What are the most developed artificial intelligence in recent years?

Today artificial intelligence (AI) is one of the computer areas that is continuously evolving, with new developments and progress emerging regularly.  

It should be noted that this technology has been existed for decades, but it has been in recent years when it has been significantly improved and developed These advances have meant the creation of several technologies that have changed the way we interact with the world. 

The most developed artificial intelligence in recent years 

As we have said before, artificial intelligence will be a key factor this 2023 to improve the competitiveness of the company.  If you want to know that other trends will have a great impact, we leave you our previous  news. Don’t miss it!  

Artificial intelligence is a key element in modern technology, allowing machines to perform complex tasks such as searching and gathering information, natural language processing, decision-making and the most well-known machine learning. 

A variety of applications have been developed in the world of technology, from the automation of processes, the stopping of patterns and the creation of predictive systems, to the creation of autonomous robots. 

Each intelligence has its own characteristics and applications. Below, we present the technologies with the greatest progress in recent years. 

1. Machine learning

Machine learning is one of the AI that we have commented on the most, it is a branch of AI focused on the development of algorithms and systems through which a computer is programmed to learn and improve from data and experiences.  Automating the entire process to get results. 

This intelligence from large organizations includes techniques such as supervised, unsupervised and reinforcement learning. 

  • Supervised learning 

It represents learning that requires label input and output data, used to solve classification and regression problems.  

Classification problems are used to identify or generate diagnoses, such as spam arrest, voice recognition, etc. 

  • Unsupervised learning 

Represents data training, without processing and without labeling. As its name suggests, this learning does not require human intervention compared to supervised learning.  Mostly used to understand the relationship of a large amount of data. 

This type of learning is used for initial data analysis, to understand the relationship between different data points for data relationships with common characteristics. 

  • Reinforcement Learning (RL) 

It represents a variety and another approach to machine learning that gives the ability to plan strategies and model possible scenarios, implementing algorithms that allow and guide decision making based on interaction with the environment. Mostly used in video games, robots. 

2. Natural language processing 

Natural language processing (NLP) is a branch of AI dedicated to computational linguistics, focused on understanding, and generating text in natural language. 

The goal of (NPL) is to create programs that can analyze and understand human language, such as speech and writing, processing information that makes sense and obtain meaning, that is, they are based on the understanding of grammar, semantics, and vocabulary.  

These programs are the interaction between human beings and computer science, currently used in applications such as machine translation and information search.  

The clearest examples are the best-known applications created such as chatbots, virtual assistants and sentiment analysis systems. 

3. Computer vision:  

Computer vision is a branch of AI that studies how to extract information from digital images and video games.  This technology can be used to track and recognize objects and people and events captured digitally by cameras. All this is possible thanks to the use ofgorhythms, image processing techniques and custom software.  

This technology can be used in a wide variety of fields, from facial recognition to video surveillance systems, satellite image processing, object identification in robotics, etc. 

Examples of computer vision applications include facial recognition systems, object tracking, and autonomous driving. 

4. Robotics 

Robotics is an interdisciplinary field that combines AI with mechanics and electronics to develop robots that can perform automated tasks. 

It should be noted that these are two different concepts. Although, from AI, robots are programmedto perform unlimited tasks. 

Collaborative robotics has become one of the unavoidable technologies for industry 4.0, the digitization of artificial intelligence products, the development of the internet of things and virtual reality.  

While according to sources such as Precedence Research, it estimatesthe market for artificial intelligence (AI) robots will be worth 54.3 billion by 2030.”  

If you want to know which the most developed robots are due to Artificial Intelligence. Next, I leave you a  very interesting article about its features and functions. 

CENTUM DIGITAL specialists in the field of technology  

From CENTUM Digital we are aware of new technologies and all the impact they have on companies. 

Thanks to our extensive experience, both in the field of electronic engineering and in the world of software communications. We offer solutions that optimize industrial processes and the use of Big Data algorithms and artificial intelligence. 

Learn more about us

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