Introduction to Emerging Technologies PDF

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E m erg i ng d ucti o n to Intro es lo g i Techno 1  Objective After completing this chapter, the students will be able to: Deve...

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CHAPT
E m erg i ng d ucti o n to Intro es lo g i Techno 1  Objective After completing this chapter, the students will be able to: Develop knowledge about the era of industrial evolutions Identify the technological advances that made the industrial revolution possible Analyze the changing conditions created by the industrial revolution in both Europe and the united states Understand the causes of the Industrial Revolution in Great Britain, continental Europe, and the United States. Describe the technological innovations that spurred industrialization Identifies and understand the programmable device Understand concepts relating to the design of human-computer interfaces in ways making computer-based systems 2 comprehensive, friendly and usable.  Emerging Technology Activity 1.1 1. Define emerging technologies? 2. Define Technology and Evolution in the context of your prior knowledge and compare it with the discussion given below? Emerging technology is used to describe a new technology, but it may also refer to the continuing development of existing technology. It can have slightly different meanings when used in different areas, such as media, business, science, or education. It also refers to technologies that are currently developing, or that are expected to be available within the next five to ten years. It is usually reserved for technologies that are creating or are expected to create significant social or economic effects. 3  Cont’d… Technology: 1610s, "discourse or treatise on an art or the arts," from Greek tekhnologia "systematic treatment of an art, craft, or technique," originally referring to grammar, from tekhno- (see techno-) + -logy. The meaning "science of the mechanical and industrial arts " is first recorded in 1859. Evolution: it means the process of developing by gradual changes. This noun is from Latin evolutio, "an unrolling or opening," combined from the prefix e-, "out," plus volvere, "to roll." ❖ Technological evolution is a theory of radical transformation of society through technological development. Activity 1.2 List out at list top five currently available emerged technologies? Gage univeristy department of IT emerging technology By Amare Seifu 4  Cont’d… ❖ List of some currently available emerged technologies ✔ Artificial Intelligence ✔ DevOps ✔ Block chain ✔ Internet of Things (IoT) ✔ Augmented Reality and Virtual Reality✔ Intelligent Apps (I-Apps) ✔ Cloud Computing ✔ Big Data ✔ Angular and React ✔ Robotic Processor Automation (RPA) 5 Introduction to the Industrial Revolution (IR) The Industrial Revolution was a period of major industrialization and innovation that took place during the late 1700s and early 1800s. Its core occurs when a society shifts from using tools to make products to use new sources of energy, such as coal , to power machines in factories. The revolution started in England, with a series of innovations to make labor more efficient and productive. It was a time when the manufacturing of goods moved from small shops and homes to large factories. This shift brought about changes in culture as people moved from rural areas to big cities in order to work. Generally, the following industrial revolutions fundamentally changed and transfer the world around us into modern society. ∙ The steam engine, ∙ The age of science and mass production, and ∙ The rise of digital technology 6  Cont’d… The American Industrial Revolution commonly referred to as the Second Industrial Revolution, started sometime between 1820 and 1870. The impact of changing the way items was manufactured had a wide reach. Industries such as textile manufacturing, mining, glass making, and agriculture all had undergone changes. For example, prior to the Industrial Revolution, textiles were primarily made of wool and were handspun. From the first industrial revolution (mechanization through water and steam power) to the mass production and assembly lines using electricity in the second, the fourth industrial revolution will take what was starte d in th e th ird with th e adoption of compu te rs an d automation and enhance it with smart and autonomous systems fueled by data and machine learning. 7  Cont’d… Activity 1.3 What are the most important inventions of industrial revolutions? The Most Important Inventions of the Industrial Revolution are: ❖ Transportation: ❖ Communication: ✔ Steam Engine, ✔Telegraph, ✔ Railroad, ✔Transatlantic Cable, ✔ Diesel Engine, & ✔Phonograph, ✔ Airplane. ✔Telephone ❖ Industry: ✔ Cotton Gin ✔ Sewing Machine ✔ Electric Lights 8 Historical Background (IR 1.0, IR 2.0, IR 3.0) The industrial revolution began in Great Britain in the late 1770s before spreading to the rest of Europe. The first European countries to be industrialized after England were Belgium, France, and the German states. The final cause of the Industrial Revolution was the effects created by the Agricultural Revolution. As previously stated, the Industrial Revolution began in Britain in the 18th century due in part to an increase in food production, which was the key outcome of the Agricultural Revolution. The four types of industries are: ✔ The primary industry involves getting raw materials e.g. mining, farming, and fishing. ✔ The secondary industry involves manufacturing e.g. making cars and steel. ✔ Tertiary industries provide a service e.g. teaching and nursing. ✔ The quaternary industry involves research and development industries 9  Cont’d… 1. Industrial Revolution (IR 1.0) The Industrial Revolution (IR) is described as a transition to new manufacturing processes. IR was first coined in the 1760s, during the time where this revolution began. The transitions in the first IR included going from hand production methods to machines, the increasing use of steam power (see Figure 1.1), the development of machine tools and the rise of the factory system. Figure 1.1 steam engine 10  Cont.