Introduction
Artificial Intelligence which is commonly called AI. Artificial intelligence refers to systems or machines that mimic human intelligence to perform tasks and can iteratively improve themselves based on the information they collect. AI manifests in a number of forms. A few examples are:
Chatbots use AI to understand customer problems faster and provide more efficient answers.
Intelligent assistants use AI to parse critical information from large free-text datasets to improve scheduling.
Recommendation engines can provide automated recommendations for TV shows based on users’ viewing habits
Artificial intelligence is the gift of science and technology to mankind and it has revolutionized the modern world. Artificial intelligence is relatively of recent origin and it is used in different spheres of human life and has made life easy.
As the hype around AI has accelerated, vendors have been scrambling to promote how their products and services use AI. Often what they refer to as AI is simply one component of AI, such as machine learning. AI requires a foundation of specialized hardware and software for writing and training machine learning algorithms. No one programming language is synonymous with AI, but a few, including Python, R and Java, are popular.
In general, AI systems work by ingesting large amounts of labeled training data, analyzing the data for correlations and patterns, and using these patterns to make predictions about future states. In this way, a chatbot that is fed examples of text chats can learn to produce lifelike exchanges with people, or an image recognition tool can learn to identify and describe objects in images by reviewing millions of examples.
AI programming focuses on three cognitive skills: learning, reasoning and self-correction.
Learning processes:
This aspect of AI programming focuses on acquiring data and creating rules for how to turn the data into actionable information. The rules, which are called algorithms, provide computing devices with step-by-step instructions for how to complete a specific task.
Reasoning processes:
This aspect of AI programming focuses on choosing the right algorithm to reach a desired outcome.
Self-correction processes:
This aspect of AI programming is designed to continually fine-tune algorithms and ensure they provide the most accurate results possible.
Artificial intelligence has made its way into a wide variety of markets. Here are examples.
AI in healthcare:
The biggest bets are on improving patient outcomes and reducing costs. Companies are applying machine learning to make better and faster diagnoses than humans. One of the best-known healthcare technologies is IBM Watson. It understands natural language and can respond to questions asked of it. The system mines patient data and other available data sources to form a hypothesis, which it then presents with a confidence scoring schema.
Other AI applications include using online virtual health assistants and chatbots to help patients and healthcare customers find medical information, schedule appointments, understand the billing process and complete other administrative processes. An array of AI technologies is also being used to predict, fight and understand pandemics such as COVID-19.
AI in education:
AI can automate grading, giving educators more time. It can assess students and adapt to their needs, helping them work at their own pace. AI tutors can provide additional support to students, ensuring they stay on track. And it could change where and how students learn, perhaps even replacing some teachers.
AI in law:
The discovery process – sifting through documents – in law is often overwhelming for humans. Using AI to help automate the legal industry’s labor-intensive processes is saving time and improving client service. Law firms are using machine learning to describe data and predict outcomes, computer vision to classify and extract information from documents and natural language processing to interpret requests for information.
AI in banking:
Banks are successfully employing chatbots to make their customers aware of services and offerings and to handle transactions that don’t require human intervention. AI virtual assistants are being used to improve and cut the costs of compliance with banking regulations. Banking organizations are also using AI to improve their decision-making for loans, and to set credit limits and identify investment opportunities.
Because hardware, software and staffing costs for AI can be expensive, many vendors are including AI components in their standard offerings or providing access to artificial intelligence as a service (AIaaS) platforms. AIaaS allows individuals and companies to experiment with AI for various business purposes and sample multiple platforms before making a commitment. Popular AI cloud offerings include the following:
Amazon AI
IBM Watson Assistant
Microsoft Cognitive Services
Google AI
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