{"id":347494,"date":"2026-01-15T17:45:00","date_gmt":"2026-01-15T17:45:00","guid":{"rendered":"https:\/\/xamai.com\/que-es-la-inteligencia-artificial\/"},"modified":"2026-04-28T17:01:54","modified_gmt":"2026-04-28T17:01:54","slug":"que-es-la-inteligencia-artificial","status":"publish","type":"post","link":"https:\/\/www.xamai.com\/en\/blog\/que-es-la-inteligencia-artificial","title":{"rendered":"What is artificial intelligence and why is it transforming the way we live and work?"},"content":{"rendered":"

What is artificial intelligence and why is it transforming the way we live and work?<\/span><\/strong><\/p>\n

<\/p>\n

It is undeniable that artificial intelligence is already a technology present in our daily lives and the engine of many organizations that have stopped seeing it as an element only of science fiction movies to apply it in their production processes.<\/p>\n

AI is practically everywhere: from image recognition on a mobile phone, to systems capable of analyzing large volumes of data in just seconds, <\/span>with a very small margin of error and facilitating informative results<\/p>\n

We are facing a new tool that improves the productivity of employees and organizations <\/span>and also directly affects an entire society that uses artificial intelligence directly or indirectly; especially when directly associated with advances such as machine learning, deep learning, and artificial neural networks.<\/p>\n

For that reason, it is the duty of everyone to understand how AI works, how it has evolved, how AI models work, and why its impact is increasingly relevant in areas such as business, education, industry, and society in general.<\/p>\n

What is artificial intelligence?<\/h2>\n

Artificial intelligence is a discipline of computer science whose objective is to design systems and programs that can perform tasks that normally require human intelligence. To explain it better, lAI is not one thing, it is a set of techniques, algorithms, and models<\/span> that allow machines to interpret information, recognize patterns, and, on occasion, make decisions within a real environment.<\/p>\n

In just a few years, we have seen that AI has evolved so much that it can now process large amounts of data and extract information in just seconds.<\/p>\n

A definition of AI<\/h3>\n

A practical definition of artificial intelligence (AI) would be: the ability of a system to perform activities such as reasoning, problem-solving, natural language interpretation, and learning from data.<\/p>\n

This learning is automatic and is called machine learning, and in turn, performs deep learning, called deep learning.<\/p>\n

What is the difference between AI and human intelligence?<\/h3>\n

It might seem like an obvious question, but unlike human intelligence, AI has no consciousness or intuition; it only works using algorithms and models that learn from the data it previously analyzes.<\/p>\n

As people, we acquire knowledge from experiences, the context in which we live, and some preconceived judgments. But, AI systems apply statistics and patterns extracted from data to generate highly accurate responses.<\/span><\/p>\n

The essential components of AI: data, models, and learning<\/h3>\n

AI works with 3 main components: data, models, and learning. Without data, a system cannot learn; they are the basis for AI models to organize information and allow for generalization. Machine learning is the process by which these models adjust their parameters to improve their performance. In more complex systems, deep learning and neural networks also help to recognize patterns in images, text, or signals.<\/p>\n

AI as a practical tool<\/h3>\n

AI was designed to expand human capabilities and be a tool to help automate processes, accelerate any type of analysis, and solve problems that previously consumed a lot of time.<\/p>\n

For example, image recognition systems that use AI use neural networks to classify photographs, which previously took weeks to achieve now takes seconds; on the other hand, natural language processing models understand and generate text according to existing data; and generative AI creates new content based on previously learned patterns.<\/span><\/p>\n

A simple example to ground the idea<\/h3>\n

Let's put a practical example within a company that requires filtering thousands of resumes for the personnel recruitment process and needs to detect candidates with experience in a certain profile.<\/p>\n

Previously, that selection was a long and exhausting process, but today, there is AI that uses pattern-detecting algorithms among thousands of applicants and can prioritize those who meet the criteria the company is looking for. It does not replace human judgment, but accelerates the selection and reduces repetitive errors.<\/span><\/p>\n

At Xamai, we work alongside companies to provide them with AI integrated into SAP solutions that allow them to take advantage of its benefits in real processes within their daily operations.<\/p>\n

