When you ask Alexa to dim the lights, you're harnessing the power of Artificial Intelligence (AI). Once a tapestry of science fiction, AI now weaves itself into the fabric of everyday life, mimicking human intelligence. But do you know the applications of the branches of AI in our world? Keep reading this article to understand how AI is creating a smarter and more efficient future!
1. Expert Systems
Expert Systems are a branch of AI designed to simulate the decision-making ability of human experts. At their core, they are intelligent systems consisting of a knowledge base and inference engine.
This knowledge base stores curated knowledge from human experts, while the inference engine applies rules to the knowledge to solve complex tasks and problems. Think of it as a library brimming with books written by the best minds in a field, coupled with a librarian adept at finding the right knowledge for any specific query.
For example, in healthcare, Expert Systems can assist doctors and nurses by suggesting medical diagnoses of diseases and treatments while monitoring patients' evolution. For example, MYCIN, created by Edward Shortliffe, is capable of diagnosing bacterial infections and recommending antibiotics.
On the other hand, virtual assistants, like CIMON-2, enable users to get quick, tailored answers and support by referencing a knowledge base specific to their needs. Lastly, financial institutions rely on these systems for fraud detection, risk assessment, and portfolio management.
2. Natural Language Processing
Natural Language Processing (NLP) focuses on the intersection between computers and human language. This branch of AI powers virtual assistants and intelligent machines to comprehend, interpret, manipulate, and generate human language.
For example, imagine you're talking to a friend who not only understands your words but can also grasp the underlying emotions, respond appropriately, and sometimes predict what you're about to say. That's what NLP strives to achieve but between humans and computers.
One prominent example of NLP applied to our lives is Amazon's virtual assistant, Alexa, which understands spoken requests and answers accordingly through Speech Recognition.
Whether you're asking for weather updates, playing music, or controlling smart home devices, Alexa leverages NLP to decipher your natural language commands and perform the desired actions.
While NLP-powered customer service chatbots can answer questions and troubleshoot problems, Machine translation tools like Google Translate leverage NLP algorithms to break down the grammatical structure of one language and rebuild it in another.
3. Neural Networks
Neural Networks (NNs) are a powerful Machine Learning subfield that follows a set of linear instructions, similar to neurons in the human brain.
These networks are composed of interconnected nodes that process information and learn from data by passing signals back and forth through the network.
Neural Networks excel at tasks that involve recognizing complex patterns, such as identifying objects in images or understanding spoken language.
Although this pattern recognition ability to process language may sound similar to NLP, NNs go further into diverse applications!
Imagine looking at a picture of a cat. Your brain can instantly recognize the cat based on its shape, fur texture, and facial features. NNs achieve similar features by analyzing vast amounts of image data.
That makes them ideal for applications like facial recognition, which is used on social media platforms to identify people in photos.
This ML subfield is being used in autonomous vehicles or self-driving cars. Tesla, with the help of NVIDIA, enables object detection so cars navigate complex road environments, making roads safer for drivers and pedestrians.
4. Robotics
Robotics blends engineering and science to design, build, and program robots to perform tasks, either autonomously or with human supervision. Robots can move and perform actions independently, often equipped with sensors to perceive and interact with their environment.
A compelling example of robotics is Eyepick's AI automation and Soft Robotics' grippers' dexterity that sorts tomatoes based on their quality, color and other features.
Just imagine a robotic arm capable of helping farmers streamline routinary tasks, turning a manual process of the agriculture field into modern food-processing, sorting, and packing operations.
5. Machine Learning
Machine Learning focuses on the development of algorithms and statistical models that enable computers to perform tasks without explicit instructions.
Through techniques such as Reinforcement Learning and Unsupervised Learning, machines can learn from data and make predictions based on that data in a wide range of applications, from product recommendation systems to fraud detection and image recognition.
Streaming services like Spotify use Machine Learning algorithms to analyze a user's listening history, including favorite songs, artists, and genres. By identifying patterns in this data, the algorithms can recommend similar music or create playlists that cater to the user's mood or activity.
For instance, if you frequently listen to upbeat music during your workout routine, the algorithm might suggest a high-energy playlist for your next gym session. This data-driven approach to music selection personalizes the listening experience and keeps users engaged.
6. Fuzzy Logic
Fuzzy Logic is a branch of Artificial Intelligence (AI) that mimics human reasoning by accounting uncertainties. Imagine deciding how to wash your clothes: factors like fabric type, dirt level, and desired water temperature can exist on a spectrum, not just clean or dirty.
Fuzzy Logic excels in these situations, making it well-suited for applications with inherent uncertainty.
Fuzzy Logic helps handle ambiguity and complexity for a more nuanced evaluation process. It enables decision-makers to consider both quantitative and qualitative factors simultaneously, leading to more informed and comprehensive evaluations of product ideas.
Its benefits for Product Development offer a more accurate, efficient, and reliable method for evaluating product ideas during the early stages of the development process.
Overall, Fuzzy Logic is a powerful tool for Artificial Intelligence systems, enabling them to make nuanced decisions in complex control systems or uncertain situations. Its applications extend beyond Product Design and Development, impacting various industries and everyday appliances.
7. Computer Vision
Computer Vision is a branch of AI that empowers machines to interpret and understand visual information from the real world. By mimicking human visual perception, Computer Vision systems can analyze images and videos to extract meaningful insights.
This technology finds applications in diverse areas, including facial recognition, self-driving cars, medical image analysis, and quality control in manufacturing.
For instance, in healthcare, Computer Vision algorithms can analyze X-rays and MRIs to detect abnormalities with remarkable accuracy, aiding in early diagnosis and treatment.
