The idea of a “thinking machine” was born with the British mathematician and cryptographer Alan Turing in 1950, and has been evolving ever since. Today, whether or not you work in technology, artificial intelligence is a very everyday topic.
What is artificial intelligence and how does it work?
Artificial intelligence is a technology that makes it possible to create machines and computer systems that operate with some autonomy by simulating human behavior.
In general, AI is trained by absorbing a large amount of data, from which it searches for patterns and associations. This information is processed so that it can simulate predictions of future events and, thus, make decisions.
The advantage of artificial intelligence over an ordinary worker is the volume of data it can evaluate and process in a short period of time. AI-powered software can absorb information 365 days a year, 24 hours a day without breaks, which easily surpasses the human capacity for learning.
Where can we find artificial intelligence?
Artificial intelligence is present in many segments of society, such as industry, medicine, transportation, the economy, and education, among others.
Some examples of software that uses the technology and is currently in the spotlight are DALL-E 2 (artificial intelligence that creates images, and a chatbot that uses AI to perform written tasks), voice assistants such as Siri and Alexa, and the content recommendation algorithms seen on social networks and streaming platforms.
How does an artificial intelligence think?
Artificial intelligence is able to learn thanks to the instructions in its program code. It is the algorithms that determine what knowledge the AI should or should not acquire.
From there, the technology is exposed to thousands of patterns so that it can recognize elements and thus handle different situations autonomously. In this process, machines are exposed to a large volume of data and, through analyses and statistical models, identify patterns and trends.
This system is known as “machine learning” and allows machines, over time, to make increasingly accurate predictions and make autonomous decisions.
Within this process, there are two types of learning: Machine Learning and Deep Learning.
Machine learning acquires knowledge through the collection, organization, and categorization of a dataset. With it, AI can interpret information to make decisions and perform tasks automatically and autonomously.
Deep learning simulates neural networks in a process similar to human intelligence. In this format, the system is able to understand information in a more complex and in-depth way. With it, AI can learn without as much human intervention and recognize images and speech more accurately.
What are the types of artificial intelligence?
Artificial intelligence can be classified into three types: artificial narrow intelligence (ANI), artificial general intelligence (AGI), and artificial superintelligence (ASI). In addition to this nominal classification, they are also divided into the “weak AI” and “strong AI” groups.
- Weak AI. artificial narrow intelligence (ANI) is an example, as these are systems trained to perform a single specific task, such as driving a vehicle, searching the internet, or playing chess.
- Strong AI. examples are artificial general intelligence (AGI) and artificial superintelligence (ASI). AGI is focused on simulating human intelligence, with the ability to handle many different tasks, make decisions, solve problems, and plan for the future. ASI, in turn, aims to surpass the intellectual capacity of the human brain. Artificial superintelligence is a technology still under development in the scientific world and, with it, it would be possible to solve complex calculations that are humanly impossible.
Understanding the artificial intelligence landscape in industry
Artificial intelligence is considered essential to the digital transformation of society and is increasingly becoming a priority for the world's major powers.
In the industrial setting, AIs are increasingly optimizing their results, and new demands arise in the attempt to reach their maximum degree of efficiency. The concept of artificial intelligence has been used to refer to predictive analytics, augmented reality, robotics, performance diagnostic software, and many others.
But how do we understand the performance of each of these applications in industry? In this section we provide information that can clarify this and other questions about the impact of automation on industry through Artificial Intelligence.
Artificial Intelligence delivers optimized results for industry through efficient solutions
The enhanced capabilities provided by AIs can contribute to industrial operations in several ways, such as:
A safer work environment
Machines can withstand extreme conditions that would be harmful to the health of an industrial plant's employees. Cooling chambers, chemical processes, and the handling of explosive materials, for example, can be carried out through automation. Safety alerts that point to the need for maintenance, and real-time performance reports indicating the best measures to take, are also very useful features.
Increased productivity
With entire procedures carried out by machines capable of making data-driven decisions, agility and increased productivity are natural consequences. The investment in modernizing industrial processes is quickly offset by better production results.
Cost reduction
New technologies are developed to work using the smallest possible amount of resources in terms of raw materials and energy consumption. Therefore, mitigating errors and operational waste are considerable advantages.
Higher quality of products and services
Artificial intelligence reduces execution errors and uses operational data to analyze performance and make improvements, which is why production quality is always advancing.
New, more effective products and services
With the ability to evaluate proposed designs, identify material variables and weak points to be improved, and use augmented reality to run tests before going into production, AI provides an efficient and original process.
Each industry sector receives contributions from artificial intelligence in a different way. Companies with strong logistics and inventory structures, for example, can benefit from this technology to identify and control demand.
Industries with production chains that include many machines, such as the automotive industry, also see great effects from the use of predictive analytics to identify the need for maintenance on their machines.
Enacom has been developing Artificial Intelligence solutions since 2009 for the Energy, Logistics, Steel, Healthcare, and Sustainability sectors. This technology presents many possibilities for the future of industry, and its results tend to be increasingly significant.
Talk to Enacom's experts and apply Artificial Intelligence capabilities to your company's production processes.