detective cap and explore the mystery hidden behind cloud computing.


Cloud Computing Deployment Models


  • Public cloud
  • Private cloud
  • Hybrid cloud
  • Community cloud

Public Cloud


The “public” in public cloud means anyone who wants to use that service can get it. Public clouds are easy to access and usually have a “general” purpose many can benefit from.


It’s important to mention that with public clouds, the infrastructure is owned by the service provider, not by consumers. This means you can’t “purchase” a public cloud service forever.


Advantages of Public Cloud


  • Cost-effectiveness – Some public clouds are free. Those that aren’t free typically have a reasonable fee.
  • Scalability – Public clouds are accommodating to changing demands. Depending on the cloud’s nature, you can easily add or remove users, upgrade plans, or manipulate storage space.
  • Flexibility – Public clouds are suitable for many things, from storing a few files temporarily to backing up an entire company’s records.

Disadvantages of Public Cloud


  • Security concerns – Since anyone can access public clouds, you can’t be sure your data is 100% safe.
  • Limited customization – While public clouds offer many options, they don’t really allow you to tailor the environment to match your preferences. They’re made to suit broad masses, not particular individuals.

Examples of Public Cloud Providers


  • Amazon Web Services (AWS)
  • Microsoft Azure
  • Google Cloud Platform

Private Cloud


If you’re looking for the complete opposite of public clouds, you’ve found it. Private clouds aren’t designed to fit general criteria. Instead, they’re made to please a single user. Some of the perks private clouds offer are exclusive access, exceptional security, and unmatched customization.


A private cloud is like a single-tenant building. The tenant owns the building and has complete control to do whatever they want. They can tear down walls, drill holes to hang pictures, paint the rooms, install tiles, and get new furniture. When needs change, the tenant can redecorate, no questions asked.


Advantages of Private Cloud


  • Enhanced security – The company’s IT department oversees private clouds. They’re usually protected by powerful firewalls and protocols that minimize the risk of information breaches.
  • Greater control and customization – Since private clouds are one-on-one environments, you can match them to your needs.
  • Improved performance – Private clouds can have functions that suit your organization to the letter, resulting in high performance.

Disadvantages of Private Cloud


  • Higher costs – The exclusive access and customization come at a cost (literally).
  • Limited scalability – You can scale private clouds, but only up to a certain point.

Examples of Private Cloud Providers


  • VMware
  • IBM Cloud
  • Dell EMC

Hybrid Cloud


Public and private clouds have a few important drawbacks that may be deal-breakers for some people. You may want to use public clouds but aren’t ready to compromise on security. On the other hand, you may want the perks that come with private clouds but aren’t happy with limited scalability.


That’s when hybrid clouds come into play because they let you get the best of both worlds. They’re the perfect mix of public and private clouds and offer their best features. You can get the affordability of public clouds and the security of private clouds.


Advantages of Hybrid Cloud


  • Flexibility and scalability – Hybrid clouds are personalized environments, meaning you can adjust them to meet your specific needs. If your needs change, hybrid clouds can keep up.
  • Security and compliance – You don’t have to worry about data breaches or intruders with hybrid clouds. They use state-of-the-art measures to guarantee safety, privacy, and security.
  • Cost optimization – Hybrid clouds are much more affordable than private ones. You’ll need to pay extra only if you want special features.

Disadvantages of Hybrid Cloud


  • Complexity in management – Since they combine public and private clouds, hybrid clouds are complex systems that aren’t really easy to manage.
  • Potential security risks – Hybrid clouds aren’t as secure as private clouds.

Examples of Hybrid Cloud Providers


  • Microsoft Azure Stack
  • AWS Outputs
  • Google Anthos

Community Cloud


Community clouds are shared by more than one organization. The organizations themselves manage them or a third party. In terms of security, community clouds fall somewhere between private and public clouds. The same goes for their price.


Advantages of Community Cloud


  • Shared resources and costs – A community cloud is like a common virtual space for several organizations. By sharing the space, the organizations also share costs and resources.
  • Enhanced security and compliance – Community clouds are more secure than public clouds.
  • Collaboration opportunities – Cloud sharing often encourages organizations to collaborate on different projects.

