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“Our intelligence is what makes us human, and Artificial Intelligence is an extension of this quality,” said Yann LeCun, a professor at New York University. Artificial Intelligence and Machine Learning have been widely discussed topics among computer enthusiasts and scientists in recent decades.
From this trend, we have seen the emergence of science fiction movies depicting apocalypses caused by the “machine revolution”, as well as the development of devices like Amazon’s Alexa or Apple’s Siri, which respond to commands and answer questions from users.
Artificial Intelligence and Machine Learning are two fields of study that are often correlated but have conceptual and usage differences. In this article, we will discuss their characteristics, functions, and ultimately their differences.
What is Artificial Intelligence?
The term, created in 1956 at a conference on the Dartmouth College campus in New Hampshire, United States, was proposed by McCarthy, Marvin Minsky, Nathaniel Rochester, and Claude Shannon. It represents the branch of computer science that seeks to create resolutions so that machines can receive data and make decisions based on their own interpretation – mimicking human behavior – through learning and generalization algorithms that simulate human capabilities.
To demonstrate the great potential of using AI in large companies, here are some examples of success:
■ UPS: The giant American logistics company achieved annual savings of approximately $400 million through the use of AI-based applications. This significant amount is due to a more accurate selection of delivery routes, simultaneously considering traffic, travel time, and road quality. This made delivery routes much more efficient.
■ Netflix: The largest movie and show streaming company has been increasingly implementing AI solutions in its recommendation system. Its latest implementation brings a novelty: recommendations based on movie covers.
According to the subscribers’ recent movie viewing history, cover images are changed to better influence their decision-making, aiming to keep them on the platform for longer and avoid frustrations with the available content, as well as possible cancellations.
■ Bradesco: one of the giants in the Brazilian financial sector, Bradesco obtained a 70% satisfaction rate with its services performed by robots through the bank’s app, which led directors to double their investment in this department in recent years.
Currently, AI is related to several areas of study, such as psychology and biology, neural networks, mathematics, and engineering with complex calculations and many other scientific areas. Machine Learning, one of the subdivisions of AI, emerged to meet this range of studies and applications,
What is Machine Learning or Machine Learning?
“Machine Learning is a field of study that gives computers the ability to learn without being explicitly programmed,” said Arthur Samuel, the creator of the concept that emerged in 1959. As stated by him, Machine Learning is a subfield of AI that aims to study the processes and programming necessary for machines to undergo the learning process and achieve a learning curve similar to humans. In other words, this basically means computers learning through experiences.
A simple example of Machine Learning is the video below, which briefly shows a neural network learning to play the classic game Snake:
Demonstrating Machine Learning in the business field, we have American Express, which uses AI systems with Machine Learning to manage over 110 million cards and transactions worth trillions of dollars. The company’s main objective is to identify potential fraudsters and prevent million-dollar losses.
What are the prospects for the future?
Moving away from theory and talking about business perspectives, the AI market has significant growth expectations, with innovative and highly profitable applications for companies of all sizes and sectors. According to the Brazilian Association of Software
Companies (ABES), 15.3% of companies in this sector are using AI solutions in their operations.
Current perspectives indicate that this number will double by 2023, making the market more automated, and efficient, and improving customer service in various aspects. With this scenario in mind, the Inter-American Development Bank (IDB) stated that in the year 2020, the Brazilian GDP may have grown up to 4.1% due to a wider dissemination of AI technologies in the market.
With the imminent growth in the need for software that automates processes, manages documents, and analyzes indicators, as well as caters to an increasingly computerized business market seeking innovation and agility in their operations, the Fusion Platform comes to light.
The platform offers BPM (Business Process Management), ECM (Enterprise Content Management), and Analytics solutions, bringing tools that aim to improve companies’ business outcomes by reducing internal bureaucracy, and accelerating, ensuring, and facilitating the execution of internal and external processes. Additionally, it stores and organizes documents and has an indicator analysis system to assist managers in their day-to-day tasks.
Conclusion
Artificial Intelligence is the ability of certain computer systems to simulate human cognitive capabilities, automating decisions and processes through specially developed algorithms. Machine Learning is the method used by Artificial Intelligence to evolve on its own, focusing on the learning and self-development of machine “intelligence” without the need for human intervention.
Therefore, it can be concluded that they are different things but do not exist independently, as each of their modus operandi depends on the other. The prospects for the future, both in Brazil and worldwide, are exciting and demonstrate a vast horizon of implementation and market growth for AI and ML in business automation, across companies of all sizes and market segments.
To learn more about AI and many other topics in the field, visit the Neomind Blog. Haven’t heard about Fusion Platform? Test it for free for 15 days!