… 2. Industrial Revolution (IR 2.0) The Second IR, also known as the Technological Revolution, began somewhere in the 1870s. The advancements in IR 2.0 included the development of methods for manufacturing interchangeable parts and widespread adoption of pre-existing technological systems such as telegraph and railroad networks. This adoption allowed the vast movement of people and ideas, enhancing communication. Moreover, new technological systems were introduced, such as electrical power (see Figure 1.2) and telephones. Figure 1.2. Electricity transmission line 11 3. Industrial Revolution (IR 3.0) Cont’d… IR 3.0 introduced the transition from mechanical and analog electronic technology to digital electronics (see Figure 1.3) which began from the late 1950s. Due to the shift towards digitalization, IR 3.0 was given the nickname, “Digital Revolution ”. The core factor of this revolution is the mass production and widespread use of digital logic circuits and its derived technologies such as the computer, handphones and the Internet. These technological innovations have arguably transformed traditional production and business techniques enabling people to communicate with another without the need of being physically present. Certain practices that were enabled during IR 3.0 is still being practiced until this current day, for example – the proliferation of digital computers and digital record. Figure 1.3 High Tech Electronics 12  Cont’d… Activity 1.4 What do you think that IR 4.0 differs from the previous IR (i.e. 1-3)? 4. Fourth Industrial Revolution (IR 4.0) Now, with advancements in various technologies such as robotics, Internet of Things (IoT see Figure 1.4), additive manufacturing and autonomous vehicles. IR 4.0 was coined by Klaus Schwab, the founder and executive chairman of World Economic Forum, in the year 2016. The technologies mentioned above are what you call – cyber- physical systems. A cyber-physical system is a mechanism that is controlled or monitored by computer-based algorithms, tightly integrated with the Internet and its users. Gage univeristy department of IT emerging technology By Amare Seifu 13 Cont’d… Figure 1. 4 Anybody Connected device (ABCD) Activity 1.5 Discus about Agricultural Revolutions, Information Revolutions and level of the industrial revolution in Ethiopia and also compare with UK, USA, and China? 14  Human to Machine Interaction Human-machine interaction (HMI) refers to the communication and interaction between a human and a machine via a user interface. Nowadays, natural user interfaces such as gestures have gained increasing attention as they allow humans to control machines through natural and intuitive behaviors What is interaction in human-computer interaction? ✔HCI is the study of how people interact with computers and to what extent computers are or are not developed for successful interaction with human beings. ✔As its name implies, HCI consists of three parts: the user, the computer itself, and the ways they work together. 15  How do users interact with computers? Cont’d… ✔ The user interacts directly with hardware for the human input and output such as displays, e.g. through a graphical user interface. ✔ The user interacts with the computer over this software interface Future using the Trends given input and in Emerging output (I/O) hardware. Technologies ❖ Emerging technology trends in 2019 ✔ 5G Networks ✔ Digital Twins ✔ Artificial Intelligence (AI) ✔ Enhanced Edge Computing and ✔ Autonomous Devices ✔ Im m e r siv e E xp e r ie nc e s in S m a r t Spaces ✔ Blockchain ✔ Augmented Analytics 16  TE R two

CHAP
e ata Sci enc cti o n to D Introdu
Gage univeristy department of IT emerging technology By Amare Seifu 17  Objective After completing this chapter, the students will be able to: Describe what data science is and the role of data sc Differentiate data and information. Describe data processing life cycle Understand different data types from diverse perspec Describe data value chain in emerging era of big data Understand the basics of Big Data. Describe the purpose of the Hadoop ecosystem com Gage univeristy department of IT emerging technology By Amare Seifu 18  An Overview of Data Science Activity 2.1 What is data science? Can you describe the role of data in emerging technology? What are data and information? What is big data? Data science is a multi-disciplinary field that uses scientific methods, processes, algorithms, and systems to extract knowledge and insights from structured, semi-structured and unstructured data. Data science is much more than simply analyzing data. It offers a range of roles and requires a range of skills. Gage univeristy department of IT emerging technology By Amare Seifu 19  What are data and information? Data can be defined as a representation of facts, concepts, or instructions in a formalized manner, which should be suitable for communication, interpretation, or processing, by human or electronic machines. It can be described as unprocessed facts and figures. It is represented with the help of characters such as alphabets (A-Z, a- z), digits (0-9) or special characters (+, -, /, *, , =, etc.). Information is the processed data on which decisions and actions are based. It is data that has been processed into a form that is meaningful to the recipient and is of real or perceived value in the current or the prospective action or decision of recipient. Furtherer more, information is interpreted data; Gage univeristy created department from organized, structured, of IT emerging 20 technology By Amare Seifu  Cont’d… Activity 2.2 Describe in some detail the main disciplines that contribute