What is Artificial Intelligence?

Artificial intelligence is an emerging field in technology that attempts to emulate human brain functions.

Humans show off artificial intelligence by using language, tools, apparatus, and culture, while machines demonstrate primarily robotic artificial intelligence. A comparison between these two types of artificial intelligence can be illustrated by the commonly used acronym, “Wise A Machine.” Basically, this means that a machine is able to reason like a human, but more importantly, it shows no emotions.

Humans have shown strong artificial intelligence throughout their species’ existence. Consider the common cold or flu. While most people would readily identify and treat the common cold, a machine would not. This example illustrates how narrow air has become in recent years. While a broad ai still exists, it is predominantly confined to AI labs and project research.

Challenges to narrowing artificial intelligence

There are many challenges to narrowing artificial intelligence. Some analysts worry that we may create something like superintelligence, which would have human intelligence as its byproduct. Superintelligence, in some definitions, could potentially lead to the singularity, which experts dispute. However, researchers in the computer science field continue to strive toward creating machines with narrow ai, rather than broad ai, to aid the development of artificial intelligence for computer science, medicine, and other fields.

Today, self-driving cars and robotic assistance are just two applications of artificial intelligence. In fact, artificially intelligent machines are now used in many aspects of our day-to-day lives. Examples include self-driving trucks that load goods on the highway, self-driving delivery vehicles that load items at various locations, and even self-driving shuttle buses. The goal of these technologies, and others like them, are to enhance our lives by reducing the amount of human error, preventing needless accidents, and increasing productivity. Such technologies will undoubtedly become widespread over the coming decade.

While some claim that artificial intelligence is superior to human intelligence because it is more versatile, others point out that the two forms of intelligence are similar, and in some ways even interchangeable. After all, when a child shows a level of intelligence beyond what a toddler or adult possesses, that child is classified as a “high-functioning” child. This definition doesn’t necessarily mean that such a child has an intelligence that is more complex than that of an adult, but it does suggest that artificial intelligence and machine learning are similar in a way that both involve a problem-solving, application, and learning. Additionally, while the concept of what is artificial intelligence was first introduced in AI journals and popular press in the 1970s, most people today consider machine learning and artificial intelligence to be synonymous.

Many definitions of AI

Artificial intelligence is described in a variety of ways. One commonly used definition is “the ability to gather and evaluate data, especially in the form of natural language, in order to make reliable predictions about the future.” In other words, this means that an artificial intelligence system can project what is called a “neural network” and use that network to make predictions about the future. These neural networks are typically comprised of recurrent, forward, and backward processing networks. Each of these networks has learned how to make the corresponding decisions, and these decisions can then be executed by a machine (hence, the term, “machine learning“).

Since humans are capable of doing some things better than machines, artificial intelligence systems must adapt. One example of an adaptive machine is the chatbot, which operates online at Yahoo! Answers and other sites. The chatbot uses a database of past questions from users to determine what they most likely need to answer. Humans, on the other hand, are not good at doing this.

Still, experts believe that a truly intelligent machine can achieve more, especially if it is programmed to work as a human would. Artificial intelligence researchers have been making progress in the past decade or so, and experts expect that progress continues in the future. For now, we can say that artificial intelligence solutions like chatbots use a very shallow form of artificial intelligence – they are merely implementing the same general principles of natural language processing that most people are taught in school. However, as artificial intelligence researchers improve their software, these systems will become more able and capable and will continue to make improvements in speech recognition, pattern recognition, voice recognition, natural language processing, and more. Eventually, it may be possible for Internet users to completely interact with these artificially intelligent machines.


The science behind artificial intelligence has developed radically in the last decade and it is expected to do so even more in the ones which follow. The machines are constantly improved to serve as a tool to help humankind survive. It is up to the people to use it wisely and appropriately.

Infrastructure as Code 101

Not so long ago, many companies hosted their IT infrastructure on company premises. This worked for a while because, at the time, this was the only viable option. 

Maintaining an in-house datacenter was a challenging task. You had to add or remove hardware physically, install software on each device manually, and so on. Then came cloud-based technology that changed everything. Companies no longer needed to have on-premise datacenters. 

Instead, they can leverage an entire cloud-based infrastructure through Infrastructure as a Service (IaaS). However, cloud services weren’t cheap, and many companies opted for more affordable shared resources. 

The ones that could afford top-notch services managed to gain a significant advantage by using resources provided solely for their purposes. Once again, modern technology is changing the landscape, and in comes Infrastructure as Code (IaC) that will revolutionize cloud services. With that in mind, here’s an IaC 101 guide.

The problems with the legacy systems

As mentioned before, traditional IT data centers had their set of problems. Due to the fact that almost every process was conducted manually, human error was quite a common issue. Moreover, scalability in such legacy systems was troublesome at the very least and quite expensive. 

If your business started to grow, you could add more hardware for the time being. However, eventually, you’d need to replace it altogether. Adding hardware means more room for storing it. This is especially problematic with storage space, as you’d need to add more and more hard drives to store your data. 

Oftentimes, companies would store hard drives off-site to accommodate everything because there was simply no more room on company grounds. When the market competitiveness started to gain pace, these traditional infrastructures simply couldn’t meet company needs. 

What exactly is IaC?

Infrastructure as Code is used in automating infrastructure management. This may not sound as much at first glance, but the benefits of using Infrastructure as code are quite significant. 

The way it works is that instead of conducting various optimization processes manually, you simply automate them using a specific code so that the infrastructure can optimize itself based on specifications listed in the code. 

For example, if you need a specific environment to create enterprise applications in your company, you can simply run the code, and it will set everything up for those specific needs. 

That means optimizing computing power, adding virtual machines, creates users and groups, starting coding processes, etc. As you can imagine, this drastically saves time on otherwise mundane and time-consuming tasks. 

Infrastructure as Code

How does IaC work exactly?

The IaC process is fairly simple, even though it sounds quite complex. As you may already know, infrastructure specifications need to be converted into a code so that automation can be applied. 

The first thing to do is that developers have to define and write infrastructure specifications in a domain-specific computer language. After that, created files need to be stored in the management API or code repository. 

Finally, the platform in use will then take all the necessary actions to create and optimize computing resources. There are two approaches IaC can operate in. Here are the examples: 

  • The Declarative approach – This approach allows you to specify how the infrastructure will be set up, and the code will do the rest. This approach is also known as the functional approach.


  • The Imperative approach – In this approach, you can prepare automation scripts that allow you to set up the infrastructure step by step. Also referred to as the procedural approach, this process requires more management, but it allows the administrators to utilize the full potential of every resource. 

The benefits of IaC

 As mentioned before, IaC may not seem as much, but its value can easily be seen through the benefits it provides to the company. This technology changes the cloud-computing landscape and levels the field in terms of competitive advantage. 

Companies that use this infrastructure automation, especially companies that opted for shared cloud resources, can easily catch up to their competitors in the market in terms of creating highly-functional products at a much faster rate. Here are some of the main benefits IaC has to offer.

  • Faster time to market – By automating the distribution of computing resources, companies can greatly improve efficiency in terms of development, testing, and production.


  • Improved consistency – IaC sets up a specific environment that’s consistent every time. You can slightly alter it based on current needs, but it will always meet expectations when it comes to development and deployment.


  • Cost reduction and improved ROI – By reducing time, skill, and resources requirements for seamless scaling, IaC reduces the operation costs while improving ROI through speed and efficiency. 

Infrastructure as Code has the potential to revolutionize how companies utilize cloud computing and its resources. By offering valuable automation features when it comes to infrastructure, companies can now build an environment specifically tailored to their business needs.