When you’re faced with a task, you often wish you had the help of a friend. As they say, two heads are better than one, and collaboration can be the key to solving a problem or overcoming a challenge. With computer networks, we can say two nodes are better than one. These unique environments consist of at least two interconnected nodes that share and exchange data and resources, for which they use specific rules called “communications protocols.” Every node has its position within the network and a name and address to identify it.

The possibilities of computer networks are difficult to grasp. They make transferring files and communicating with others on the same network a breeze. The networks also boost storage capacity and provide you with more leeway to meet your goals.

One node can be powerful, but a computer network with several nodes can be like a super-computer capable of completing challenging tasks in record times.

In this introduction to computer networks, we’ll discuss the different types in detail. We’ll also tackle their applications and components and talk more about network topologies, protocols, and security.

Components of a Computer Network

Let’s start with computer network basics. A computer network is comprised of components that it can’t function without. These components can be divided into hardware and software. The easiest way to remember the difference between the two is to know that software is something “invisible,” i.e., stored inside a device. Hardware components are physical objects we can touch.

Hardware Components

  • Network interface cards (NICs) – This is the magic part that connects a computer to a network or another computer. There are wired and wireless NICs. Wired NICs are inside the motherboard and connect to cables to transfer data, while wireless NICs have an antenna that connects to a network.
  • Switches – A switch is a type of mediator. It’s the component that connects several devices to a network. This is what you’ll use to send a direct message to a specific device instead of the entire network.
  • Routers – This is the device that uses an internet connection to connect to a local area network (LAN). It’s like a traffic officer who controls and directs data packets to networks.
  • Hubs – This handy component divides a network connection into multiple computers. This is the distribution center that receives information requests from a computer and places the information to the entire network.
  • Cables and connectors – Different types of cables and connectors are required to keep the network operating.

Software Components

  • Network operating system (NOS) – A NOS is usually installed on the server. It creates an adequate environment for sharing and transmitting files, applications, and databases between computers.
  • Network protocols – Computers interpret network protocols as guidelines for data communication.
  • Network services – They serve as bridges that connect users to the apps or data on a specific network.

Types of Computer Networks

Local Area Network (LAN)

This is a small, limited-capacity network you’ll typically see in small companies, schools, labs, or homes. LANs can also be used as test networks for troubleshooting or modeling.

The main advantage of a local area network is convenience. Besides being easy to set up, a LAN is affordable and offers decent speed. The obvious drawback is its limited size.

Wide Area Network (WAN)

In many aspects, a WAN is similar to a LAN. The crucial difference is the size. As its name indicates, a WAN can cover a large space and can “accept” more users. If you have a large company and want to connect your in-office and remote employees, data centers, and suppliers, you need a WAN.

These networks cover huge areas and stretch across the globe. We can say that the internet is a type of a WAN, which gives you a good idea of how much space it covers.

The bigger size comes at a cost. Wide area networks are more complex to set up and manage and cost more money to operate.

Metropolitan Area Network (MAN)

A metropolitan area network is just like a local area network but on a much bigger scale. This network covers entire cities. A MAN is the golden middle; it’s bigger than a LAN but smaller than a WAN. Cable TV networks are the perfect representatives of metropolitan area networks.

A MAN has a decent size and good security and provides the perfect foundation for a larger network. It’s efficient, cost-effective, and relatively easy to work with.

As far as the drawbacks go, you should know that setting up the network can be complex and require the help of professional technicians. Plus, a MAN can suffer from slower speed, especially during peak hours.

Personal Area Network (PAN)

If you want to connect your technology devices and know nobody else will be using your network, a PAN is the way to go. This network is smaller than a LAN and can interconnect devices in your proximity (the average range is about 33 feet).

A PAN is simple to install and use and doesn’t have components that can take up extra space. Plus, the network is convenient, as you can move it around without losing connection. Some drawbacks are the limited range and slower data transfer.

These days, you encounter PANs on a daily basis: smartphones, gaming consoles, wireless keyboards, and TV remotes are well-known examples.

Network Topologies

Network topologies represent ways in which elements of a computer network are arranged and related to each other. Here are the five basic types:

  • Bus topology – In this case, all network devices and computers connect to only one cable.
  • Star topology – Here, all eyes are on the hub, as that is where all devices “meet.” In this topology, you don’t have a direct connection between the devices; the hub acts as a mediator.
  • Ring topology – Device connections create a ring; the last device is connected to the first, thus forming a circle.
  • Mesh topology – In this topology, all devices belonging to a network are interconnected, making data sharing a breeze.
  • Hybrid topology – As you can assume, this is a mix of two or more topologies.

Network Protocols

Network protocols determine how a device connected to a network communicates and exchanges information. There are the five most common types:

  • Transmission Control Protocol/Internet Protocol (TCP/IP) – A communication protocol that interconnects devices to a network and lets them send/receive data.
  • Hypertext Transfer Protocol (HTTP) – This application layer protocol transfers hypertext and lets users communicate data across the World Wide Web (www).
  • File Transfer Protocol (FTP) – It’s used for transferring files (documents, multimedia, texts, programs, etc.)
  • Simple Mail Transfer Protocol (SMTP) – It transmits electronic mails (e-mails).
  • Domain Name System (DNS) – It converts domain names to IP addresses through which computers and devices are identified on a network.

Network Security

Computer networks are often used to transfer and share sensitive data. Without adequate network security, this data could end up in the wrong hands, not to mention that numerous threats could jeopardize the network’s health.

Here are the types of threats you should be on the lookout for:

  • Viruses and malware – These can make your network “sick.” When they penetrate a system, viruses and malware replicate themselves, eliminating the “good” code.
  • Unauthorized access – These are guests who want to come into your house, but you don’t want to let them in.
  • Denial of service attacks – These dangerous attacks have only one goal: making the network inaccessible to the users (you). If you’re running a business, these attacks will also prevent your customers from accessing the website, which can harm your company’s reputation and revenue.

What can you do to keep your network safe? These are the best security measures:

  • Firewalls – A firewall acts as your network’s surveillance system. It uses specific security rules as guidelines for monitoring the traffic and spotting untrusted networks.
  • Intrusion detection systems – These systems also monitor your network and report suspicious activity to the administrator or collect the information centrally.
  • Encryption – This is the process of converting regular text to ciphertext. Such text is virtually unusable to everyone except authorized personnel who have the key to access the original data.
  • Virtual private networks (VPNs) – These networks are like magical portals that guarantee safe and private connections thanks to encrypted tunnels. They mask your IP address, meaning nobody can tell your real location.
  • Regular updates and patches – These add top-notch security features to your network and remove outdated features at the same time. By not updating your network, you make it more vulnerable to threats.

Reap the Benefits of Computer Networks

Whether you need a network for a few personal devices or want to connect with hundreds of employees and suppliers, computer networks have many uses and benefits. They take data sharing, efficiency, and accessibility to a new level.

If you want your computer network to function flawlessly, you need to take good care of it, no matter its size. This means staying in the loop about the latest industry trends. We can expect to see more AI in computer networking, as it will only make them even more beneficial.

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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

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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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