to data science. Let the teacher explain the role of data scientists and students may write a small report on the same. D at a P roc e s s i n g Data processing isCycle the re-structuring or re-ordering of data by people or machines to increase their usefulness and add values for a particular purpose. Data processing consists of the following basic steps - input, processing, and output. These three steps constitute the data processing cycle. Figure 2.1 Data Processing Gage univeristy department of IT emerging Cycle technology By Amare Seifu 21  Cont’d… Input − the input data is prepared in some convenient form for processing. The form will depend on the processing machine. ✔ For example, when electronic computers are used, the input data can be recorded on any one of the several types of storage medium, such as hard disk, CD, flash disk and so on. Processing − the input data is changed to produce data in a more useful form. ✔ For example, interest can be calculated on deposit to a bank, or a summary of sales for the month can be calculated from the sales orders. Output − the result of the proceeding processing step is collected. The particular form of the output data depends on the use of the data. ✔ For example, output Gage data univeristymay be of department payroll for employees. IT emerging 22 technology By Amare Seifu  Cont’d… Activity 2.3 Discuss the main differences between data and information with examples. Can we process data manually using a pencil and paper? Discuss the differences with data processing using the computer. Data types and their representation ❖ Data types can be described from diverse perspectives. In computer science and computer programming, for instance, a data type is simply an attribute of data that tells the compiler or interpreter how the programmer intends to use the data. Gage univeristy department of IT emerging technology By Amare Seifu 23  Cont’d… 1. Data types from Computer programming perspective ❖ Almost all programming languages explicitly include the notion of data type, though different languages may use different terminology. Common data types include: ✔ Integers(int)- is used to store whole numbers, mathematically known as integers ✔ Booleans(bool)- is used to represent restricted to one of two values: true or false ✔ Characters(char)- is used to store a single character ✔ Floating-point numbers(float)- is used to store real numbers ✔ Alphanumeric strings(string)- used to store a combination of characters and numbers ❖ A data type makes the values that expression, such as a variable or a function, might take. Gage Thisuniveristy datadepartment type defines the operations that can be of IT emerging technology By Amare Seifu 24 2. Data types from Data Analytics Cont’d… perspective From a data analytics point of view, it is important to understand that there are three common types of data types or structures: Structured, Semi-structured, and Unstructured data types. Fig. 2.2 below describes the three types of data and metadata. Figure 2.2 Data types from a data analytics perspective Gage univeristy department of IT emerging technology By Amare Seifu 25 Structured Data Cont’d… ✔ Structured data is data that adheres to a pre-defined data model and is therefore straightforward to analyze. ‘ ✔ It conforms to a tabular format with a relationship between the different rows and columns. ✔ Common examples of structured data are Excel files or SQL databases. Each of these has structured rows and columns that can be sorted. Semi-structured Data ✔ Semi-structured data is a form of structured data that does not conform with the formal structure of data models associated with relational databases or other forms of data tables, but nonetheless, contains tags or other markers to separate semantic elements and enforce hierarchies of records and fields within the data. ✔ Therefore, it is also known as adepartment Gage univeristy self-describing of IT emerging structure. technology By Amare Seifu 26  Cont’d… Unstructured Data ✔ Unstructured data is information that either does not have a predefined data model or is not organized in a pre-defined manner. ✔ Unstructured information is typically text-heavy but may contain data such as dates, numbers, and facts as well. ✔ This results in irregularities and ambiguities that make it difficult to understand using traditional programs as compared to data stored in structured databases. ✔ Common examples of unstructured data include audio, video files or No- SQL databases. Gage univeristy department of IT emerging technology By Amare Seifu 27  Metadata – Data about Data The last category of data type is metadata. From a technical point of view, this is not a separate data structure, but it is one of the most important elements for Big Data analysis and big data solutions. Metadata is data about data. It provides additional information about a specific set of data. In a set of photographs, for example, metadata could describe when and where the photos were taken. The metadata then provides fields for dates and locations which, by themselves, can be considered structured data. Because of this reason, metadata is frequently used Activity 2.4 by Big data Discuss Datatypes solutions for initial and from programing analysis. analytics perspectives. Compare metadata with structured, unstructured and semi-structured data Given at least one example of structured, unstructured and semi-structured data types Gage univeristy department of IT emerging technology By Amare Seifu 28  Data value Chain Data Value Chain is introduced to describe the information flow within a big data system as a series of steps needed to generate value and useful insights from data. The Big Data Value Chain identifies the following key high-level activities: Figure 2.3 Data Value Chain Gage univeristy department of IT emerging technology By Amare Seifu 29 1. Data Acquisition Cont’d… It