Definition of Artificial Intelligence

Artificial Intelligence (AI ) is a field of computer science that seeks to develop algorithms and systems that can perform tasks that normally require human intelligence. This includes tasks such as pattern recognition, machine learning, natural language processing, and decision making.

Types of Artificial Intelligence

Artificial Intelligence is divided into two main categories: weak AI and strong AI.

  • Weak AI, also known as “ applied AI ,” focuses on solving specific problems by using algorithms and machine learning techniques. For example, speech recognition and face detection are examples of weak AI.
  • Strong AI, also known as “ general AI ,” seeks to develop systems that can perform tasks that can be performed by a human . This includes the ability to understand natural language, the ability to reason, and the ability to learn. Although strong AI has not yet been achieved, research is underway to develop increasingly sophisticated systems. 

In short, Artificial Intelligence is a discipline that seeks to develop algorithms and systems that can perform tasks that normally require human intelligence such as learning, pattern recognition, natural language processing and decision making.

Applications of Artificial Intelligence in Industry

In industry, AI is increasingly being used to improve the efficiency, quality and safety of processes, products and services. Some of the most common applications of AI in industry include: 

Preventive Maintenance:

Artificial Intelligence is used in industry to analyse data from all types of sensors and detect patterns that may indicate equipment failure and future breakdowns . This allows companies to proactively schedule maintenance before a failure occurs, reducing downtime, repair costs and avoiding interruption of production or service.

Data processing:

AI is being used to analyze large volumes of data, such as machine sensor data, to detect patterns and trends that can help companies improve their processes and increase efficiency .

Industrial process control:

AI is being used to control and optimize industrial processes, such as factory production, through the use of machine learning algorithms and model-based controllers. One use is also automatic product inspection by performing quality level classifications or detecting breakages.

Robotics:

AI is being used to control industrial robots, allowing companies to automate dangerous or repetitive tasks , such as loading and unloading materials.

Security:

AI is being used to improve security at industrial facilities by using technologies such as facial and object recognition , as well as video analytics to detect potential threats.

Non-industrial applications:

AI is also being used in customer service, healthcare, banking, transportation, energy, agriculture and manufacturing. However, its application in industry is proving especially valuable due to the need to improve efficiency and safety in processes.

It is also important to mention that AI presents some challenges and concerns, such as data privacy and security. These and many other aspects are part of the discussions and improvements that a technology as futuristic but already real as Artificial Intelligence still needs.

Artificial Intelligence in Edge Computing

Artificial intelligence algorithms can not only be processed on large computers in the cloud or data centers, thanks to the continuous optimization of programming languages ​​and computing in general, it is possible to perform tasks based on Artificial Intelligence “locally” or in what is known as ” edge computing “.

From a Raspberry Pi to a graphics card to a VITRIKO industrial router,   they are all perfectly valid devices for doing this type of processing.

Specifically, NVIDIA is one of the manufacturers that is gaining the most prominence since its cards are capable of performing high-performance computing in local mode.

In the case of VITRIKO, as mentioned, equipment such as the IR5G-Heavy industrial router with 1GHz CPU and 1GB RAM is enough to perform Edge Computing tasks based on Artificial Intelligence models, such as video analysis (people counting, license plate reading, etc.)

Local computing with Artificial Intelligence technology presents great advantages in critical processes thanks to:

  • High processing speed due to lower latency.
  • Predictive insights through proactive and preventative problem resolution.
  • Increased uptime as information processing can take place even without a network connection.
  • Local filtering of relevant data obtained from data considered irrelevant.