In recent years, Artificial Intelligence has brought to our daily lives several products and solutions that have changed our routine and even social interactions. Today it is possible to buy products through e-commerce and be served by a chatbot, analyze Big Data with a Business Intelligence application, help your customers in an omnichannel way, and schedule payments directly from your smartphone screen.
The evolution of Artificial Intelligence has enabled all this. Transformations are always coming, and your business needs to follow the impacts. Below, check out the top 10 AI trends!
This concept is that cars can work without needing a human being to drive them. The development of this solution is in progress. However, it has not yet been made available for commercial use. The idea is that autonomous vehicles can contribute to reducing traffic accidents – 1.35 million people die each year – and increase productivity and mobility.
Part of Generation Z (born after the mid-1990s) and all of the Alpha generation (born after 2010) were already held in a society marked by digital transformation. The connected world is part of their reality: tinkering with smartphones and apps is as natural to them as walking.
Traditional education no longer has space; it does not meet the cognitive needs of the new generations. Thus, the reality of schools is changing: technology is reaching the school environment. With Artificial Intelligence, it is possible to develop an application focused on learning that maps the most frequent doubts of the students.
In this way, classes and activities can be customized according to each student’s difficulties, enhancing learning. In this scenario, the teacher assumes the position of facilitator and the student of executor, as he is conditioned to the stimuli most adhering to his profile. This can even be migrated and adapted to the context of people development and training in organizations.
The need for isolation made people and businesses adapt to continue the routine. The high risk of contagion inaugurated the modality of virtual consultations to verify the probability of a patient being contaminated with the new coronavirus during the pandemic.
This scenario is being seen as embryonic for the development of new technologies applied to medicine that will be able to diagnose a patient remotely through exams carried out on the spot. Imagine your smartphone could be used to identify a fracture, for example. This may not be that far off. After all, today, it is possible to count your steps and caloric expenditure and measure your blood pressure using a digital bracelet.
Internet Of Things
Also known by the acronym IoT (Internet of Things), the internet of things is a technological concept that advocates the integration of objects we use in everyday life with the digital environment. Some existing solutions include this proposal, such as some car models whose keys are applications.
A very close example is the solution developed by the car rental company Localiza for its customers. The brand offers consumers the option of renting through the app, making the payment digitally, and picking up the desired car without going through the service desk: the car is unlocked through the app, and the key is inside the vehicle.
Chatbots are already part of our daily lives, aren’t they? We are more used to interacting with this type of robot. However, voice assistants are expected to gain traction in the coming years. This technology includes Apple’s Siri, Amazon’s Alexa, and Google Assistant.
According to Google, by 2021, 1.6 billion people will use voice assistants regularly. The biggest differentiator of this technology is the ability to develop it to capture the user’s emotions through the voice: this will take the consumer experience to another level.
Following the same idea as autonomous cars, there is a strong tendency for companies to invest more to develop more autonomous solutions, mainly focused on improving the operation of many processes. Today we already find operational flows automated by robots in organizations, but they are simpler executions. Autonomous things can transform some segments, like industry.
About six years ago, portals reported what seemed to be the arrival in the Jetsons’ universe: Amazon announced the registration of a patent for a technology that would allow predictive delivery. In other words, the product would be prepared for shipment even before the customer decides to buy it. This is possible through the analysis of data obtained by Artificial Intelligence software. The brand continues to carry out studies to calibrate the technology.
When it comes to Artificial Intelligence, it is widespread to hear about the concept of machine learning. It corresponds to a robot’s ability to “learn” as it is used. However, another idea has gained space on information technology agendas: deep learning.
Deep learning is an offshoot of machine learning: its functions are similar, but the capabilities are different. Machine learning will always need human interference to guide it. The deep learning model allows the machine to make decisions through its own “neural network.” The Google AlphaGo intelligent computer is an example of this technology.
Last year, during NeurIPS — the world’s largest Artificial Intelligence event —Google’s Artificial Intelligence board announced that it is working on using this technology to reduce carbon emissions to zero. For example, the company is evaluating how to use AI to measure carbon emissions during a user-simulated journey on Maps.
With the scandals of leaking user information, like with Facebook, countries are consolidating stricter regulations to ensure the security of sensitive customer data.
Thus, private organizations need to comply with the law. With this, cybersecurity gained more prominence, and Artificial Intelligence is applied in cloud computing solutions, focusing on deep learning. With AI, it is possible to identify an attack on the information before it does any damage.
IBM, for example, already offers an innovative cybersecurity solution that uses a technology it calls cognitive security: a combination of traditional machine learning and deep learning.