ARTIFICIAL INTELLIGENCE: WHAT IS IT ?
Artificial intelligence (AI) is an area of computer science that emphasizes the creation of intelligent machines that work and react like humans.
Research associated with artificial intelligence is highly technical and specialized. The core problems of artificial intelligence include programming computers for certain traits such as:
- Problem solving
- Ability to manipulate and move objects
Most AI examples that you hear about today – from chess-playing computers to self-driving cars – rely heavily on deep learning and natural language processing. Using these technologies, computers can be trained to accomplish specific tasks by processing large amounts of data and recognizing patterns in the data.
There are two types of Artificial Intelligence:
Narrow AI (weak AI) and
General AI (AGI or strong AI)
- Narrow Artificial Intelligence
This type of AI is what everyone is using today. The design parameters for narrow AI is that it can only perform a "specific small task." For instance, facial recognition software is "only" used to identify faces, not cars or other objects. This type of AI can outperform humans at specific tasks such as chess, but nothing else.
- General Artificial Intelligence
General AI (AGI) is what every researcher is aiming to create. While narrow AI deals with specific tasks, AGI has a much broader reach. This type of artificial intelligence will blow humans out of the water when it comes to cognitive tasks. Think of androids or robots that look and act human, but are smarter, faster, and stronger.
ARTIFICIAL INTELLIGENCE IN TODAY’S WORLD
See AI in Every Industry
Peek inside an AI-enabled hospital, an AI-assisted retail store and a predictive analytics system that talks. This report from Harvard Business Review examines the AI landscape, takes a look at the AI workforce – and explains why you shouldn’t swear at Siri.
AI and the Internet of Things
Data is all around us. The Internet of Things (IoT) and sensors have the ability to harness large volumes of data, while artificial intelligence (AI) can learn patterns in the data to automate tasks for a variety of business benefits.
Integrate AI into your Analytics Program
For AI to be used effectively, it’s important that the strategy around it feeds into your larger business strategy, always taking into account the convergence of people, process and technology.
Benefits and Uses of Artificial Intelligence
1. For the Economy, Business, and Industries
Artificial intelligence can benefit the economy by helping the evolution of work. Robots and AI will help people perform their tasks better, not take their jobs. The combination of man and machine will be unstoppable.
Facial recognition, pattern identification, and digital content analysis will be huge. Academic research, health sciences, and tech companies will enjoy enhanced capabilities.
2. For Humanity and Society
AI enhances information throughput and efficiency, helping people create new opportunities. We're talking about new streams for revenue generation, savings, and jobs.
Artificial intelligence enhances users' lifestyle choices by using search algorithms that provide targeted information. AI will handle all mundane tasks, such as data entry and answering emails. AI-powered smart homes can cut down on energy use and provide better security.
3.For Health care and Medicine
Health care services will be better at diagnostics because an AI wearable can monitor users 24/7. Artificial intelligence can help people extend their knowledge and understanding of Medicine. Image-based AI diagnoses can help doctors better treat their patients.
Challenges of using Artificial Intelligence
Artificial intelligence is going to change every industry, but we have to understand its limits.
The principle limitation of AI is that it learns from the data. There is no other way in which knowledge can be incorporated. That means any inaccuracies in the data will be reflected in the results. And any additional layers of prediction or analysis have to be added separately.
Today’s AI systems are trained to do a clearly defined task. The system that plays poker cannot play solitaire or chess. The system that detects fraud cannot drive a car or give you legal advice. In fact, an AI system that detects health care fraud cannot accurately detect tax fraud or warranty claims fraud.
In other words, these systems are very, very specialized. They are focused on a single task and are far from behaving like humans.
Likewise, self-learning systems are not autonomous systems. The imagined AI technologies that you see in movies and TV are still science fiction. But computers that can probe complex data to learn and perfect specific tasks are becoming quite common.
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