Artificial Intelligence

           

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AI (ARTIFICIAL INTELLIGENCE)

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What is Artificial Intelligence?Artificial Intelligence (AI), sometimes refered to as machine intelligence (Computer Science). "This is intelligence demonstrated by machines, in contrast to the natural intelligence displayed by humans and animals" (Wikipedia).

In Computer science AI is define as the research as the study of "intelligent agents" (that is any device that perceives its environment and takes actions that maximize its chance of successfully achieving its goals). Therefore the term "artificial intelligence" is used to describe machines that mimic "cognitive" functions that humans associate with other human minds, such as "learning" and "problem solving".

Modern machines AI are those that successfully understanding human speech, competing at the highest level in strategic game systems (like the chess and Go), autonomously operating cars, intelligent routing in content delivery, military simulations and activities performed by machine that would require an extent amount of intelligence.

 CLASSIFICATION OF AI

Artificial intelligence can be classified into three different types of systems: 

(1) analytical

(2) human-inspired                          (3)humanized artificial intelligence. Analytical AI has only characteristics consistent with cognitive intelligence; generating a cognitive representation of the world and using learning based on past experience to inform future decisions. Human-inspired AI has elements from cognitive and emotional intelligence; understanding human emotions, in addition to cognitive elements, and considering them in their decision making. Humanized AI shows characteristics of all types of competencies ( i.e. cognitive,     emotional and social intelligence ) is able to be self-conscious and is self-aware in interactions with others.

                    THE BIRTH OF AI

The Idea that gave birth to the term AI(Artificial Intelligence) has been around even as far back the World War. During this time, a British computer scientist "Alan Turing" worked to crack the ‘Enigma’ code which was used by German forces to send messages securely. Alan Turing and his team created the Bombe machine that was used to decipher Enigma’s messages.

The Enigma and Bombe Machines laid the foundations for Machine Learning. According to Turing, a machine that could converse with humans without the humans knowing that it is a machine would win the “imitation game” and could be said to be “intelligent".

                    Alan Turing 1927
In 1956, American computer scientist John McCarthy organised the Dartmouth Conference, at which the term ‘Artificial Intelligence’ was first adopted.

Artificial intelligence was founded as an academic discipline in 1956, and in the years sjince has experienced several waves of optimism, which was also accompanied by some disappointment and the loss of funding (known as the "AI winter"). 

This period of time was quick followed by new approaches to Artificial Intelligence, success and renewed funding in this field.

                      John McCarthy

MAJOR DEVELOPMENT IN THIS FIELD

In 1951, an machine known as Ferranti Mark 1 successfully used an algorithm to master checkers. Subsequently, Newell and Simon developed General Problem Solver algorithm to solve mathematical problems. Also in the 50s John McCarthy, often known as the father of AI, developed the LISP programming language which became important in machine learning.

In the 1960s, researchers emphasized developing algorithms to solve mathematical problems and geometrical theorems. In the late 1960s, computer scientists worked on Machine Vision Learning and developing machine learning in robots. WABOT-1,the first‘intelligent’ humanoid robot, was built in Japan in 1972.

          Sophia the first Humanoid AI
       (image source from Google engine)

THE GOALS OF AI

(The Ultimate driving force)

The ultimate goal of  AI research include 
1. Reasoning
2. Knowledge representation
3. Planning
4. Learning
5. Natural language processing
6. Perception
7. Move and manipulate objects

These goals has then turn to be problems, hurdles, constraints and at same time a "Driving Force" scientists in this field of research. One must note that General intelligence is among the field's long-term goals. 

Approaches include statistical methods, computational intelligence, and traditional symbolic AI. 

TOOLS USED IN AI

Many tools are used in AI, including :
1. Versions of search and mathematical optimization
2. Artificial neural networks
3. Statistics methods
4. Probability methods
5. Economics methods

 The AI field draws upon computer science, information engineering, mathematics, psychology, linguistics, philosophy, and many other fields.

