1. Interacting with the environment
The last of the three major AI functions we will explore is the interaction between AI and the outside environment.
2. AI functions and areas involved
And to discuss it,
3. AI functions and areas involved
we will make a quick stop at the three areas that involve interacting with the physical or digital environment to some degree: computer vision, natural language processing, and robotics.
4. Computer vision
The area of computer vision has a close relationship with deep learning algorithms and models, which have proven very effective to solve computer vision problems, like:
Image processing, which is the application of AI to make improvements to images and videos. This is the kind of AI behind photographic filters, for example.
Object detection in images and videos, used in applications like surveillance, package tracking, and so on.
Motion analysis analyzes image frames to extract motion information like the speed or direction of an object.
And image-video generation is one of AI's most attractive features, making it possible to generate realistic images by just describing what you want to visualize.
5. Natural Language Processing (NLP)
Natural Language Processing, or NLP, is perhaps the most popular AI area today.
The range of problems NLP can address is growing fast. From the classification of text documents to sentiment analysis of customer reviews, to driving conversations which is the building block of chatbots.
Speech recognition is another important sub-area of NLP, and it is responsible for home assistants and personal assistants in your mobile phone. Thanks to speech recognition, it is possible to translate audio into text and vice versa.
6. Robotics
If there is one area of AI where the interaction with the physical environment is nearly omnipresent, that's robotics.
Robotics combine computer vision and NLP in a wide number of applications. Usually, robotics can be divided into the following areas.
Sensing and perception occur when a robot senses and gathers data from the environment. This is important not only to collect outside data, for example, aerial images captured by drones, but also to make decisions and execute other actions like mobility. For example, a mobile robot may decide to stop moving and change the course of action when its proximity sensors encounter an obstacle in the surroundings.
Manipulation occurs when the robot modifies the current state of its environment. For example, industrial robots that assemble vehicles by grabbing, releasing, and assembling pieces together.
Lastly, if you have ever seen humanoid robots that speak and listen to humans, that is a fascinating example of human-robot interaction where the areas of robotics and NLP meet closely together.
7. Let's practice!
OK, let's wrap up with some exercises.