Disadvantages of Community Cloud


  • Limited scalability – Community clouds are scalable, but only to a certain point.
  • Dependency on other organizations – As much as sharing a cloud with another organization(s) sounds exciting (and cost-effective), it means you’ll depend on them.

Examples of Community Cloud Providers


  • Salesforce Community Cloud
  • Rackspace
  • IBM Cloud for Government

Cloud Computing Service Models


There are three types of cloud computing service models:


  • Infrastructure as a Service (IaaS)
  • Platform as a Service (PaaS)
  • Software as a Service (SaaS)

IaaS


IaaS is a type of pay-as-you-go, third-party service. In this case, the provider gives you an opportunity to enjoy infrastructure services for your networking equipment, databases, devices, etc. You can get services like virtualization and storage and build a strong IT platform with exceptional security.


IaaS models give you the flexibility to create an environment that suits your organization. Plus, they allow remote access and cost-effectiveness.


What about their drawbacks? The biggest issue could be security, especially in multi-tenant ecosystems. You can mitigate security risks by opting for a reputable provider like AWS or Microsoft (Azure).


PaaS


Here, the provider doesn’t deliver the entire infrastructure to a user. Instead, it hosts software and hardware on its own infrastructure, delivering only the “finished product.” The user enjoys this through a platform, which can exist in the form of a solution stack, integrated solution, or an internet-dependent service.


Programmers and developers are among the biggest fans of PaaS. This service model enables them to work on apps and programs without dealing with maintaining complex infrastructures. An important advantage of PaaS is accessibility – users can enjoy it through their web browser.


As far as disadvantages go, the lack of customizability may be a big one. Since you don’t have control over the infrastructure, you can’t really make adjustments to suit your needs. Another potential drawback is that PaaS depends on the provider, so if they’re experiencing problems, you could too.


Some examples of PaaS are Heroku and AWS Elastic Beanstalk.


SaaS


Last but not least is SaaS. Thanks to this computing service model, users can access different software apps using the internet. SaaS is the holy grail for small businesses that don’t have the budget, bandwidth, workforce, or will to install and maintain software. Instead, they leave this work to the providers and enjoy only the “fun” parts.


The biggest advantage of SaaS is that it allows easy access to apps from anywhere. You’ll have no trouble using SaaS as long as you have internet. Plus, it saves a lot of money and time.


Nothing’s perfect, and SaaS is no exception. If you want to use SaaS without interruptions, you need to have a stable internet connection. Plus, with SaaS, you don’t have as much control over the software’s performance and security. Therefore, you need to decide on your priorities. SaaS may not be the best option if you want a highly-customizable environment with exceptional security.


The most popular examples of SaaS are Dropbox, Google Apps, and Salesforce.



Sit on the Right Cloud


Are high security and appealing customization features your priority? Or are you on the hunt for a cost-effective solution? Your answers can indicate which cloud deployment model you should choose.


It’s important to understand that models are not divided into “good” and “bad.” Each has unique characteristics that can be beneficial and detrimental at the same time. If you don’t know how to employ a particular model, you won’t be able to reap its benefits.

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Il Sole 24 Ore: Integrating Artificial Intelligence into the Enterprise – Challenges and Opportunities for CEOs and Management
OPIT - Open Institute of Technology
OPIT - Open Institute of Technology
Apr 14, 2025 6 min read

Source:


Expert Pierluigi Casale analyzes the adoption of AI by companies, the ethical and regulatory challenges and the differentiated approach between large companies and SMEs

By Gianni Rusconi

Easier said than done: to paraphrase the well-known proverb, and to place it in the increasingly large collection of critical issues and opportunities related to artificial intelligence, the task that CEOs and management have to adequately integrate this technology into the company is indeed difficult. Pierluigi Casale, professor at OPIT (Open Institute of Technology, an academic institution founded two years ago and specialized in the field of Computer Science) and technical consultant to the European Parliament for the implementation and regulation of AI, is among those who contributed to the definition of the AI ​​Act, providing advice on aspects of safety and civil liability. His task, in short, is to ensure that the adoption of artificial intelligence (primarily within the parliamentary committees operating in Brussels) is not only efficient, but also ethical and compliant with regulations. And, obviously, his is not an easy task.

