What is artificial intelligence and how does it work

Artificial intelligence (AI) is a branch of computer science that deals with the construction of smart machines capable of performing tasks that usually require human intelligence. AI is an interdisciplinary science with multiple approaches, which creates a paradigm shift in most sectors of the technology industry. Devices that use artificial intelligence try to reproduce human behavior as much as possible.

Artificial intelligence systems are supported by algorithms, using techniques such as machine learning, deep learning, and rules. Machine learning algorithms provide computer data to AI systems by using statistical techniques to enable AI systems to learn. Through machine learning, AI systems become progressively more efficient in performing tasks, without the need to be specifically programmed to do so.

Artificial intelligence falls into three categories

  • Artificial general intelligence (AGI), also called “strong AI”. It is the kind of artificial intelligence that allows the understanding and learning of any task related to the intellect that a human being can perform. AGI can think, understand and act in a way that is indistinguishable from the human in certain situations.

  • Artificial narrow intelligence (ANI), also called “weak AI”. This type of artificial intelligence works in a limited context and is a simulation of human intelligence. Narrow AI focuses on performing specific tasks but has some limitations. Examples of Narrow AI: Siri (from Apple), Alexa (from Amazon), Google Search.

  • Artificial superintelligence (ASI). This is, hypothetically, that artificial intelligence that not only understands and imitates human behavior, but machines become self-aware.

How artificial intelligence works

Artificial intelligence works by processing data using advanced algorithms. It combines large data sets with its algorithms, learning from data patterns or characteristics. In order to understand how artificial intelligence actually works, one must analyze its different subdomains.

  • machine learning (ML) teaches a machine how to make decisions based on past experiences. It is based on the idea that systems can learn from data, identify models and make decisions with minimal human intervention. Two of the most popular machine learning methods are supervised learning and unsupervised learning. Supervised learning algorithms are trained using labeled examples, such as an input where the desired result is known. Through methods such as classification, regression, and prediction, supervised learning uses models to predict label values ​​on additional unlabeled data. Supervised learning is frequently used in applications where historical data predict probable future events. Unsupervised learning is used with data that has no historical labels. The system is not called the “correct answer.” The algorithm must realize what it looks like. Unsupervised learning works well on transactional data. These algorithms are also used to segment text topics, recommend items, and identify abnormal data values.

  • deep learning (DL) is a function of AI that mimics the functioning of the human brain in data processing and creating models for their use in decision making. Deep learning is a subset of machine learning in artificial intelligence that has networks capable of learning unsupervised from unstructured or unmarked data. Deep learning teaches a machine to process inputs through layers to classify, deduce and predict the result. Deep learning can be used to detect objects, recognize speech, translate languages, and make decisions.

  • neural networks. A neural network is a series of algorithms that try to recognize relationships in a data set through a process that mimics how the human brain works. Neural networks operate on principles similar to human neural cells.

  • natural language processing (NLP). Natural language processing is a science of reading, understanding, interpreting a language by a machine. From the moment a car understands what the user intends to communicate, it responds accordingly.

  • computer vision. Computer vision algorithms try to understand an image by decomposing it and studying different parts of objects. This helps the car to classify and learn from a set of images, to make a better decision based on previous observations.

  • cognitive computing. Cognitive computational algorithms try to mimic the human brain by analyzing text, speech, objects, and images in the way a human would, and try to give the desired result. Cognitive calculation tends towards a natural, human-like interaction with cars.

Why is artificial intelligence important?

AI automates repetitive learning at the human command and does it with incredible precision. It helps to advance technologies that keep us safe, such as detecting certain diseases and other health problems, safer driving, helping in business, etc. The possibilities are endless.

Today, artificial intelligence can perform the following actions: learning, speech recognition, planning, reasoning, perception, problem solving, manipulating and moving objects. This allows people to be smarter, helping us to analyze, learn and act faster than we can without technology.

Advantages of artificial intelligence:

  • 24/7 availability;
  • increased security;
  • digital assistance in various fields;
  • reduction of human errors;
  • automation;
  • helps make decisions faster;
  • increase efficiency.

Applications of artificial intelligence

Artificial intelligence has many applications in various fields:

  • medical: administration, assisted diagnosis, robots used in operations, telemedicine, monitoring of vital signs and alerts in case of their modification;
  • human resources: rapid analysis of CVs and selection of suitable candidates based on the criteria established by the company, distribution of employees in different teams and projects based on skills and other data about them;
  • automotive: robots that assemble cars and autonomous cars;
  • e-commerce: better recommendation engines, chatbots, mass emails, spam removal, demand predictions to help manage stocks.

In e-commerce, it is very important that a platform can support customers with some product recommendations as relevant as possible. One platform that has such a well-developed search engine is VTEX, which with the help of VTEX Intelligent Search can give the business an AI-boost.

VTEX Intelligent Search helps increase conversion rates with an advanced search engine that uses artificial intelligence to understand buyers’ intentions and return the most relevant search results. With this search engine, you gain visibility and control over AI, and you can influence it to get the best results for your business.

AI-powered VTEX algorithms offer autocompletion, spell checking, synonyms, and instantly suggest terms and products, all while the customer interacts with the search bar. Specific products can be promoted based on user behavior by defining triggers, for example the search terms or applied filters. These triggers will add, remove or promote products, brands or categories.

See here more about artificial intelligence in e-commerce!

The examples of uses of artificial intelligence mentioned above represent only a small part of its applications. The technology is currently used in many sectors, including transportation, finance, education, etc.

The impact of artificial intelligence is increasingly present in society. Some companies have understood this, and have chosen to use AI to increase their profits and be one step ahead of their competitors.

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