Artificial Intelligence is already used in almost all market segments, as its flexibility and its
technology for personalization contribute enormously to the development of operational tasks and
decision-making.
Between futuristic technology and science fiction films, Artificial Intelligence has become, in fact, a
widely used resource in everyday life, from when we perform a simple action on our smartphone, to
the moment we make an online purchase.
Applications of Artificial Intelligence have become popular and widespread. However, the more we
investigate, the more new uses and potentials are revealed by the advancement of technology ,
proving that there are still many possibilities to explore .
Despite the wide diffusion of technology, many people still have doubts about how it works and how it
can actually be applied in different business segments.
Keep reading this post and understand more about the topic!
What is Artificial Intelligence or AI and how does it work?
The term Artificial Intelligence is not as new switzerland telegram data as it seems. In 1956, Professor
John McCarthy coined the expression to refer to the ability of machines to solve problems that, until
then, only humans could solve.
The concept of AI remains the same: the feasibility of machines thinking like humans ,
developing the ability to learn, reason, perceive, deliberate and decide logically on the
facts .
Another important aspect of AI is that, due to its ability to learn, it must be constantly fed so that it
can continue to evolve as well as a person. As complex as this may be, it is only possible with simple
calculation processes, such as:
- data model: structures for intelligently processing, categorizing, and analyzing data;
- big data : a base that allows large amounts of data to be accessed for processing.
- processing power: operational and logistical capacity to process information quickly and efficiently.
In any case, to understand how AI works, it is necessary to know that there is a combination of technologies that makes it possible.
What technologies enable AI to work?
Artificial Intelligence is made up of use user-generated content codes and data. The former is responsible for reading and interpreting the latter.
However, it is more than just data analysis and, to fulfill a multitude of complex commands that result in the ability to imitate humans, it includes several technologies.
Machine Learning
The first pillar of AI is machine learning, through jiangxi mobile phone number list which computers become capable of learning and evolving. In technology, what happens is the logical processing of data and the identification of patterns that generate intelligence.
Without machine learning , what we understand as artificial intelligence would not materialize. Today, for example, Amazon widely uses the technology to make more personalized and relevant recommendations for customers.
The system works like this: the machine monitors all customer actions on the site and identifies patterns, such as when customers who viewed product X also show interest in Y.
Therefore, when a user performs the first search , the system indicates another product because it recognizes that there is a relationship between the searches.
In Machine Learning, these patterns are identified in infinite networks, so that there are thousands of intersection points that are connections between information, thus allowing large-scale intelligence .
Deep Learning
Another essential concept for the realization of current AI is Deep Learning , which consists of a deepening of Machine Learning, making it more intelligent and complex. The technology uses more sophisticated tools that make the results better.
For example, in the same Amazon example cited, the technology identifies exceptions to avoid making poor quality suggestions.
If out of 1000 customers looking for a smartTV 800 they continue their search with the home theater, the software understands this as a relevant indication.
However, if five users after searching for smartTV start a search for shoes, for example, Machine Learning could understand this as a valid indication.
Deep learning, on the other hand, understands that they are unrelated products and therefore prevents some exceptions in user behavior from becoming a rule.
The technology therefore uses more complex networks to understand that while something is happening, it is not a causal search and therefore not a relevant result for the user.
With this, Deep Learning can understand human thoughts in more detail than Machine Learning.
Natural Language Processing (NLP)
The final pillar of AI is Natural Language Processing, which is responsible for the work of finalizing the results, making them more natural and more human.
For example, many e-commerce companies currently use chatbots to serve their customers. However, the quality of the technology lies in NLP.
When not integrated into the solution, the robot becomes artificial, unable to improve the language used to make it more similar to that used by customers.
The excessive perfection of language and the inability to incorporate more informal elements is what makes the robot become artificial, regardless of the ability to really help the consumer.
What are the benefits of Artificial Intelligence?
Artificial Intelligence has provided direct and indirect benefits to the business, being incorporated into operational stages and strategies due to the multiplicity of possible applications.
Learn about the four advantages that technology has brought to companies.
Automation
AI makes it possible to automate processes with a large volume of information, avoiding the need for humans to perform tasks or even identify patterns.
However, for this, trained professionals are needed to configure the system.
The function is also used in robotic automation , in which operational tasks such as precisely tightening a screw are replaced.
In both cases, technology optimizes processes and improves business performance.
Predictability
Among the applications of AI is the predictability of markets, behaviors and processes due to big data analysis that identifies patterns and establishes predictions based on past events.
Through predictive analytics using Machine Learning and AI, it is possible to consider infinite data and scenarios to identify the most likely events, helping to make more effective and strategic decisions.
Deeper data
Big Data already made systematic data analysis possible a few years ago. However, AI has deepened this interpretative capacity, generating more intelligence from the analysis of information.
Therefore, a company that has a competitor using similar techniques can differentiate itself if it has a good data set and applies AI to identifying patterns and predictions, allowing it to extract more complex and valuable information from the data.
Constant improvement
AI allows for a constant evolution in the use of data because it uses multi-layered neural networks that are used to build more complex and effective interpretive structures.
To adopt Deep Learning, the company needs big data so that the model can learn from this information. Moreover, the more data that is included in the model, the more effective it will be.
How does AI work in practice?
Artificial Intelligence is already used in almost all business segments due to its flexibility and customization of the solution.
With this, examples of technology applications include strategic development, Digital Marketing , consumer relations, new business models, etc.
E-commerces
E-commerce companies use Artificial Intelligence mainly to provide a better experience to the consumer . Among the uses of AI in this area are:
- Identify consumer preferences based on browsing and consumption habits and provide a better shopping experience ;
- make recommendations to customers based on the behavior of others;
- perform integrated customer service, such as using chatbots and CRM .
Through these AI applications, e-commerce becomes more efficient in its relationship with customers .
While giants like Amazon innovate in the use of technologies to obtain competitive advantages, tools and specialized partners, they also promote the adoption of these resources by small and medium-sized stores.