Brief history and evolution of artificial intelligence<\/h2>\n

To understand what artificial intelligence is today, it is always worth looking to the past, because AI did not appear overnight.<\/p>\n

It is a work achieved after a lot of research and the advances that have been made in computing, a work aimed at trying to imitate certain capabilities of human intelligence using machines and computer systems.<\/p>\n

The origin<\/h3>\n

It all started with the question that many researchers asked themselves about whether a computer could reason, learn, or solve problems in a similar way to humans. And to try to answer, a research approach was made where they created programs capable of performing tasks that normally require human intelligence.<\/span><\/p>\n

In this initial stage, the goal was not massive automation, but to understand how intelligence works, how knowledge is generated, and how systems could imitate basic cognitive processes such as logical reasoning or simple problem solving.<\/p>\n

So, who invented artificial intelligence?<\/h3>\n

Although there is no single person who \u201cinvented\u201d AI, there are researchers who laid the groundwork and created a precedent for development. One of the most important names in this context is Alan Turing, mathematician and pioneer of computing. In 1950 Turing posed a fundamental question: can machines think?<\/p>\n

It seems like a risky question and, as such, he decided to explore the famous Turing test, an experiment that evaluates whether a machine can imitate human behavior in a conversation.<\/p>\n

Years later, in 1956, John McCarthy officially coined the term artificial intelligence during an academic conference and it was at that moment when AI began to consolidate as a formal research field where scientists, programmers, and researchers who wanted to create systems capable of learning from the data they analyzed, interpreted information, and began to make decisions became involved.<\/p>\n

The evolution of AI<\/h3>\n

The history of artificial intelligence has had its ups and downs, during some years the progress has been remarkable and in others there have been stagnation, especially when expectations exceeded the technological capabilities of the moment.<\/p>\n

There were times when research paused due to the limited computing power, complexity of algorithms, etc. However, once these conditions improved and there was a growth in computing power, the landscape changed.<\/p>\n

A milestone that marked history was when IBM's Deep Blue, which defeated a world chess champion, demonstrated that AI systems could outperform humans in very specific tasks.<\/span><\/p>\n

Currently, the rise of machine learning, deep learning, and artificial neural networks has allowed AI to advance rapidly towards more complex applications, such as natural language processing, image recognition, and content generation.<\/p>\n

From research to real applications<\/h3>\n

What was once exclusive to laboratories and research centers is now part of products, platforms, business processes, and home technology; in the blink of an eye, artificial intelligence went from being a laboratory tool to an applied tool in areas such as business, education, industry, medical diagnosis, and human resources.<\/p>\n

AI is no longer just about technological innovation, but about how to integrate intelligent systems <\/span>that support processes and facilitate the daily life of businesses and society in general.<\/p>\n

How does artificial intelligence work?<\/h2>\n

It's time to talk about how AI works, because although it might seem like something complex or difficult to understand, the reality is that the principle behind artificial intelligence is simpler than it appears.<\/p>\n

It's simple: AI works based on data, algorithms, and models<\/span> that allow systems to learn, recognize patterns, and from that, help in decision-making quickly and without needing to stop to give step-by-step instructions for each task.<\/p>\n

AI systems are designed to adapt and improve over time as they process new information, and without anyone needing to intervene in this improvement.<\/p>\n

As we mentioned earlier, the pillars of AI are data, algorithms, and learning models. We explain it in more detail below.<\/p>\n

Data and AI<\/h3>\n

It all starts with data. For AI to learn, it needs large amounts of data from multiple sources <\/span>which can be historical records, digital interactions, sensors, platforms, and even elements like cookies that allow understanding user preferences and behaviors. Once the AI collects all the data in seconds, it organizes it and creates a set of it, which then serves as the basis for learning.<\/p>\n

Algorithms<\/h3>\n

Algorithms are the mathematical instructions that analyze that data and look for patterns and relationships<\/span>once they have them, AI models are built, which are representations capable of generalizing what has been learned and applying it to new scenarios.<\/p>\n

Machine learning and deep learning<\/h3>\n

Once data is collected and algorithms are applied, comes machine learning, which is one of the most important techniques within artificial intelligence. It means that systems learn from data without being explicitly programmed for each situation.<\/span> Instead of telling the computer what to do at each step, it is shown information and it learns on its own.<\/p>\n

