Kips Class 8 AI Unit 4: Possibilities

Unit 4: Possibilities

Question 1: What was the reason to gain the popularity to become popular of AI?
The term Artificial Intelligence or Al was first used in 1956, but it did not gain popularity until much later. With time, the use of computer increased, the internet was born and mobile internet picked pace. All of this led to an increase in data volumes, the improvement in the computer's computing power, increased data storage capabilities and as a result the Al gained popularity.

Question 2: Explain the various phases of AI research.

• First Phase
The first phase of Al research started with the Dartmouth Conference and involved techniques related to General Problem Solving (GPS). During this phase, researchers assumed that any problem can be solved by using a program code and mathematical models. To solve these problems, the researchers used computer data that was searched until a solution emerged.
For example, to solve chess, the whole problem was converted into mathematical problem in which the board, the pieces, moves, etc. were all converted into symbols. Searching through moves based on heuristics of previous games would allow the computer to find the best result. This approach showed substantial initial benefits, but the approach did not continue for a long time.

• Second Phase
The GPS approach was not fit for solving real world problems because the number of search combinations increased exponentially with an increase in the problem complexity. The second phase of Al research focused on reducing the search space so that the searching can become better. During this period:
→ Attempts were made to find better ways of representing data.
→ The research in Al initially slowed down due to negative publicity regarding them.
→ Japan announced the Fifth Generation Computer Systems Project (FGCS) in 1982, which once again increased the interest in development of Al systems.

• Third Phase
The third phase of Al research focused on developing Intelligent Knowledge Based Systems or IKBS. Such systems were also known as Expert Systems. These systems relied on specific domain-based data for solving Al problems. The main highlights of this phase were:
→ IKBS worked on data in the form of rules
→ IKBS was restricted in the sense that it was incapable of learning and its focus was extremely narrow.
→ IKBS needed to be regularly updated. This was a time-consuming and resource-intensive work.
→ IKBS lacked common sense that made humans more suited for certain tasks and work

• Further Phases
The problem with Als is that all the research in the Al field is leading to the development of weak Als We have not made much breakthrough in the development of strong Als The further phases of Al research involves developing systems that can learn and as such would not need to be regularly updated The ongoing developments in this area are:
→ Cyc project of Cycorp Inc. was the first project towards developing Al systems capable of common sense reasonings. The challenges of ambiguities of human language and the high ambition caused the project slowdown.
→ The recent attempts in this direction use a concept known as big data. Sometimes, this approach involves capturing data from the web.
→ The development of techniques like neural networks and genetic algorithms for developing machine learning

Question 3: Explain possibilities of AI in various fields.

• Artificial Intelligence influences Business
Commercial establishments and big businesses, along with the government, are the drivers for artificial intelligence development. Adopting Al-based solutions allows businesses to cut both cost and time and provide better services and products to the customers. Leading companies in every field are using Al solutions to stay ahead of the competition.

• Life-Saving AI
Healthcare industry is using Al to improve the quality of life and save it. The developments in this field include personalised drug treatments based on 24 × 7 monitoring using various sensors Robot assisted surgeries improve diagnosis. In the field of disaster management, these techniques are helping in both reducing the impact of disasters and managing the post disaster rescue.

• Entertaining Al
Entertainment industry is experimenting with Al to produce original music, books, recipes, etc. Companies, like, Netflix and Spotify use Al to predict what the users would like to watch or listen.

Question 4: Define the following terms:
a) Perception
b) Notification
c) Recommendation
d) Automation
e) Prediction
f) Prevention
g) Situational Awareness

a) The loop of perception is used by the Al systems to know what is happening or the present status. The Al system provides recommendations to you. For providing recommendation, it needs some basic information. For example, in the above instance, the Al system loads the directions to the canteen in your device. For giving these directions, the Al system needs to know the layout of the hospital, the areas that visitors can visit, the areas that visitors cannot visit, etc.
b) The loop of notification is used by the Al system to provide information to us. These notifications can take various forms. In the above example, the Al system informs you that the visiting hours end at 6:00 PM. The other forms of notification can include signals, alerts, reminders, alarms, changing the environment (for example, lightings), etc.

