AI Edge Consulting helps businesses implement Artificial Intelligence in their operations, marketing, finances, HR – virtually any part of the organization. Exponentially growing capabilities of technology allow any business to leverage the power of Artificial Intelligence, and it is our mission to help you get there first.
Why use Edge AI?
In today’s world of ubiquitous data and exponential technologies it has become commonplace for companies to leverage disruptive technologies such as Deep Learning and Artificial Intelligence to enhance their operations. And yet experts predict that 40% of today’s Fortune 500 companies will no longer exist in 10 years. Why?
Even when a business is determined to disrupt itself from inside it may face challenges. It may be hard to see things from within that are obvious from without. That’s where AI Edge Consulting comes in. We help businesses see their operations from a different lens and with a fresh perspective in mind we facilitate disruptive innovation.
The future of Artificial Intelligence is on the Edge
Edge AI is a system that uses Machine Learning algorithms to process data generated by a hardware device at the local level. The device such as an IOT device does not need to be connected to the Internet to process such data and make decisions in real time, in a matter of milliseconds. This EDGE system considerably reduces the communication costs derived from the cloud model.
EDGE AI promotes IoT devices
Edge AI takes the data and its processing to the closest point of interaction with the user, whether it is a computer, an IoT device or an Edge server.
Siri or Google are perfect examples.
An example of this technology can be seen in the speakers of Google, Alexa or the Apple Homepod, which have learned words and phrases through Machine Learning and then stored them locally on the device. When the user communicates something to applications such as Siri or Google, they send the voice recording to an Edge network where it is passed to text via AI and a response is processed. Without an Edge network the response time would be seconds, with Edge the times are reduced to less than 400 milliseconds.
Benefits of Edge AI
Some of the main advantages offered by Edge AI are:
- Reduces costs and latency times for an improved user experience This facilitates the integration of wearable technologies focused on the user experience, where you interact in real time to make payments, or where bracelets monitor your exercise and sleep patterns.
- It increases the level of security in terms of data privacy through local processing. Data is no longer shared in a centralized cloud.
- Technically, the reduction in required bandwidth should lead to a reduction in the costs of the contracted internet service.
- Edge technology devices do not require specialized maintenance by data scientists or AI developers. The graphic data flows are automatically delivered for monitoring, therefore, it is an autonomous technology.
On the other hand, the list of Edge AI applications is long. Current examples include facial recognition and real-time traffic updates on smartphones, as well as semi-autonomous vehicles or smart devices. Other Edge AI-enabled devices include video games, smart speakers, robots, drones, security cameras, and wearable health monitoring devices. Below are a few more areas where Edge AI is expected to continue to be used:
- It will provide intelligence to the security camera detection process. Traditional surveillance cameras record images for hours and then store and use them if necessary. However, with Edge AI, the algorithmic processes will be carried out in real time in the system itself, so the cameras will be able to detect and process suspicious activities in real time, for a more efficient and less expensive service.
- The autonomous vehicles will increase their capacity to process data and images in real time for the detection of traffic signs, pedestrians, other vehicles, and roads, improving the levels of security in transportation.
- It will be possible to use it in image and video analysis, to generate responses to audiovisual stimuli, or for real-time recognition of scenes and spaces, for example, in smartphones.
- It will reduce costs and improve safety in terms of industrial IoT (IIoT). The AI will monitor machinery for possible defects or errors in the production chain, while the Machine Learning will recompile data in real time of the whole process.
- It will be used for the analysis of medical images in emergency medical care.
- The deployment of 5G technology networks will mean greater speed and very low latency for mobile data transmission, making Edge AI more useful. Companies have already embraced this, and for example, IBM and Red Hat have partnered to launch 5G-based edge solutions to enable companies to more easily manage workloads across a massive volume of devices from different vendors, giving the telecommunications industry the agility it needs to quickly deliver services to its customers.
There are no application limits for Edge AI technology. After the crisis of the Covid-19, the ingenuity of the companies has led to deploy solutions based on Artificial Intelligence to provide accurate information in real time. In healthcare, for example, AI is helping with patient monitoring, testing and treatment.
The creativity and imagination of the developer community is the only real limit of Edge technology. That is why there are already collaborative projects trying to train students and professionals with STEM profile in this new technology.
An example of this is that of Intel and Udacity, which are collaborating in the Intel Edge AI for IoT Developers Nanodegree programme, with the aim of training the developer community in Deep Learning and Computer Vision. This includes software engineers, machine learning engineers, data scientists, and all those involved in the development of cloud-based AI applications. The program is expected to lead to more user-oriented Edge AI application development.