Deep learning is part of the evolution of machine learning, and its main characteristic is that it is based on artificial neural networks, inspired by the functioning of the human brain.<\/p>\n

Neural networks have several layers that process information progressively, allowing them to perform more complex tasks, such as image recognition, voice interpretation, or natural language analysis. This evolution has allowed AI to perform tasks that previously only humans could do, such as classifying information, detecting anomalies, or predicting behaviors.<\/p>\n

Natural language processing and decision making<\/p>\n

Since we touched on the evolutionary topic, or highlights an area of AI that has seen great improvements at an accelerated pace and is natural language processing, just as we humans do.<\/h3>\n

It is a technology that allows systems to understand, interpret, and generate natural language, so as to have a more real interaction between people and machines. Today we are full of virtual assistants, chatbots and customer service systems that are constantly improving when interacting with people.<\/p>\n

But, beyond interaction, AI also actively participates in decision making, because by analyzing large volumes of data, it is possible<\/p>\n

to analyze trends, evaluate scenarios and offer recommendations based on evidence. It is undoubtedly of great value to companies and organizations that need to make quick and informed decisions based on reliable information.<\/span><\/p>\n

It is undoubtedly of great value to companies and organizations that need to make quick and informed decisions based on reliable information.<\/p>\n

How is AI applied in practice<\/h3>\n

In practice, the functioning of AI translates into continuous processes of analysis, learning, and adjustment. A system receives data, processes it using trained models, generates results, and over time, improves its performance as new information is integrated. For companies, this capability allows for automated operations, which in turn enables better resource management and improves team performance. At Xamai, for examplethe integration of AI systems along with platforms like SAP allows you to support each process in your company<\/span> reducing operational failures and allowing you to make decisions based on real-time information.<\/p>\n

Types and classifications of artificial intelligence<\/h2>\n

Talking about Artificial Intelligence is not talking about a single tool that works the same way for everyone. There are different types and classifications because not all have the same scope, nor do they respond effectively to different tasks, and many of them do not even resemble human intelligence.<\/p>\n

These classifications help to put into context what AI can do today, what is under development, and what remains, for now, part of theory.<\/p>\n

Types of artificial intelligence according to their capability<\/h3>\n

One of the most common ways to classify AI is by its level of capability or \u201cintelligence.\u201d Let's go:<\/p>\n

Narrow or Weak AI<\/h3>\n

Contrary to what one might think due to its name, it is the most used today. This type of AI is designed to perform specific and well-defined tasks, such as image recognition, email filtering, or data analysis. Although it can achieve high performance, it has no general understanding or consciousness and is used in most business applications and digital tools.<\/p>\n

Artificial General Intelligence<\/h3>\n

For the time being, it is more of a theoretical than a practical concept, as it is an AI that would have the ability to learn and reason in a similar way to humans, applying its knowledge to various tasks. It does not yet exist in practice, but it remains a research goal for many scientists and developers.<\/p>\n

Superintelligent AI<\/h3>\n

It is an idea that belongs more to the field of advanced research and science fiction, but at this point, the intention is for AI systems to surpass human intelligence in practically all areas.<\/p>\n

Generative Artificial Intelligence<\/h3>\n

Generative AI is one of the most recent and relevant developments within the types of artificial intelligence and is designed to create new content from patterns learned in large datasets. These systems use advanced AI models, such as transformers and deep neural networks, to generate their content based on statistics, patterns, and relationships present in the data they were trained on. Generative AI opens up new possibilities for automating creative processes within a company, it can also improve communication, accelerate content development, and support areas such as marketing, human resources, or customer service.<\/span><\/p>\n

These systems use advanced AI models, such as transformers and deep neural networks, to generate their content based on statistics, patterns, and relationships present in the data they were trained on.<\/p>\n

Generative AI opens up new possibilities for automating creative processes within a company, it can also improve communication, accelerate content development, and support areas such as marketing, human resources, or customer service.<\/p>\n

Why is it important to understand the types of AI?<\/h3>\n

Knowing the types of artificial intelligence helps to establish realistic expectations about what AI can and cannot do, especially in a business context when integrating technology, selecting tools, and designing processes that truly generate value for the business.<\/p>\n