c) The loop of recommendation deals with predictions. The Al system has to predict what you would like to do. For this, it uses perceptions combined with the data about your past behaviour. In our example, the Al system used past data to know your reason for visiting the hospital. It uses data on behaviour to make recommendations, i.e., visit to the canteen, because you were hungry and gift shop because you were empty handed. These recommendations are made with the help of machine learning and complex probability calculations.

d) The automation loop learns from your actions over time and responds accordingly. In our example, the canteen starts storing data related to the customer. Over a period of time it learns that you like to drink soda when it is raining outside. So, on your next visit soda will be ready for you in the canteen if it is raining. This loop is the extension of the loop of recommendations. Automation takes place when the Al system has gained sufficient data about you to know exactly what you like to do.

e) The loop of prediction is an extension of the loop of recommendations and automations. In this loop, the Al system starts anticipating your behaviour and responding accordingly. For example, in the instance above, after a number of repeated visits, the Al system might learn that you always go to canteen before visiting the patient. On your next visit, the hospital Al system will automatically load the directions to the canteen and the patient without asking you for them.

f) The loop of prevention helps in preventing potential threats. In the above example, the Al system can have access to all of your medical history. Using this history, the Al system can inform the doctor about the possible reactions or consequences of combining different drugs based on past experiences. Extending this further, in case of an accident, the city Al can inform the hospital Al that accident has happened along with the status of the patient. The hospital Al can, in turn, access the history of the patient and help provide the correct first-aid information to the city Al. The city Al can provide this information to the appropriate people.

g) This loop helps in providing relevant information to the people involved. The current age is the age of information or information overload. We have access to a lot of information. The challenge is to take out the relevant information and discard the rest. Human beings do so by taking decisions. In this loop, the Al systems try to copy this human decision-making capability. In our example. Hospital Al can have access to complete medical records of the patient. But, all of this information might not be relevant to the doctor For example, a doctor treating the patient for pneumonia need not know that the patient was treated for fractures during childhood or that the patient had high fever ten years ago. But the doctor will need to know that whether the drug used for treating the patient's fever caused reaction.

Question 5: Explain different types of AI careers.
Al careers can be of two types. The first relates to developing and deploying Al systems. These are highly specialised jobs that require advance training and education. The second are related to operating Al systems. For these kinds of jobs: the entry level requirements are comparatively lower.
• The careers related to the core development and deployment of Al systems include:
→ Software analysts
→ Software developers
→ Computer scientists
→ Computer engineers
→ Algorithm specialists
In addition, the development and deployment of Al systems need specialists from different areas and fields. These careers help in the development of Al systems related to their fields.
• Mechanical, manufacturing, electrical engineers
• Medical professionals
• Defence specialists
• Graphic designers
• Architects
• Musicians and other entertainment specialists

Question 6: List the various companies that are hiring for AI roles (any 10).
Few of the various companies that are hiring for AI roles are:
→ Amazon
→ Uber
→ Apple
→ Microsoft
→ Samsung
→ Adobe
→ Lenovo
→ Facebook
→ SoluLab

Question 7: List the skills set for AI jobs.

• Machine Learning Engineer
Machine learning engineering is one of the most demanded Al related career. These engineers develop and manage machine learning projects. The skills required for these jobs include:
→ understanding of different programming languages
→ understanding of applied research and data science
→ strong mathematical skills

• Data Scientist
Data scientists are scientists who work with data. They collect, analyse, and draw interpretations from huge datasets. This is a perfect job for individuals who like to play with data. The skill sets required for these jobs include:
→ knowledge of big data platforms like Hive, Hadoop, MapReduce, etc.
→ knowledge of statistical computing and programming languages like Perl and Python
→ strong analytical and communication skills
Data analysts normally have post-graduate or doctorate degrees in fields like engineering, mathematics, or computer science.

• Business Intelligence Developer
Business intelligence developers can be regarded as a subset of data scientist jobs. They analyse data to identify business and market trends. This involves designing, modelling, analysing, interpretation, maintenance etc., of data sets. The skills required for these jobs include:
→ strong technical and analytical skills.
→ background of engineering, computer science or related fields
→ experience of business and markets

• Research Scientist
Research scientist is related to research in the field of artificial intelligence. They research and advance our knowledge of Als. The skills required for these jobs include:
→ master's or doctorate degree in computer science or related fields
→ strong background in applied mathematics

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