is the process of gathering, filtering, and cleaning data before it is put in a data warehouse or any other storage solution on which data analysis can be carried out. Data acquisition is one of the major big data challenges in terms of infrastructure requirements. The infrastructure required to support the acquisition of big data must deliver low, predictable latency in both capturing data and in executing queries; be able to handle very high transaction volumes, often in a distributed environment; and support flexible and 2. Data Analysis dynamic data structures. ✔ It is concerned with making the raw data acquired amenable to use in decision-making as well as domain-specific usage. ✔ Data analysis involves exploring, transforming, and modeling data with the goal of highlighting relevant data, synthesizing and extracting useful hidden information with high potential from a business point of view. ✔ Related areas include data mining, business intelligence, and machine Gage univeristy department of IT emerging learning. technology By Amare Seifu 30 3. Data Curation Cont’d… It is the active management of data over its life cycle to ensure it meets the necessary data quality requirements for its effective usage. Data curation processes can be categorized into different activities such as content creation, selection, classification, transformation, validation, and preservation. Data curation is performed by expert curators that are responsible for improving the accessibility and quality of data. Data curators (also known as scientific curators or data annotators) hold the responsibility of ensuring that data are trustworthy, discoverable, accessible, reusable and fit their purpose. A key trend for the duration of big data utilizes community and crowdsourcing approaches. Gage univeristy department of IT emerging technology By Amare Seifu 31  Cont’d… 4. Data Storage It is the persistence and management of data in a scalable way that satisfies the needs of applications that require fast access to the data. Relational Database Management Systems (RDBMS) have been the main, and almost unique, a solution to the storage paradigm for nearly 40 years. However, the ACID (Atomicity, Consistency, Isolation, and Durability) properties that guarantee database transactions lack flexibility with regard to schema changes and the performance and fault tolerance when data volumes and complexity grow, making them unsuitable for big data scenarios. NoSQL technologies have been designed with the scalability goal in mind and present a wide range of solutions based on alternative data Gage univeristy department of IT emerging models. technology By Amare Seifu 32  Cont’d… 5. Data Usage It covers the data-driven business activities that need access to data, its analysis, and the tools needed to integrate the data analysis within the business activity. Data usage in business decision-making can enhance competitiveness through the reduction of costs, increased added value, or any other parameter that can be measured against existing Activity 2.5 performance criteria. Which information flow step in the data value chain you think is labor- intensive? Why? What are the different data types and their value chain? Gage univeristy department of IT emerging technology By Amare Seifu 33  Cont’d… Big data is characterized by 3V and ✔ more: Volume: large amounts of data Zeta bytes/Massive datasets ✔ Velocity: Data is live streaming or in motion ✔ Variety: data comes in many different forms from diverse sources ✔ Veracity: can we trust the data? How accurate is it? etc. Figure 2.4 Characteristics of big data Gage univeristy department of IT emerging technology By Amare Seifu 34  ER THR EE C HAPT n ce ( AI )

ial I n tel l ige Artif ic

Gage univeristy department of IT emerging technology By Amare Seifu 35  Objective After completing this chapter, the students will be able to: Explain what artificial intelligence (AI) is. Describe the eras of AI. Explain the types and approaches of AI. Describe the applications of AI in health, agriculture, business and education List the factors that influenced the advancement of AI in recent years. Understand the relationship between the human’s way of thinking and AI systems Identify AI research focus areas. Identify real-world AI applications, some platforms, and tools. Gage univeristy department of IT emerging technology By Amare Seifu 36  Artificial Intelligence (AI) Artificial Intelligence is composed of two words Artificial and Intelligence. Activity 3.1 How do you define the word Artificial? And the word Intelligence? Artificial defines "man-made," and intelligence defines "thinking power", or “the ability to le arn and solve proble ms” he nce Artificial Intelligence means "a man-made thinking power." So, we can define Artificial Intelligence (AI) as the branch of computer science by which we can create intelligent machines which can behave like a human, think like humans, and able to make decisions. Gage univeristy department of IT emerging technology By Amare Seifu 37  Cont’d… Intelligence, as we know, is the ability to acquire and apply knowledge. Knowledge is the information acquired through experience. Experience is the knowledge gained through exposure (training). Summing the terms up, we get artificial intelligence as the “copy of something natural (i.e., human beings) ‘WHO’ is capable of acquiring and applying the information it has gained through exposure.” Activity 3.2 What do you think to make the machine think and make a decision like human beings do? Gage univeristy department of IT emerging technology By Amare Seifu 38  Cont’d… Artificial Intelligence exists when a machine can have human-based skills such as learning, reasoning, and solving problems with Artificial Intelligence you do not need to preprogram a machine to do some work, despite that you can create a machine with programmed algorithms