The experience gained over the last 15 years in the field of machine learning and the role played in organizations such as Europol and in leading technology companies are the requirements that Casale brings to the table to balance the needs of EU bodies with the pressure exerted by American Big Tech and to preserve an independent approach to the regulation of artificial intelligence. A technology, it is worth remembering, that implies broad and diversified knowledge, ranging from the regulatory/application spectrum to geopolitical issues, from computational limitations (common to European companies and public institutions) to the challenges related to training large-format language models.

CEOs and AI

When we specifically asked how CEOs and C-suites are “digesting” AI in terms of ethics, safety and responsibility, Casale did not shy away, framing the topic based on his own professional career. “I have noticed two trends in particular: the first concerns companies that started using artificial intelligence before the AI ​​Act and that today have the need, as well as the obligation, to adapt to the new ethical framework to be compliant and avoid sanctions; the second concerns companies, like the Italian ones, that are only now approaching this topic, often in terms of experimental and incomplete projects (the expression used literally is “proof of concept”, ed.) and without these having produced value. In this case, the ethical and regulatory component is integrated into the adoption process.”

In general, according to Casale, there is still a lot to do even from a purely regulatory perspective, due to the fact that there is not a total coherence of vision among the different countries and there is not the same speed in implementing the indications. Spain, in this regard, is setting an example, having established (with a royal decree of 8 November 2023) a dedicated “sandbox”, i.e. a regulatory experimentation space for artificial intelligence through the creation of a controlled test environment in the development and pre-marketing phase of some artificial intelligence systems, in order to verify compliance with the requirements and obligations set out in the AI ​​Act and to guide companies towards a path of regulated adoption of the technology.

Read the full article below (in Italian):

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The Lucky Future: How AI Aims to Change Everything
OPIT - Open Institute of Technology
OPIT - Open Institute of Technology
Apr 10, 2025 7 min read

There is no question that the spread of artificial intelligence (AI) is having a profound impact on nearly every aspect of our lives.

But is an AI-powered future one to be feared, or does AI offer the promise of a “lucky future.”

That “lucky future” prediction comes from Zorina Alliata, principal AI Strategist at Amazon and AI faculty member at Georgetown University and the Open Institute of Technology (OPIT), in her recent webinar “The Lucky Future: How AI Aims to Change Everything” (February 18, 2025).

However, according to Alliata, such a future depends on how the technology develops and whether strategies can be implemented to mitigate the risks.

How AI Aims to Change Everything

For many people, AI is already changing the way they work. However, more broadly, AI has profoundly impacted how we consume information.

From the curation of a social media feed and the summary answer to a search query from Gemini at the top of your Google results page to the AI-powered chatbot that resolves your customer service issues, AI has quickly and quietly infiltrated nearly every aspect of our lives in the past few years.

While there have been significant concerns recently about the possibly negative impact of AI, Alliata’s “lucky future” prediction takes these fears into account. As she detailed in her webinar, a future with AI will have to take into consideration:

  • Where we are currently with AI and future trajectories
  • The impact AI is having on the job landscape
  • Sustainability concerns and ethical dilemmas
  • The fundamental risks associated with current AI technology

According to Alliata, by addressing these risks, we can craft a future in which AI helps individuals better align their needs with potential opportunities and limitations of the new technology.

Industry Applications of AI

While AI has been in development for decades, Alliata describes a period known as the “AI winter” during which educators like herself studied AI technology, but hadn’t arrived at a point of practical applications. Contributing to this period of uncertainty were concerns over how to make AI profitable as well.

That all changed about 10-15 years ago when machine learning (ML) improved significantly. This development led to a surge in the creation of business applications for AI. Beginning with automation and robotics for repetitive tasks, the technology progressed to data analysis – taking a deep dive into data and finding not only new information but new opportunities as well.

This further developed into generative AI capable of completing creative tasks. Generative AI now produces around one billion words per day, compared to the one trillion produced by humans.