Instead of thinking of AI as a universal solution, it is more useful to see it as a set of systems with different capabilities and applications that can be used depending on the industry in which you work.<\/p>\n

Main characteristics of artificial intelligence<\/h2>\n

 <\/p>\n

What differentiates AI from other technologies? Undoubtedly its characteristics define it. These characteristics explain why AI has become such a relevant technology worldwide and why its adoption continues to grow in various sectors.<\/p>\n

1.- Ability to learn from data<\/h3>\n

One of the main characteristics of AI is its ability to learn automatically and deeply and its analysis of large amounts of data, identify patterns and relationships, and improve its performance over time. The more data a model processes, the greater its ability to offer accurate and consistent results without human intervention.<\/p>\n

2.- Automation of complex tasks<\/h3>\n

Another characteristic is automation; that is, AI can perform tasks that normally require human intelligence, such as classifying information, detecting anomalies, or supporting decision-making processes. By doing so in seconds, it frees up time and resources for people to focus on strategic, creative, or higher-value activities.<\/p>\n

3.- Processing and analysis of large volumes of information<\/h3>\n

Artificial intelligence can handle large volumes of data in very short times. While a person might take days or weeks to analyze certain information, AI systems can do it in minutes, identifying trends, correlations, and opportunities. In areas such as business analysis, medical diagnosis, security, and operations, AI has added greater value to this feature offered.<\/p>\n

4.- Interaction in natural language<\/h3>\n

As AI can process natural language, this makes it much easier for people to interact with systems. This feature is the basis of chatbots, virtual assistants, and automated support platforms, which helps to improve the user experience and customer support or internal communication.<\/p>\n

5.- Adaptability and continuous improvement<\/h3>\n

As AI is not static, its models can be adjusted as they receive new information, which allows adaptability to changes in the environment, something key today where needs evolve constantly.<\/p>\n

6. - Practical approach for companies and organizations<\/h3>\n

These characteristics make artificial intelligence a fundamental tool for improving processes, strengthening decision-making, and enhancing team capabilities, always having a people-centered vision and ensuring complete organizational goal achievement.<\/p>\n

 <\/h2>\n

 <\/h2>\n

<\/span><\/p>\n

So, what is artificial intelligence for?<\/h2>\n

Now that we've read about what AI is, how it works, its types, and characteristics, the question arises: what is artificial intelligence really for in various contexts?<\/p>\n

The short answer is that AI is used to support, optimize, and automate processes <\/span>that previously depended entirely on human intelligence. In practice, artificial intelligence is used to analyze information, solve problems, and facilitate decision-making in increasingly complex scenarios.<\/p>\n

It is not an isolated tool; now AI is integrated into systems, platforms, and tools that are part of everyday life and the internal workings of organizations, just as SAP integrates AI to transform the way businesses operate. SAP provides the structure, processes, and data; AI adds intelligence, analysis, and automation. The result is more efficient, predictive, and prepared organizations to compete in this accelerated growth context.<\/p>\n

AI is also used to automate tasks that normally require human intervention<\/span>such as information classification, document processing, or email management. It also contributes to improving the overall performance of teams and systems. AI can detect inefficiencies, suggest improvements, and adapt to changes in real time.<\/span> Applications and use cases of artificial intelligence<\/p>\n

The<\/h2>\n

applications of artificial intelligence are becoming increasingly broad and can be seen in everyday life thanks to its ability to adapt to different contexts and needs. Let's analyze the <\/span>main applications of AI to understand its scope and lay the foundation for more specific content.<\/span>Applications in companies and organizations<\/p>\n

In the business world, artificial intelligence is mainly used to improve performance and support decision-making. AI systems analyze data to anticipate risks, identify opportunities, and improve operational efficiency.<\/h3>\n

In areas such as human resources, AI supports recruitment processes, performance evaluation, and workplace climate analysis. In operations and compliance, they help detect anomalies, improve security, and ensure that processes are executed correctly.<\/p>\n

For organizations that work with Xamai, they know that SAP uses AI to improve the experience of those who use its systems. Intelligent assistants, personalized recommendations, and simpler processes make daily work more agile and less complicated, even for non-technical users.<\/p>\n