which can work with own intelligence. ✔ Perception Intelligence is composed of: ✔ Linguistic Intelligence ✔ Reasoning ✔ Learning ✔ Problem Solving An AI system is composed of an agent and its environment. An agent (e.g., human or robot) is anything that can perceive its environment through sensors and acts upon that environment through effectors. Gage univeristy department of IT emerging technology By Amare Seifu 39  Cont’d… Many times, students get confused between Machine Learning and Artificial Intelligence (see figure 3.1), but Machine learning, a fundamental concept of AI research since the field’s inception, is the study of computer algorithms that improve automatically through experience. The term machine learning was introduced by Arthur Samuel in 1959. Neural networks are biologically inspired networks that extract features from the data in a hierarchical fashion. The field of neural networks with several hidden n ce (AI), layers is called deep learning. In tellig e if icia l u re 3. 1 Art M L ) and F ig rning ( e L e a Machin in g (DL) ea rn Deep L Gage univeristy department of IT emerging technology By Amare Seifu 40  Cont’d… Activity 3.3 Why we need AI at this time? Need for Artificial ✔ Intelligence To create expert systems that exhibit intelligent behavior with the capability to learn, demonstrate, explain and advice its users. ✔ Helping machines find solutions to complex problems like humans do and applying them as algorithms in a computer-friendly manner. Activity 3.4 You have been learned about AI and the need for it. What do you think the main goal of the advancement in AI? Gage univeristy department of IT emerging technology By Amare Seifu 41  Goals of Artificial Cont’d… ❖ Intelligence Following are the main goals of Artificial Intelligence: ✔ Replicate human intelligence ✔ Solve Knowledge-intensive tasks ✔ An intelligent connection of perception and action ✔ Building a machine which can perform tasks that requires human intelligence such as: ▪ Proving a theorem ▪ Playing chess ▪ Plan some surgical operation ▪ Driving a car in traffic ✔ Creating some system which can exhibit intelligent behavior, learn new things by itself, demonstrate, explain, and can advise to its Gage univeristy department of IT emerging user. technology By Amare Seifu 42  Advantages of Artificial Intelligence Activity 3.6 What do we get from using AI technology instead of previous reactive ❖ technology? Following are some main advantages of Artificial Intelligence: ✔ High Accuracy with fewer errors: AI machines or systems are prone to fewer errors and high accuracy as it takes decisions as per pre-experience or information. ✔ High-Speed: AI systems can be of very high-speed and fast- decision making, because of that AI systems can beat a chess champion in the Chess game. ✔ High reliability: AI machines are highly reliable and can perform the same action multiple times with high accuracy. ✔ Useful for risky areas: AI machines can be helpful in situations such as defusing a bomb, exploring the ocean floor, where to employ a humanGage can be risky. univeristy department of IT emerging technology By Amare Seifu 43  Cont’d… ✔ Digital Assistant: AI can be very useful to provide digital assistant to use rs such as AI te chnology is curre ntly use d by various E- commerce websites to show the products as per customer requirements. ✔ Useful as a public utility: AI can be very useful for public utilities such as a self-driving car which can make our journey safer and hassle- free, facial recognition for security purposes, Natural language processing (for search engines, for spelling checker, for assistant like Siri, for translation like google Disadvantages translate),Intelligence of Artificial etc. Activity 3.7 As we all know, engineering is a tradeoff; improving or enhancing in one aspect will lead you to worsen or deteriorating in another aspect. In the previous chapter, weGage have learned univeristy the department of ITadvantages emerging of AI; write down technology By Amare Seifu 44  Cont’d… Following are the disadvantages of AI: ✔ High Cost: The hardware and software requirement of AI is very costly as it requires lots of maintenance to meet current world requirements. ✔ Can't think out of the box: Even we are making smarter machines with AI, but still they cannot work out of the box, as the robot will only do that work for which they are trained, or programmed. ✔ No feelings and emotions: AI machines can be an outstanding performer, but still it does not have the feeling so it cannot make any kind of emotional attachment with humans, and may sometime be harmful for users if the proper care is not taken. ✔ Increase dependence on machines: With the increment of technology, people are getting more dependent on devices and hence they are losing their mental capabilities. ✔ No Original Creativity: As humans are so creative and can imagine some new ideas but still AI machines cannot beat this power of human intelligence and cannot be creative and imaginative. Gage univeristy department of IT emerging technology By Amare Seifu 45  Levels of AI Cont’d… Stage 1 – Rule-Based Systems The most common uses of AI today fit in this bracket, covering everything from business software (Robotic Process Automation) and domestic appliances to aircraft autopilots. Stage 3 – Context Awareness and Retention Algorithms that develop information about the specific domain they are being applied in. They are trained on the knowledge and experience of the best humans, and their knowledge base can be updated as new situations and queries arise. Well, known applications of this level are chatbots and “roboadvisors ”. Gage univeristy department of IT emerging technology By Amare Seifu 46  Cont’d… Stage 3 – Domain-Specific Expertise Going beyond the capability of humans, these systems build up expertise in a specific context taking in massive volumes of