Due to digital transformation, let’s learn about some of the Deep Learning applications already present in business operations.
It doesn’t matter which platform you interact with. Siri, Cortana, Google Home, or Alexa — virtual assistants or agents rely on deep learning to replicate human speech and provide a more natural interaction.
Virtual agents represent the most efficient and economical way companies deal with the new reality. This technology was developed to automate telephone and internet chat services.
This has become possible thanks to integrating Artificial Intelligence into customer interaction. Virtual agents can understand the user’s needs and present a precise solution without human intervention.
A virtual agent is, therefore, an attempt to replicate, through technology, what a human agent does. When implemented with quality, the virtual assistant guarantees the company a more pleasant, objective, and error-free service. In addition, the virtual agent’s results can be easily measured, so your schedule is always up to date.
With virtual agents, the paradigm is different; it is unlimited. In the future, in the same way that you have today, a human being assisting and managing to take things forward, there will be a robot that will be able to do the same things, and this is the differential of the technology that we are presenting here.
This tool allows for personalized, quick, and practical service, allowing it to be used in all market segments and integrated into any messaging platform — with access from a computer, notebook, smartphone, or tablet.
In the same way, a system can understand a language to communicate; it is possible to work with more languages simultaneously and perform automatic translations. A feature like this gives professionals access to efficient and fast translations. The trend is that, as technology evolves, the quality of deliverables will improve, and the process will happen in less time.
Vision For Self-Driving Cars
Amid discussions about labor rights linked to the process of delivering goods and even drivers’ work for trips, autonomous cars may take on functions like these in the future.
With Deep Learning, cars can efficiently learn the realities of a highway, knowing how to respond quickly to signals and predicting the movement of vehicles and people along a given path.
The more data available, the greater the ability of an autonomous vehicle to learn and know how to react to each situation, even if, for example, there are situations such as poor visibility of road signs on foggy days.
A chatbot must have already served you. They can understand what people want to say and develop satisfying and intelligent responses in virtual service processes. As deep learning has grown, systems are more capable of responding to customers. In this process, the trend is for customer service to become completely independent.
The possibilities for facial recognition go beyond security issues. In the future, making payments in stores with just face identification will be possible.
However, for the technology to gain maturity and reliability, it is necessary to detect even when faces undergo significant changes, as with haircuts or signs of natural aging.
It is possible to make personalized diagnoses and treatments. All considering the patient’s genome. As a result, the tendency is for medications to be more effective, as they will meet people’s specific needs.
Finally, it’s important to note that you can already use Deep Learning and Machine Learning in the customer experience. Therefore, it is time to research and pay attention to market transformations. Not all functionalities will be compatible with the business model that your company operates, but, knowing different cases, it is possible to have interesting insights on how to improve processes and achieve more satisfactory results. The faster your business adapts, the better it will be!
Also Read: Deep Learning: How Does It Improve Company Processes?