What is Multimodal AI?
Discover its full potential
Artificial Intelligence and its application in multiple sectors is advancing at a dizzying pace given the endless opportunities it provides for companies of all types and industries. Day by day, we are witnessing the emergence of new AI and Machine Learning products in the market. However, Multimodal Artificial Intelligence is a great treasure to be discovered because there are very few professional solutions on the market capable of working in this extremely innovative technological area.
BUT WHAT EXACTLY IS MULTIMODAL ARTIFICIAL INTELLIGENCE?
People are able to understand the meaning of the crossing of different types of data [text, video, image and audio] when they interact in a given context. That is, if we see a photograph of an empty theater we can interpret that the show is over or that there was no audience. However, if we see the same photograph accompanied by a text that says “The pandemic empties theaters” we understand that due to the health crisis cultural shows have been canceled. This example helps us to understand the concept of multimodality applied to Artificial Intelligence.
Multimodal AI systems are characterized by processing multiple sets of different types of data using learning-based methods to provide more accurate, truthful and intelligent information.
Or put another way, multimodal learning is able to consolidate independent data from multiple AI devices into a single model and make predictions automatically.
MULTIMODAL AI USE CASES
The application of multimodal AI is extensible to all industries. Increasingly, we are seeing how innovative companies and organizations are taking an interest in this area of artificial intelligence and how they can implement it in their digital transformation strategies.
The automotive industry, for example, is working with multimodal AI in its driver assistance systems, its HMI (human-machine interface) assistants in vehicles and driver monitoring systems designed to detect sleep, fatigue, distractions or loss of attention. Imagining all the possibilities that multimodal interaction with our vehicle offers us is exciting. It means communicating with our car through our voice (Natural Language Processing), our image (visual inspection) and our actions.
Other major sectors where the application of Multimodal Artificial Intelligence is promising are:
– The Healthcare sector and the pharmaceutical industry and the possibility of making diagnoses automatically and immediately by multimodal analysis of image data, symptoms, background and patient histories.
– The media and entertainment sector with its recommendation systems, personalized advertising and remarketing.
We must not forget the field of product design or any business in which the association between visual and textual concepts is strategic and fundamental. In this sense, multimodality makes it possible to generate images from text descriptions and, conversely, to instantly categorize images through visual recognition.
As we can see, the applications in industry are endless. You only have to imagine to desire and find the perfect technological ally to implement new Multimodal AI systems capable of revolutionizing the processes of any company.
THE UNIQUE MULTIMODAL ARTIFICIAL
ENAIA, AIaaS platform, makes Machine Learning easy to lead the penetration of Artificial Intelligence in all businesses and processes. It is designed to be accessible to companies of any size in all sectors. It has the ability to create fully operational AI models for any task, no matter how specific.
ENAIA makes predictions from different types of input data: images, natural language and data tables. Single or combined [Multimodal AI].
√ ENAIA does not require BigData, just RightData
√ No programming or AI knowledge is required to use it.
√ Any developer can integrate it via REST API in the applications used by their company.