information which they can use for decision making. Successful use cases have been seen in cancer diagnosis and the well-known Google Deepmind’s AlphaGo. Currently, this type is limited to one domain only would forget all it knows about that domain if you started to teach it something else. Stage 4 – Reasoning Machines These algorithms have some ability to attribute mental states to themselves and others. they have a sense of beliefs, intentions, knowledge, and how their own logic works. This means they could reason or negotiate with humans and other machines. At the moment these algorithms are still in development, Gage univeristy department of IT emerging however, commercial applications technology By Amareare expected within the next few Seifu 47  Cont’d… Stage 5 – Self Aware Systems / Artificial General Intelligence (AGI) These systems have human-like intelligence – the most commonly portrayed AI in media – however, no such use is in evidence today. It is the goal of many working in AI and some believe it could be realized already from 2024. Stage 6 – Artificial Superintelligence (ASI) AI algorithms can outsmart even the most intelligent humans in every domain. Logically it is difficult for humans to articulate what the capabilities might be, yet we would hope examples would include solving problems we have failed to so far, such as world hunger and dangerous environmental change. Views vary as to when and whether such a capability could even be possible, yet there a few experts who claim it can be realized by 2029. Fiction Gage univeristy department of IT emerging technology By Amare Seifu 48 Stage 7 – Singularity and Transcendence This is the idea that development provided by ASI (Stage 6) leads to a massive expansion in human capability. Human augmentation could connect our brains to each other and to a future successor of the current internet, creating a “hive mind” that shares ideas, solves problems collectively, and even gives others access to our dreams as observers or participants. Pushing this idea further, we might go beyond the limits of the human body and connect to other forms of intelligence on the planet – animals, plants, weather systems, and the natural environment. Some proponents of singularity such as Ray Kurzweil, Google’s Director of Engineering, suggest we could see it happen by 2045 as a result of e xpon e n tial rate s of progre ss across a ran ge of scie n ce an d technology disciplines. The other side of the fence argues that Gage univeristy department of IT emerging singularity is impossible and human consciousness could never technology By Amare Seifu 49 be  Cont’d… Figure 3.4 The seven layers of AI maturity Gage univeristy department of IT emerging technology By Amare Seifu 50  Types of AI Activity 3.10 Since AI is making a machine intelligent, based on the strength of intelligence and functionality, list down some types or classification of AI? Intelligence can be divided into various types, there are Artificial mainly two types of the main categorization which are based on capabilities and based on functionally of AI, as shown in figure 3.5. Following is the flow diagram which explains the types of AI. A. Based on Capabilities 1. Weak AI or Narrow AI: Narrow AI is a type of AI which is able to perform a dedicated task with intelligence. The most common and currently available AI is Narrow AI in the world of Artificial Intelligence. Gage univeristy department of IT emerging technology By Amare Seifu 51  Cont’d… Figure 3.5 types of Artificial Intelligence (AI) Narrow AI cannot perform beyond its field or limitations, as it is only trained for one specific task. Hence it is also termed as weak AI. Narrow AI can fail in unpredictable ways if it goes beyond its limits. Apple Siri is a good example of Narrow AI, but it operates with Gage univeristy department of IT emerging technology By Amare Seifu 52 a limited pre-defined range of functions.  Cont’d… IBM's Watson supercomputer also comes under Narrow AI, as it uses an Expert system approach combined with Machine learning and natural language processing. Some Examples of Narrow AI are Google translate, playing chess, purchasing suggestions on e-commerce sites, self-driving cars, speech recognition, and image recognition. 2. General AI: ✔ General AI is a type of intelligence that could perform any intellectual task with efficiency like a human. ✔ The idea behind the general AI to make such a system that could be smarter and think like a human on its own. ✔ Currently, there is no such system exists which could come under general AI and can perform any task as perfect as a human. It may arrive within the next 20 or so years but it has challenges relating to hardware, the energy Gageconsumption required univeristy department of IT emerging in today’s powerful technology By Amare Seifu 53 machines, and the need to solve for catastrophic memory loss that  Cont’d… ✔ The worldwide researchers are now focused on developing machines with General AI. ✔ As systems with general AI are still under research, and it will take lots of effort and time to develop such systems. 3. Super AI: Super AI is a level of Intelligence of Systems at which machines could surpass human intelligence, and can perform any task better than a human with cognitive properties. This refers to aspects like general wisdom, problem solving and creativity. It is an outcome of general AI. Some key characteristics of strong AI include capability include the ability to think, to reason solve the puzzle, make judgments, plan, learn, and communicate on its own. Super AI is still a hypothetical concept of Artificial Intelligence. The Gage univeristy department of IT emerging development of such systems inAmare technology By realSeifu is still a world-changing task. 54 B. Based on the functionality Cont’d… 1. Reactive Machines Purely reactive machines are the most basic types of Artificial Intelligence. Such AI systems do not store memories or past experiences for future actions. These machines only focus on current scenarios and react on it as per possible best action. IBM's Deep Blue system is an example of reactive machines. Google's AlphaGo is also an example of reactive machines. 