We are now at the stage where AI can complete complex tasks involving multiple steps. In her webinar, Alliata gave the example of a team creating storyboards and user pathways for a new app they wanted to develop. Using photos and rough images, they were able to use AI to generate the code for the app, saving hundreds of hours of manpower.

The next step in AI evolution is Artificial General Intelligence (AGI), an extremely autonomous level of AI that can replicate or in some cases exceed human intelligence. While the benefits of such technology may readily be obvious to some, the industry itself is divided as to not only whether this form of AI is close at hand or simply unachievable with current tools and technology, but also whether it should be developed at all.

This unpredictability, according to Alliata, represents both the excitement and the concerns about AI.

The AI Revolution and the Job Market

According to Alliata, the job market is the next area where the AI revolution can profoundly impact our lives.

To date, the AI revolution has not resulted in widespread layoffs as initially feared. Instead of making employees redundant, many jobs have evolved to allow them to work alongside AI. In fact, AI has also created new jobs such as AI prompt writer.

However, the prediction is that as AI becomes more sophisticated, it will need less human support, resulting in a greater job churn. Alliata shared statistics from various studies predicting as many as 27% of all jobs being at high risk of becoming redundant from AI and 40% of working hours being impacted by language learning models (LLMs) like Chat GPT.

Furthermore, AI may impact some roles and industries more than others. For example, one study suggests that in high-income countries, 8.5% of jobs held by women were likely to be impacted by potential automation, compared to just 3.9% of jobs held by men.

Is AI Sustainable?

While Alliata shared the many ways in which AI can potentially save businesses time and money, she also highlighted that it is an expensive technology in terms of sustainability.

Conducting AI training and processing puts a heavy strain on central processing units (CPUs), requiring a great deal of energy. According to estimates, Chat GPT 3 alone uses as much electricity per day as 121 U.S. households in an entire year. Gartner predicts that by 2030, AI could consume 3.5% of the world’s electricity.

To reduce the energy requirements, Alliata highlighted potential paths forward in terms of hardware optimization, such as more energy-efficient chips, greater use of renewable energy sources, and algorithm optimization. For example, models that can be applied to a variety of uses based on prompt engineering and parameter-efficient tuning are more energy-efficient than training models from scratch.

Risks of Using Generative AI

While Alliata is clearly an advocate for the benefits of AI, she also highlighted the risks associated with using generative AI, particularly LLMs.

  • Uncertainty – While we rely on AI for answers, we aren’t always sure that the answers provided are accurate.
  • Hallucinations – Technology designed to answer questions can make up facts when it does not know the answer.
  • Copyright – The training of LLMs often uses copyrighted data for training without permission from the creator.
  • Bias – Biased data often trains LLMs, and that bias becomes part of the LLM’s programming and production.
  • Vulnerability – Users can bypass the original functionality of an LLM and use it for a different purpose.
  • Ethical Risks – AI applications pose significant ethical risks, including the creation of deepfakes, the erosion of human creativity, and the aforementioned risks of unemployment.

Mitigating these risks relies on pillars of responsibility for using AI, including value alignment of the application, accountability, transparency, and explainability.

The last one, according to Alliata, is vital on a human level. Imagine you work for a bank using AI to assess loan applications. If a loan is denied, the explanation you give to the customer can’t simply be “Because the AI said so.” There needs to be firm and explainable data behind the reasoning.

OPIT’s Masters in Responsible Artificial Intelligence explores the risks and responsibilities inherent in AI, as well as others.

A Lucky Future

Despite the potential risks, Alliata concludes that AI presents even more opportunities and solutions in the future.

Information overload and decision fatigue are major challenges today. Imagine you want to buy a new car. You have a dozen features you desire, alongside hundreds of options, as well as thousands of websites containing the relevant information. AI can help you cut through the noise and narrow the information down to what you need based on your specific requirements.

Alliata also shared how AI is changing healthcare, allowing patients to understand their health data, make informed choices, and find healthcare professionals who meet their needs.

It is this functionality that can lead to the “lucky future.” Personalized guidance based on an analysis of vast amounts of data means that each person is more likely to make the right decision with the right information at the right time.

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