The furure has arrived with Artificial Intelligence

Posted on Thu, 08/10/2017 - 11:43 by avantgarde

Artificial intelligence (AI) has been defined as a branch of computer science that focuses on the creation of intelligent machines that work and react like humans. The overall research goal of artificial intelligence is to create technology that allows computers and machines to function in an intelligent manner

There are two core parts of AI:

Knowledge engineering - Machines can often act and react like humans only if they have abundant information relating to the world. Artificial intelligence must have access to objects, categories, properties, and relations between all of them to implement knowledge engineering.

Machine learning - Learning without any kind of supervision requires an ability to identify patterns in streams of inputs, whereas learning with adequate supervision involves classification and numerical regressions. Machine perception deals with the capability to use sensory inputs to deduce the different aspects of the world.

With AI, the general problem of creating intelligence has been broken down into sub-problems.

Reasoning, problem-solving

By the late 1980s and 1990s, AI research had developed methods for dealing with  or incomplete information, employing concepts from  and . For difficult problems, algorithms can require enormous computational resources. The amount of memory or computer time required becomes astronomical for problems of a certain size. Human beings ordinarily use fast, intuitive judgments rather than step-by-step deduction that early AI research could model.

Knowledge representation

 and  are central to AI research. Many of the problems machines are expected to solve will require extensive knowledge about the world. Among the most difficult problems in knowledge representation are:

Planning

Intelligent agents must be able to set goals and achieve them. They need a way to visualize the future, a representation of the state of the world and can make predictions about how their actions will change it and be able to make choices that maximize the  of available choices.

Natural language processing

gives machines the ability to read and  human language. A sufficiently powerful natural language processing system would enable  and the acquisition of knowledge directly from human-written sources, such as newswire texts. Some straightforward applications of natural language processing include  and .

Perception

 is the ability to use input from sensors (such as cameras, microphones, , sonar and others) to deduce aspects of the world.  is the ability to analyze visual input. A few selected subproblems are , and .

Motion and manipulation

The field of  is closely related to AI. Intelligence is required for robots to handle tasks such as object manipulation and , with sub-problems such as , and .

Risks associated with AI:

Widespread use of artificial intelligence could have unintended consequences that are dangerous or undesirable. In the long-term, the scientists have proposed to continue optimizing function while minimizing possible security risks that come along with new technologies.

Devaluation of humanity

AI applications cannot, by definition, successfully simulate genuine human empathy and that the use of AI technology in fields such as  or  was deeply misguided. AI was willing to view the human mind as nothing more than a computer program.

Malevolent and friendly AI

AI can be neither designed nor guaranteed to be benevolent.

Types of artificial intelligence:

Weak AI  is also known as narrow AI, is an AI system that is designed and trained for a task. Virtual personal assistants, such as Apple's Siri, are a form of weak AI.

, also known as artificial general intelligence, is an AI system with generalized human cognitive abilities so that when presented with an unfamiliar task, it has enough intelligence to find a solution. The , developed by mathematician Alan Turing in 1950, is a method used to determine if a computer can actually think like a human, although the method is controversial.

AI applications:

  • 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 . 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 scheme. Other AI applications include , a computer program used online to answer questions and assist customers, to help schedule follow-up appointments or aiding patients through the billing process, and virtual health assistants that provide basic medical feedback.
  • AI in business. Robotic process automation is being applied to highly repetitive tasks normally performed by humans. Machine learning algorithms are being integrated into analytics and CRM platforms to uncover information on how to better serve customers. Chatbots have been incorporated into websites to provide immediate service to customers. Automation of job positions has also become a talking point among academics and IT consultancies such as Gartner and Forrester.
  • AI in education. AI can automate grading, giving educators more time. AI 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. AI could change where and how students learn, perhaps even replacing some teachers.
  • AI in finance. AI applied to personal finance applications, such as Mint or Turbo Tax, is upending financial institutions. Applications such as these could collect personal data and provide financial advice. Other programs, IBM Watson being one, have been applied to the process of buying a home. Today, the  performs much of the trading on Wall Street.
  • AI in law. The discovery process, sifting through of documents, in law is often overwhelming for humans. Automating this process is a better use of time and a more efficient process. Startups are also building question-and-answer computer assistance that can sift programmed-to-answer questions by examining the taxonomy and ontology associated with a .
  • AI in manufacturing. This is an area that has been at the forefront of incorporating robots into the . Industrial robots used to perform single tasks and were separated from human workers, but as the technology advanced that changed.

 

Tags: AI Artificial Intelligence Weak AI Strong AI