2. Limited Memory Limited memory machines can store past experiences or some data for a short period of time. These machines can use stored data for a limited time period only Gage univeristy department of IT emerging Self-driving cars are one of the best examples of Limited Memory technology By Amare Seifu 55 3. Theory of Mind Cont’d… Theory of Mind AI should understand human emotions, people, beliefs, and be able to interact socially like humans. This type of AI machines is still not developed, but researchers are making lots of efforts and improvement for developing such AI machines. 4. Self-Awareness Self-awareness AI is the future of Artificial Intelligence. These machines will be super intelligent and will have their own consciousness, sentiments, and self- awareness. These machines will be smarter than the human mind. Self-Awareness AI does not exist in reality still and it is a hypothetical concept. Gage univeristy department of IT emerging technology By Amare Seifu 56  How humans Cont’d… think Activity 3.11 From the previous discussion, General AI is intelligence that could perform any intellectual task with efficiency like a human. So, to achieve this intelligence level, do you think that future intelligence must mimic the way humans think? If your answer is yes, why? The goal of many researchers is to create strong and general AI that learns like a human and can solve general problems as the human brain does. Achieving this goal might require many more years. How does a human being think? Intelligence or the cognitive process is composed of three main stages: ▪ Observe and input the information or data in the brain. ▪ Interpret and evaluate the input that is received from the surrounding environment. ▪ Make decisions as a reaction towards what you received as input and interpreted and evaluated. AI researchers are simulating the same stages in building AI systems or models. This process represents the main three layers or Gage univeristy department of IT emerging 57 components of AI systems. technology By Amare Seifu  Cont’d… Mapping human thinking to artificial intelligence components Activity 3.12 Is it possible to map the way of human thinking to artificial intelligence components? If your answer is yes, why? Because AI is the science of simulating human thinking, it is possible to map the human thinking stages to the layers or components of AI systems. In the first stage, humans acquire information from their surrounding environments through human senses, such as sight, hearing, smell, taste, and touch, through human organs, such as eyes, ears, and other sensing organs, for example, the hands. Gage univeristy department of IT emerging technology By Amare Seifu 58  Cont’d… In AI models, this stage is represented by the sensing layer, which perceives information from the surrounding environment. This information is specific to the AI application. For example, there are sensing agents such as voice recognition for sensing voice and visual imaging recognition for sensing images. Thus, these agents or sensors take the role of the hearing and sight senses in humans. The second stage is related to interpreting and evaluating the input data. In AI, this stage is represented by the interpretation layer, that is, reasoning and thinking about the gathered input that is acquired by the sensing layer. The third stage is related to taking action or making decisions. After evaluating the input data, the interacting layer performs the necessary tasks. Robotic movement control and speech generation are examples of functions that Gage univeristy are implemented department of IT emerging technology By Amare Seifu in the interacting 59  Influencers of artificial intelligence Activity 3.13 List down some influential factors that accelerate the rise of AI? The following influencers of AI are described in this section: Big data: Structured data versus unstructured data Advancements in computer processing speed and new chip architectures Cloud computing and APIs The emergence of data science Gage univeristy department of IT emerging technology By Amare Seifu 60  Cont’d… Big Data Activity 3.14 From chapter two, what is big data? Where do you get big data? Big data refers to huge amounts of data. It requires innovative forms of information processing to draw insights, automate processes, and help decision making. It can be structured data that corresponds to a formal pattern, such as traditional data sets and databases. Big data includes semi-structured and unstructured formats, such as word-processing documents, videos, images, audio, presentations, social media interactions, streams, web pages, and many other kinds of content. Figure 3.6 depicts the rapid change of the data landscape. Gage univeristy department of IT emerging technology By Amare Seifu 61  Cont’d… Figure 3.6 Current changes in the data landscape Gage univeristy department of IT emerging technology By Amare Seifu 62  Structured data versus unstructured Cont’d… data Activity 3.15 What is structured and unstructured data mean? Where do you get structured and unstructured data? Which one of them is better to analyze? Which of the two is the influencer of AI? Is AI important to analyze structured or unstructured data? Why? Traditionally, computers primarily process structured data, that is, information with an organized structure, such as a relational database that is searchable by simple and straightforward search engine algorithms or SQL statements. But, real-world data such as the type that humans deal with constantly does not have a high degree of organization. For