3 min read

Edge AI: discover the new limits of Artificial Intelligence

If you follow our blog, you’ve probably heard of the term Edge Computing. Now, let’s present a similar concept, but related to Artificial Intelligence: Edge AI.

Ten years ago, we would not imagine that Artificial Intelligence would be at today’s levels. Now, it is part of industries and even devices for customer service. The time has come to take a step forward. The new frontier is Edge AI.

In today’s post, you will understand what this concept is and why you will hear it a lot in the coming years. 

What is Edge AI?

Edge AI is the processing of Artificial Intelligence algorithms on edge, that is, on users’ devices. The concept derives from Edge Computing, which starts from the same premise: data is stored, processed, and managed directly at the Internet of Things (IoT) endpoints.

As a result, the device does not necessarily need to be connected to Edge AI, as the data is processed right there for Machine Learning purposes. Besides, they can apply Deep Learning models and advanced algorithms autonomously.

How does Edge AI work in practice?

As we have seen, Edge AI relies on the devices’ own hardware for processing data and processes related to Machine Learning and Deep Learning. But how does this work in practice?

A good example could be virtual assistants, such as Alexa or Google for example. They learn from the user’s words and phrases and can store them directly on the device.

Thus, in addition to not necessarily depending on the internet connection to perform all functions, IoT devices achieve a much longer response time for the user.

Of course, this is just an example. Later, we will see more possible applications in the future. The fact is that we are still witnessing the advances that this type of application can bring to people’s daily lives and industries in general.

What are the 4 benefits of Edge AI?

A technology like Edge AI can bring several benefits, especially for the industry, which relies more and more on IoT devices. Next, we will list some of them:

  1. Reduced latency to improve the user experience
  2. Integration between wearable technologies, such as bracelets
  3. Reduction of the necessary bandwidth and, consequently, of the costs of internet services
  4. Greater security and privacy of data, since the processing is done locally and not in the cloud.

Why will Edge AI be important?

Facial recognition, traffic updates on smartphones, autonomous vehicles, and smart devices. The list of devices that today have computing solutions at the edge keeps growing. Soon, they will no longer be new and will be in everyone’s homes.

Edge AI surfs this movement since the need for data processing on the devices themselves also represents the increasing use of Artificial Intelligence. Shortly, we will see more of Edge AI meeting the following needs:

  • Improvement in autonomous vehicles, which will start to identify images much more quickly for decision making;
  • Intelligence for security cameras, detecting suspicious activity in real-time;
  • Reduce costs and improve IoT security in industries;
  • Use in the medical field for emergency care and surgeries.

The future for companies

Have you ever stopped to think about what benefits this type of solution can bring to your business? Only taking into account what we have explained so far, it is possible to see that Edge AI brings benefits to many industry sectors.

The financial market, for example, can count on greater security in transactions and fraud detection. The insurance market also sees benefits, especially when considering telemetry devices.

The future of computing is at Edge, and your business needs to face that reality now to present disruptive solutions in the future. Edge AI is just one example of how we can deliver products and services connected with consumers’ needs. 

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