Artificial Intelligence (AI) is already part of our day to day and helps us to improve and evolve many sectors of our society. Within organizations, it collaborates in increasing productivity, potentializing results, and reducing costs. Some of those improvements are due to machine learning and deep learning, which are forms of artificial intelligence.
Machine learning is a technology in which computers are capable of learning and responding based on analyses from different kinds of data. It manages to aggregate value for enterprises which try to interpret a large volume of data and helps them to better understand consumer preferences and behaviour changes.
Deep learning, in turn, is useful for non-structured data patterns and it is increasingly set in the routine of organizations. A specific method which uses more complex algorithms than machine learning, a machine"s deep learning incorporates neural networks so as to learn with data and generate effective results from them. The main point in common between machine learning and deep learning is to make machine reasoning closer to that of humans.
Presence in every market
Those technologies are part of every market and are a reality on the everyday of a number of enterprises. Data from the Global A[rtificial] I[ntelligence] Survey by McKinsey in 2020 show that organizations are using artificial intelligence as a tool to generate value, adopting it in service operations, product development, and marketing and sales.
The same survey also indicates that 16% are for the first time taking deep learning beyond the pilot stage in their business. Now in high technology and telecommunications enterprises, the incorporation of resources from deep learning reaches 30%. In response to the pandemic, 61% increased their investments in AI, showing that the economic challenges of the period did not impede evolution of the technology.
Hypercubes, a startup we invest in, founded in 2015 by entrepreneur Fábio Teixeira, develops technologies which will help big enterprises and world leaders to make more intelligent decisions. Based on analyses of data obtained through information from nanosatellites present in the space, which monitor and photograph the Earth, it will be possible to analyse different aspects, to identify and detect problems. "Artificial intelligence enables us to find information within data, because they alone don"t mean anything", declares Fábio.
Technologies for optimization of processes
Hypercubes nanosatellites will make analyses of our planet, allowing organizations to see what has never been seen before and to have useful information for assertive decision-making. An autonomous search mechanism, which allows providing precise information in a simultaneous way. "We can only improve what we measure ? it"s necessary to have metrics, it"s necessary to understand today whether we perform better or worse than yesterday", completes Fábio.
The startup major focus is on agrobusiness, soil monitoring and data supplying for rural producers so that they identify diseases, anomalies, invading species and plagues, and thus they can understand specific needs of each plantation; making possible to produce more food with less resources, in a more sustainable way and in larger quantity, attaining the startup major objective, which is to put an end to hunger in the world.
The developed solutions are promising for various productive sectors, the analyses of geo-spatial data create ways of identifying different aspects on very detailed images. With those technologies it is possible that enterprises accomplish studies more rapidly and efficiently, in order to lessen reworking by teams and increase productivity capacity.
Future of Hypercubes
Hypercubes is going to quantify global resources at a large scale every day, and through artificial intelligence understand and make the forecast of a farming production, for example, even before its harvest. "Through artificial intelligence, we produce customized models for identification of parameters, processing data within the satellite almost in real time, which has a lot of value for the industry", declares Fábio.
Man and machine work together; from the human, the intelligence and experience of decades come in order that, through technology, it is possible to escalate that knowledge, that is, the machine looks for that which the producer has taught it so. "We train the system to identify cases of specific use", the founder explains.
In 2021, the startup predicts to send a prototype into space, which will be installed for the performance of the first tests. When soil analyses begin, machine learning and deep learning will be essential for the active monitoring and building of intelligent information.