Introduction to Artificial Intelligence Applications
Artificial Intelligence Application is a subject widely prevalent in the IT world for more than 4 decades and it was in the laboratory all through.
In today’s digital world, abundant availability of
- Data generated from multiple sources (Big data)
- Compute and storage resources (on-premises and Cloud)
- Internet Bandwidth
- Complex Algorithms to derive insights from big data facilitated the development of AI applications using a variety of new technologies. AI platforms are being built for old business cases but not implemented due to limitations in technology and for new use cases that got evolved along with AI technology.
What is Artificial Intelligence Applications?
AI is all about building intelligence into machines to enable it to perform human tasks with precision for the known operations. It also packs machines with a lot of data points for the machines to learn and handle unknown situations. AI simulates machines to work, learn, think and react like human beings.
In this article let’s see the applications developed using AI technologies.
Most adopted AI Technologies
Natural Language Processing
NLP is a method of making machines to understand the natural language human speaks or interacts with it. It also enables a machine to respond back to the human after processing his request, in the way human understands. Syntax and semantics are the key parameters in NLP.
ML enables the machine to learn itself automatically using the data points available to them without depending on external instructions. ML algorithm helps the machine to handle unknown situations and manage them. Deep learning is a subset of ML and it works with unstructured big data with a structured layer approach like the human brain to derive deep insights.
Robotic Process Automation
It automates the mundane manual transaction process with the software robot. This robot navigates ERP/CRM/FSM software steps and completes the transaction in the way a human does. It improves the efficiency of business operations and releases manual resources for value-added work.
It helps to identify human face using technology. Using Biometric features human face is mapped from video or photo and matched with the database to find a match. The privacy issue is a major challenge in using this technology.
List of Top Artificial Intelligence Applications
Applications are being built using the AI technologies for Industries, Agriculture, Education, and E-commerce. Apps like Digital Assistant, developed on voice recognition technology are widely used in the public domain. AI Apps are on different levels of maturity. List of top AI apps across various segments are
- Drivers are facilitated with AI features like self-parking, advanced cruise controls to assist them.
- AI techniques are used in improving traffic management system that reduces wait times, fuel consumption and emissions by 25%
- Automatic transmission system
- A driverless (Autonomous) car is in a pilot stage.
- Robot in manufacturing in non-ergonomic conditions.
- Predictive smart maintenance to avoid production loss
- Early alert on probable quality issues in manufacturing line due to machine behavior or raw material quality etc.,
- Faster diagnosis using patient’s health data and other related data (IBM’s Watson)
- Medical images scanning for the detection of diseases.
- Clinical Decision support system using data mining
- Robot to do repetitive jobs in surgery and patient care
4. Finance and Banking
- Measuring creditworthiness of clients and risk-free loan disbursement using data from social media and other sources.
- The investment decision of financial institutions is assisted by AI engines.
- Algorithmic trading, complex AI systems, is used in automating trading decision making.
5. Human resources
- AI-assisted recruitment
- Predicting attrition of Employees
- AI techniques to increase the yield of crops and suggest methods to increase efficiency in farming.
- Monitoring crop and soil condition to track the health of crops
- Data inputs to farmers on changes in weather conditions, market environment to plant their crops.
- AI Tutor: Individual care for students in the areas wherever they need extra inputs.
- AI offers Adaptive learning program that matches the preference of the students
- Visual Search to identify items to shop
- Chatbot to provide information contents
- Automatic display of products based on browsing history
9. Digital Assistant
Voice recognition applications are popular in the public domain and there are many digital assistant platforms in the market that interacts with people and provide information contents as per their need on anything on earth. Siri (Apple), Alexa (Amazon), Google Now, Cortana (Microsoft), Facebook messenger, Blackberry Assistant, Teneo, Speaktoit Assistant, Hound and Braina are the most popular digital assistant software platforms. This software is either built into end-user devices like phone and tablet or marketed as separate gadgets like Amazon Echo, Google Home, etc.
10. AI embedded in Devices
AI applications are embedded into connected devices like machines, fridge, A/c units, electrical fittings and making them smarter. People can interact with these devices and activate and deactivate them remotely and these devices can talk to other systems and perform certain functions.
AI functionalities are built-in standard ERP. SAP, Oracle, and other ERP vendors are building add on AI modules into their ERP and making them smart and Intelligent ERP.
Features of Artificial Intelligence Applications Functionalities
It can be classified into the below functions
Narrow Artificial Intelligence Applications
In Narrow AI, systems are designed to perform specified tasks in a reactive way. Many successful AI implementations like Voice recognition system, RPA, facial recognition, and data intelligence belong to this category and these Apps undergo continuous improvements.
Strong Artificial Intelligence Applications
In Strong AI, Systems are designed to match human cognitive abilities to think, decide like human beings when presented with unfamiliar scenarios. Machine learning, Deep learning, and neural networks are in this category. Historical data and data from surrounding systems are essential in building intelligence into these systems. Autonomous/driverless vehicles and decision-making systems are designed in this way.
Other Features of Artificial Intelligence Applications
Skills like Knowledge, Reasoning, Problem-solving, Perception, Learning, Planning and Manipulation, and physical movement will have to be featured in AI programming. Data access from several sources and intuitive algorithms built in the program helps AI to acquire these skills.
Conclusion – Artificial Intelligence Applications
More than 50% of major Industries globally have implemented at least one use case in AI technology and the adoption of AI is on the fast lane. There are successful AI implementations in automating mundane tasks (RPA, Chatbot), Voice recognition, Service calls management, Data Intelligence areas. A current trend in AI now is to migrate from Decision support AI to Decision making AI.