Applications in daily life<\/p>\n

Applications in daily life<\/h3>\n

Currently, we use artificial intelligence sometimes without realizing it; for example, when we use virtual assistants or recommendation systems, AI is present in devices, platforms, and digital services. These applications improve the user experience by offering faster, more personalized, and efficient responses, based on previous preferences and behaviors.<\/p>\n

AI Applications and Their Impact on Various Sectors<\/h3>\n

AI applications cover sectors such as industry, education, research, business, and services. In each one, AI adapts to the needs of the environment, constantly learning about it, which will allow a set of tools to be developed around it that can be integrated flexibly according to the objectives of each organization.<\/p>\n

Benefits and Disadvantages of Artificial Intelligence<\/h2>\n

At this point, talking about artificial intelligence implies recognizing both its advantages and its limitations. AI offers very important benefits for companies and organizations, but also presents challenges that must be considered when using it.<\/p>\n

Everything requires balance, and with that, using technology responsibly.<\/p>\n

Benefits of Artificial Intelligence<\/h3>\n

One of the main benefits of AI is its ability to process large volumes of data quickly and accurately. <\/span>This allows analyzing complex information based on real data, not just assumptions.<\/p>\n

AI also drives the automation of tasks that normally require human intervention. Repetitive processes, operational analysis, and information management can be performed more efficiently, improving performance and reducing errors. For companies, this translates into increased productivity and better use of resources.<\/p>\n

Another important benefit is that AI systems can adapt to the growth of an organization without needing to proportionally increase human effort and can help personalize experiences to improve customer service and strengthen various areas of the company.<\/p>\n

Disadvantages and Limitations of Artificial Intelligence<\/h3>\n

Despite its advantages, artificial intelligence also presents some limitations that should not be ignored, for example, the dependence on data, which means that if the data is incomplete, biased, or of low quality, the results may be inaccurate and limited.<\/p>\n

Another challenge is that, although it can mimic certain human cognitive skills, it does not possess ethical judgment, genuine creativity, or emotional understanding; it will never be able to completely replace human judgment in complex or sensitive situations.<\/p>\n

There are also challenges related to technological integration, information security, and compliance with regulations; in addition, implementing AI requires investment, training, and proper management so that organizations can get the most out of it.<\/p>\n

Risks and Challenges to Consider<\/h3>\n

In addition to operational disadvantages, AI poses risks at a social and organizational level <\/span>since automation can generate concern about the impact on employment and, on the other hand, the misuse of intelligent systems can affect user privacy or trust.<\/p>\n

It is of great importance and fundamental that organizations adopt artificial intelligence with an ethical and responsible vision because it is not a magic solution, it is only a tool that must be complemented with human intelligence.<\/p>\n

Ethics, governance, and regulation of artificial intelligence<\/h2>\n

We have arrived at an important topic because now that AI is increasingly integrated into processes, platforms, and decisions, a question arises that should not be overlooked: how do we ensure that its use is ethical, responsible, and aligned with human values?<\/p>\n

Ethics, governance, and regulation should be considered by all organizations seeking to leverage the benefits of AI without losing sight of the social and human impact because it is not about stopping innovation, but about guiding it consciously.<\/p>\n

The importance of ethics in artificial intelligence<\/h3>\n

Los AI systems do not have their own moral judgment.<\/span> This means that they can produce biases, errors, or unfair decisions if they are not designed and supervised correctly, so it is vital to ensure that AI models are transparent, ethical, and fair.<\/p>\n

It must be avoided that, in practice, people are not protected from potential negative impacts, and this is achieved by establishing limits and validating results.<\/p>\n

Governance of AI within organizations<\/h3>\n

Governance refers to the rules, processes, and responsibilities that define the direction of artificial intelligence within an organization. It is very important to have a clear governance framework to ensure that AI is used consistently with business objectives. Here, it should be defined who makes decisions about the use of AI, how data is managed, how the performance of systems is evaluated, and how these technologies are integrated into existing processes.<\/p>\n

Regulation on the use of AI<\/h3>\n

At a global level, the regulation of artificial intelligence continues to evolve because governments are seeking to establish legal frameworks that protect rights, promote transparency, and ensure responsible use of the technology, without hindering its development. Anyone who has AI technology should stay informed about safety, privacy, and compliance standards,<\/span> especially when AI processes sensitive data or influences relevant decisions.<\/p>\n