APPLICATION OF  AI

 AI can be applied virtually every area of humans day to day activities

1. Managing Medical Records and Other Data

Since the firhst step in health care is compiling and analyzing information (like medical records and other past history), data management is the most widely used application of artificial intelligence and digital automation. Robots collect, store, re-format, and trace data to provide faster, more consistent access.

2. Doing Repetitive Jobs

Analyzing tests, X-Rays, CT scans, data entry, and other mundane tasks can all be done faster and more accurately by robots. Cardiology and radiology are two disciplines where the amount of data to analyze can be overwhelming and time consuming. Cardiologists and radiologists in the future should only look at the most complicated cases where human supervision is useful.

3. Treatment Design

Artificial intelligence systems have been created to analyze data – notes and reports from a patient’s file, external research, and clinical expertise – to help select the correct, individually customized treatment path.

4. Digital Consultation

Apps like Babylon in the UK use AI to give medical consultation based on personal medical history and common medical knowledge. Users report their symptoms into the app, which uses speech recognition to compare against a database of illnesses. Babylon then offers a recommended action, taking into account the user’s medical history.

5. Virtual Nurses

The startup Sense.ly has developed Molly, a digital nurse to help people monitor patient’s condition and follow up with treatments, between doctor visits. The program uses machine learning to support patients, specializing in chronic illnesses.

In 2016, Boston Children’s Hospital developed an app for Amazon Alexa that gives basic health information and advice for parents of ill children. The app answers asked questions about medications and whether symptoms require a doctor visit.

6. Medication Management

The National Institutes of Health have created the AiCure app to monitor the use of medication by a patient. A smartphone’s webcam is partnered with AI to autonomously confirm that patients are taking their prescriptions and helps them manage their condition. Most common users could be people with serious medical conditions, patients who tend to go against doctor advice, and participants in clinical trials.

7. Drug Creation

Developing pharmaceuticals through clinical trials can take more than a decade and cost billions of dollars. Making this process faster and cheaper could change the world. Amidst the recent Ebola virus scare, a program powered by AI was used to scan existing medicines that could be redesigned to fight the disease.

The program found two medications that may reduce Ebola infectivity in one day, when analysis of this type generally takes months or years – a difference that could mean saving thousands of lives.

8. Precision Medicine

Genetics and genomics look for mutations and links to disease from the information in DNA. With the help of AI, body scans can spot cancer and vascular diseases early and predict the health issues people might face based on their genetics.

9. Health Monitoring

Wearable health trackers – like those from FitBit, Apple, Garmin and others – monitors heart rate and activity levels. They can send alerts to the user to get more exercise and can share this information to doctors (and AI systems) for additional data points on the needs and habits of patients.

10. Healthcare System Analysis

In the Netherlands, 97% of healthcare invoices are digital. A Dutch company uses AI to sift through the data to highlight mistakes in treatments, workflow inefficiencies, and helps area healthcare systems avoid unnecessary patient hospitalizations.

 THE DOWN SIDE IN AI

The field was founded on the claim that human intelligence "can be so precisely described that a machine can be made to simulate it". This raises philosophical arguments about the nature of the mind and the ethics of creating artificial beings endowed with human-like intelligence which are issues that have been explored by myth, fiction and philosophy since antiquity. Some people also consider AI to be a danger to humanity if it progresses unabated. Others believe that AI, unlike previous technological revolutions, will create a risk of mass unemployment.

CONCLUSION

In today's modern Technological Age, AI techniques have experienced a resurgence following concurrent advances in computer power, large amounts of data and theoretical understanding; and AI techniques have become an essential part of the technology     industry helping to solve many challenging problems in computer science, software engineering and operations research.

REFERENCE

https://en.m.wikipedia.org/wiki/Artificial_intelligence.

https://novatiosolutions.com/10-common-applications-artificial-intelligence-healthcare/

https://towardsdatascience.com/history-of-ai-484a86fc16ef

First AI Winter, Mansfield Amendment, Lighthill report

Crevier 1993, pp. 115–117

Russell & Norvig 2003, p. 22

Maloof, Mark. "Artificial Intelligence: An Introduction, p. 37" (PDF). georgetown.edu.

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