example, text that is written or spoken in natural language (the language that humans speak) does not constitute structured data. Unstructured data is not contained in a regular database and is growing exponentially, making up most of the data in the world. The exponential growth of unstructured data that is shown in Figure Gage univeristy department of IT emerging technology By Amare Seifu 63  Cont’d… Traditionally, computers primarily process structured data, that is, information with an organized structure, such as a relational database that is searchable by simple and straightforward search engine algorithms or SQL statements. But, real-world data such as the type that humans deal with constantly does not have a high degree of organization. For example, text that is written or spoken in natural language (the language that humans speak) does not constitute structured data. Unstructured data is not contained in a regular database and is growing exponentially, making up most of the data in the world. The exponential growth of unstructured data that is shown in Figure 3.7 below drives the need for a new kind of computer system. Gage univeristy department of IT emerging technology By Amare Seifu 64  Cont’d… Figure 3.7 The comparison between the growth of structured and unstructured data Gage univeristy department of IT emerging technology By Amare Seifu 65  Applications of AI Artificial Intelligence has various applications in today's society. It is becoming essential for today's time because it can solve complex problems in an efficient way in multiple industries, such as Healthcare, entertainment, finance, education, etc. AI is making our daily life more comfortable and faster. Activity 3.18 Having said that, AI is making our daily life more comfortable and faster in different sectors. Write down some applications of AI in health, agriculture, education, and business? Gage univeristy department of IT emerging technology By Amare Seifu 66  Cont’d… Following are some sectors which have the application of Artificial Intelligence: 1. AI in agriculture Agriculture is an area that requires various resources, labor, money, and time for the best result. Now a day's agriculture is becoming digital, and AI is emerging in this field. Agriculture is applying AI as agriculture robotics, solid and crop monitoring, predictive analysis. AI in agriculture can be very helpful for farmers. 2. AI in Healthcare In the last, five to ten years, AI becoming more advantageous for the healthcare industry and going to have a significant impact on this industry. Healthcare Industries are applying Gage univeristy department ofAI to make a better and faster IT emerging technology By Amare Seifu 67  Cont’d… 3. AI in education: AI can automate grading so that the tutor can have more time to teach. AI chatbot can communicate with students as a teaching assistant. AI in the future can be work as a personal virtual tutor for students, which will be accessible easily at any time and any place. 4. AI in Finance and E-commerce AI and finance industries are the best matches for each other. The finance industry is implementing automation, chat bot, adaptive intelligence, algorithm trading, and machine learning into financial processes. AI is providing a competitive edge to the e-commerce industry, and it is becoming more demanding in the e-commerce Gage univeristy department of IT emerging technology By Amare Seifu 68 business. AI is helping shoppers to discover associated 5. AI in Gaming Cont’d… AI can be used for gaming purposes. The AI machines can play strategic games like chess, where the machine needs to think of a large number of possible places. 6. AI in Data Security The security of data is crucial for every company and cyber-attacks are growing very rapidly in the digital world. AI can be used to make your data more safe and secure. Some examples such as AEG bot, AI2 Platform, are used to determine software bugs and cyber- attacks in a better way. 7. AI in Social Media Social Media sites such as Facebook, Twitter, and Snapchat contain billions of user profiles, which need to be stored and managed in a very efficient way. AI can organize and manage massive amounts of data. AI can analyze lots of data to identify69the Gage univeristy department of IT emerging technology By Amare Seifu  Cont’d… 8. AI in Travel &Transport AI is becoming highly demanding for travel industries. AI is capable of doing various travel related works such as from making travel arrangements to suggesting the hotels, flights, and best routes to the customers. Travel industries are using AI- powered chatbots which can make human-like interaction with customers for a better and fast response. 9. AI in the Automotive Industry Some Automotive industries are using AI to provide virtual assistants to their use for better performance. Such as Tesla has introduced TeslaBot, an intelligent virtual assistant. Various Industries are currently working for developing self- driven cars which can make your journey more safe and secure. Gage univeristy department of IT emerging technology By Amare Seifu 70 10. AI in Robotics: Cont’d… Artificial Intelligence has a remarkable role in Robotics. Usually, general robots are programmed such that they can perform some repetitive task, but with the help of AI, we can create intelligent robots which can perform tasks with their own experiences without pre-programmed. Humanoid Robots are the best examples for AI in robotics, recently the intelligent Humanoid robot named Erica and Sophia has been developed which can talk and behave like humans. 11. AI in Entertainment We are currently using some AI-based applications in our daily life with some entertainment services such as Netflix or Amazon. With the help of ML/AI algorithms, these services show the recommendations for programs or shows. 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