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Artificial Intelligence (AI) is a field in which machines are programmed to learn and perform functions. Some of these functions were previously unique to human beings, such as recognizing facial expressions, analyzing reports, and even making decisions based on facts that have already occurred. When AI becomes part of a company's structure, productivity levels are accelerated and perfected, as many tasks are passed on to robots and the workforce can be created in a strategic and lean way, ready to perform specific processes. We can experience Artificial Intelligence (AI) in situations that have already become part of our routine, such as search engines. When two people perform the same search in a virtual search engine, the results obtained will not be identical. This happens because there is an AI system that recognizes the consumer's habits within the website. Another classic example is bank credit analyses, which, in just a few moments, are able to cross-reference data and understand the customer's economic power. The goal that large companies have when they implement AI systems may seem economically ineffective, since in theory some employees lose their jobs. However, what happens is a better utilization of the truly humanized function of each person, which adds value to the company: now, the corporation gets rid of the need for an excessive workforce, and manages to move at a faster rate of growth and operation.
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Exponential organizations and accelerated growth
The concept of Exponential Organizations is linked to the idea of disruptive technology, which is when a new system enables the emergence of a solution that transforms the way something is consumed. When a segment manages to cause this disruption, it brings a market change effect that is beneficial to both the organization and the consumer. While the company optimizes its processes, reduces costs, and works with specific and reliable data, the client has access to an effective, simple, more cost-beneficial, and easily accessible product. Organizations that grow exponentially are those that bet on factors such as innovation and disruptiveness to develop, in other words: they are organizations that use Artificial Intelligence (AI) to grow strategically, understanding market pain points and producing what it needs in an innovative way. A survey conducted by the Boston Consulting Group evaluated that 85% of executives understand that investing in AI can take a company to a higher level, thus fostering the degree of competitiveness in the market. It is undeniable that, besides bringing solutions that address market pain points effectively and affordably, AI is allied with another important scenario: the ability to predict situations that may happen in the future, analyzing the strengths and weaknesses the company has to deal with them. This way, leaders and managers work with wider windows of time to solve problems, in addition to reliable data to make decisions.
Machine Learning, the self-taught technology
Freely translated as machine learning, Machine Learning is one of the segments of Artificial Intelligence (AI), more specifically the one that analyzes a large volume of information, extracts what is necessary, and makes decisions based on that. In a Machine Learning process, human interference is minimal, and the results happen through the machine's own experience. The main purpose of Machine Learning is to make a task be performed at its maximum efficiency, surpassing the work that a human could do. A classic example is the smartphone apps used for transportation, such as Uber and Cabify. These apps, in addition to providing the passenger transport service, still provide precise information about the car's location and route, as well as calculating the time and value of the ride. This entire process is done through Machine Learning; the platform identifies data from past rides and adapts according to the specific need of the client, combining information about routes, detours, time, and cost-benefit.
Pix Force develops AI solution capable of solving Mining Industry pain points
In partnership with Eneva, Pix Force has developed a technology that, when deployed on drones, is able to ensure greater efficiency in the inspection of conveyor belts, solving common problems within the mining sector. Seeking to optimize the sector's processes, the technology is capable of performing tasks previously common to human employees, such as equipment supervision and evaluation. In this way, greater efficiency in results is achieved, while safety is maintained. Called Deeptrack, the solution is equipped with infrared and RGB sensors that, when flying over the length of belts responsible for transporting ore and other inputs, can indicate individual temperatures and the georeferenced location of each roller. After capturing images, Deeptrack also integrates this information into a comprehensive platform for tracking the historical records of each inspection, providing data such as individual temperatures of the inspected rollers, conveyor alignment, and detected anomalies. Built through Artificial Intelligence (AI) applied to computer vision, Deeptrack is a Machine Learning solution that promotes efficiency, agility, and safety for the sector, in addition to having a great cost-benefit ratio compared to manned aircraft and the human inspection currently applied in the market. Likewise, the solution prevents human workers from being placed in risky situations and is able to anticipate the resolution of problems that would generate costs for the company.
Fabio Caraça
Fábio Caraça is the Chief Growth Officer at Pix Force. He leads Pix Force's transformation into a scalable SaaS operation, combining strategic vision, culture, and high-impact execution.