A human-centered approach Beyond laws and policies, the responsible use of artificial intelligence requires a human-centered vision, as it must be understood as a tool that supports humans, not as a substitute for their judgment, creativity, or responsibility.<\/span>especially when AI processes sensitive data or influences relevant decisions.<\/p>\n

A people-centered approach<\/h3>\n

Beyond laws and policies, responsible use of artificial intelligence requires a people-centered vision because it must be understood as a tool that supports humans, not as a substitute for their judgment, creativity, or responsibility.<\/p>\n

What future awaits artificial intelligence?<\/h2>\n

It's a bit complicated to talk about the future of artificial intelligence because it's not just about predicting science fiction scenarios, but observing the trends that are already underway and the evolution that is achieved as data availability increases, if computing capacity improves, and if more sophisticated AI models are developed. The future of AI points to a deeper collaboration between technology and human intelligence, where a good alliance can allow for the resolution of complex problems and better decision-making.<\/span><\/p>\n

Technological evolution and new AI models<\/p>\n

In the coming years, we will see significant advances in deep learning, artificial neural networks, which will allow<\/h3>\n

to create more precise, efficient, and adaptable systems in such a way that a <\/span>wide range of tasks can be addressed with greater context and better interpretation of information.<\/span> Generative AI will continue to grow, driving new forms of creation, automation, and analysis in sectors such as business, education, research, and industry.<\/p>\n

Impact on companies, organizations, and people<\/p>\n

The future of artificial intelligence will have a direct impact on the way organizations work, and companies and teams will be required to develop new skills, adopt digital tools, and redefine the way they collaborate, but at the same time AI will open up opportunities to improve performance and create more personalized experiences, always with an ethical vision of things.<\/h3>\n

Preparing today for the future of AI<\/p>\n

Understanding what artificial intelligence is, how AI works, and what its current applications are is the first step to being prepared. The future is not only about adopting technology, but about knowing how to integrate it consciously into processes, teams, and decisions.<\/h3>\n

At this point, platforms like SAP play a very important role because they offer products where AI models, machine learning, and automation can be incorporated safely, scalably, and always with full adherence to what organizations need. When artificial intelligence is connected with solid business systems, the impact is multiplied.<\/p>\n

At Xamai we know that it's not just about implementing technology,<\/p>\n

but about understanding the context, the people, and the processes so that AI becomes a tool that generates real value. By integrating artificial intelligence with solutions like SAP, we help companies make better decisions and prepare for a future where technology and human intelligence work together.<\/span> Artificial intelligence will continue to evolve. The key is to understand it, adopt it responsibly, and use it as an enabler of sustainable growth. That's where the combination of vision, experience, and technology makes the difference.<\/p>\n

Rom\u00e1n Garcia<\/p>","protected":false},"excerpt":{"rendered":"

What is artificial intelligence and why is it transforming the way we live and work?<\/span><\/strong><\/p>","protected":false},"author":4,"featured_media":350164,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"content-type":"","footnotes":""},"categories":[20],"tags":[],"class_list":["post-347494","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-transformacion_digital"],"_links":{"self":[{"href":"https:\/\/www.xamai.com\/en\/wp-json\/wp\/v2\/posts\/347494","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.xamai.com\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.xamai.com\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.xamai.com\/en\/wp-json\/wp\/v2\/users\/4"}],"replies":[{"embeddable":true,"href":"https:\/\/www.xamai.com\/en\/wp-json\/wp\/v2\/comments?post=347494"}],"version-history":[{"count":1,"href":"https:\/\/www.xamai.com\/en\/wp-json\/wp\/v2\/posts\/347494\/revisions"}],"predecessor-version":[{"id":352935,"href":"https:\/\/www.xamai.com\/en\/wp-json\/wp\/v2\/posts\/347494\/revisions\/352935"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.xamai.com\/en\/wp-json\/wp\/v2\/media\/350164"}],"wp:attachment":[{"href":"https:\/\/www.xamai.com\/en\/wp-json\/wp\/v2\/media?parent=347494"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.xamai.com\/en\/wp-json\/wp\/v2\/categories?post=347494"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.xamai.com\/en\/wp-json\/wp\/v2\/tags?post=347494"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}