Artificial Intelligence Applications

Artificial Intelligence Applications: Introduction

Artificial Intelligence Application has been a topic of great interest in the IT industry for over 4 decades. It was even in the lab all the time.

  • The digital age offers abundant opportunities for access in today’s digital world.
  • Data from many sources (Big data).
  • Storage and compute resources (on-premises or Cloud)
  • Bandwidth Internet

Complex Algorithms were used to extract insights from large amounts of data. This allowed for the development of AI applications that utilized a wide range of technologies. AI platforms are built for older business cases, but they have not been implemented because of technology limitations or new uses that have emerged with AI technology.

What are Artificial Intelligence Applications?

AI is about putting intelligence into machines so that they can perform human tasks accurately for known operations. AI also provides machines with lots of data points that allow them to learn from and deal with unknown situations. AI simulates machine learning, thinking, and responding like humans.

Most adopted AI Technologies.

Natural Language Processing

NLP allows machines to learn the natural language spoken by humans or interact with them. After processing a request, NLP allows a machine to reply to the human in the same way that he understands. NLP is based on syntax and semantics.

Machine Learning

ML allows the machine to learn automatically by using all the data points they have available, without having to rely on external instructions. The machine can handle unpredicted situations and manage them using the ML algorithm. Deep learning is a subset ML. It works with unstructured big-data with a structured layer approach, like the human brain, to extract deep insights.

Robotic Process Automation

The software robot automates mundane manual transactions. The robot can navigate ERP/CRM/FSM software steps, and completes transactions in the same way as a human. It increases efficiency and frees up manual resources for value-added tasks.

Facial Recognition

It allows you to identify the human face with technology. Biometric features allow you to match your face with a database by mapping your photo or video. Privacy is a significant concern when using this technology.

Top Artificial Intelligence Applications

The AI technologies are used to build applications for Industries, Agriculture and Education. Digital Assistant is a popular app that uses voice recognition technology. AI apps are at different stages of maturity. Here is a list of the top AI apps in different segments

Transport

To assist drivers, AI features such as self-parking and advanced cruise controls are available.

Artificial intelligence techniques are used to improve traffic management systems. This reduces wait times and fuel consumption by 25%.

  • Transmission system with automatic transmission
  • Pilot stage: A driverless (Autonomous), car.

Manufacturing

  • Robotic manufacturing in non-ergonomic environments
  • Predictive, smart maintenance to avoid production losses
  • Alert early on possible quality issues in manufacturing lines due to machine behavior, raw material quality, etc.

Healthcare

  • IBM Watson allows for faster diagnosis by using patient’s data and other related data (IBM Watson).
  • Scan medical images for diseases.
  • Clinical Decision support system using data mining
  • Robotic surgery robots can perform repetitive tasks in patient care and surgery

Finance and banking

Using data from social media, and other sources, to assess creditworthiness and determine risk-free loan disbursement.

  • AI engines assist financial institutions in making investment decisions.
  • Algorithmic trading is complex AI systems that are used to automate trading decision making.

Human resources

  • AI-assisted Recruitment
  • Predicting employee attrition

Agriculture

  • AI techniques can increase yields and offer methods to improve efficiency in farming.
  • Monitoring soil and crop condition to monitor the health of crops
  • Farmers receive data inputs on weather conditions and market environment changes that affect their ability to plant crops.

Education

  • AI Tutor: Individual assistance for students in areas that require it.
  • AI offers an adaptive learning program that suits the preferences of students.

E-Commerce

  • Visual Search allows you to find items that you want to buy
  • Chatbot provides information content
  • Based on browsing history, automatic display of products

Digital Assistant

The public domain is awash with voice recognition apps. There are many digital assistant platforms that can interact with people and provide relevant information to their needs. Siri (Apple), Alexa, Google Now, Cortana, Microsoft, Facebook Messenger, Blackberry Assistant and Teneo are some of the most popular digital assistant platforms. These software platforms can be integrated into phones and tablets, or sold separately as gadgets such as Amazon Echo, Google Home, and Google Home.

Artificial Intelligence embedded in Devices

Artificial intelligence applications can be embedded in connected devices such as machines, fridges, A/c units, and electrical fittings, making them smarter. These devices can be controlled remotely by people. They can also communicate with other systems and perform certain functions.

ERP

Standard ERP includes AI functionality. SAP, Oracle and other ERP vendors are adding AI modules to their ERPs, making them intelligent and intelligent.


Artificial Intelligence Applications Functionalities

  • It can be divided into the following functions.
  • Narrow Artificial Intelligence Applications

Narrow AI systems are those that can perform specific tasks in a reactive manner. This category includes successful AI implementations such as Voice recognition system, RPA and facial recognition. These Apps are constantly improving.

Strong Artificial Intelligence Applications

Strong AI is a category that allows systems to be matched in cognitive ability to think and decide as humans when faced with unknown situations. This category includes machine learning, deep learning, and neural network. These systems require intelligence to be built using historical data as well as data from the surrounding systems. Autonomous/driverless vehicles and decision-making systems are designed in this way.

Additional Features of Artificial Intelligence Applications

AI programming will require the use of skills such as knowledge, reasoning, problem-solving and perceptual ability. AI can access data from many sources and use intuitive algorithms to learn these skills.

Conclusion – Artificial Intelligence Applications

Over 50% of the major Industries have at least one application of AI technology. This is a sign that AI adoption is rapidly increasing. AI has been successful in automating mundane tasks (RPA and Chatbot), Voice recognitions, Service calls managements, and Data Intelligence. Current trends in AI include moving from Decision support AI towards Decision making AI.

Additional Resource:
https://plato.stanford.edu/entries/artificial-intelligence/
https://www.oracle.com/artificial-intelligence/what-is-ai/
https://sitn.hms.harvard.edu/flash/2017/history-artificial-intelligence/

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