Recent Developments in the Field of IT

Technology trends represent the latest shifts in the industry, and with the
internet’s influence, these changes occur rapidly. For professionals in the
software industry, staying updated with these trends is crucial. As we
progress into 2023, there are emerging technology trends that will shape our
futuristic world.
1. Artificial Intelligence (AI) and Machine Learning (ML)
2. Internet of Things (IoT)
3. 5G
4. Virtual and augmented reality (VR/AR)
5. Robotic Process Automation (RPA)
6. Blockchain
7. Quantum Computing
8. Datafication
9. Renewable Energy
10. Autonomous Vehicles
11. Digital Twins
12. Edge Computing
13. Cybersecurity
14. 3D Printing
15. Human Augmentation

Artificial Intelligence (AI) and Machine Learning

(ML)
1. Artificial intelligence (AI) is a way to make computers smart and able to
do things that normally only humans can do, like learning, figuring things
out, and making choices.
2. Machine learning (ML) is a subset of AI that involves the use of
algorithms and statistical models to enable computers to learn and
improve their performance on a specific task without being explicitly
programmed. ML algorithms are trained using large datasets and can
make predictions or take actions based on the patterns and trends
identified in the data.
Some examples of how AI and ML are helping include:
1. Healthcare: AI and ML are being used to analyze medical records,
predict patient outcomes, and assist with diagnosis and treatment
planning.
2. Finance: AI and ML can help to analyze financial data, identify trends and
patterns, and make investment recommendations.
3. Retail: AI and ML can help in personalizing customer experiences,
optimizing pricing and inventory management, and improving supply
chain efficiency.
4. Manufacturing: AI and ML can also improve production processes,
reduce defects and downtime, and improve overall efficiency.
5. Transportation: AI and ML are being used to enhance routes, reduce
fuel consumption, and improve safety in the transportation industry.
6. Agriculture: One can use AI and ML to optimize crop management,
improve yields, and reduce waste.
7. Education: AI and ML will be able to personalize learning experiences,
assess student progress, and provide customized feedback.
Internet of Things (IoT)
The Internet of Things (IoT) refers to the growing network of physical
objects connected to the Internet that can communicate with each other and
share data. These connected devices can range from simple sensors to
more complex devices such as appliances, vehicles, and industrial
equipment. The usage of IoT is one of the emerging technology trends in the
electronics and software industry that is revolutionizing the entire human
behavior of using technology.
IoT devices can collect and transmit data, and they can be controlled
and accessed remotely through the internet. This allows for the creation
of new products and services that rely on connectivity and data sharing.
Some examples of how IoT is being used include:
1. Smart homes: IoT devices such as smart thermostats, security systems,
and lighting can be controlled and accessed remotely through a
smartphone or tablet.
2. Industrial applications: Monitor and optimize industrial processes, such
as energy usage and equipment maintenance.
3. Transportation: Improve safety and efficiency in the transportation
industry, for example by tracking the location and condition of vehicles
and providing real-time traffic updates.
4. Agriculture: Optimize crop management, improve yields, and reduce
waste.
Virtual and Augmented reality (VR/AR)
Augmented reality (AR), and Virtual reality (VR), pivotal technology
trends, are advanced computer technologies that have multiple uses such as
gaming, education, and healthcare. VR creates a computer-generated world
that a person can experience as if they were there, while AR adds computer-
generated images to a person’s view of the real world. Both have a wide
range of applications and are expected to continue to grow in industries and
applications in the future. VR has already been used for gaming, education,
training, and entertainment, and will likely continue to expand.
AR has also been used for enhancing the real world with additional
information, and will likely continue to be developed and used in new ways.
VR and AR also have potential in remote work and communication, as they
can create immersive virtual environments for people to work and interact
with each other remotely. In 2019, 14 million AR and VR gadgets were sold.
Robotic Process Automation (RPA)
Like AI and VR/MR, Robotics, a notable technology trend, is being
developed for a wide range of applications, including manufacturing,
healthcare, and transportation. Robotic Process Automation (RPA) is a
type of technology that allows organizations to automate repetitive, rule-
based tasks by creating digital workers or software robots to perform them.
RPA is designed to improve efficiency, reduce errors, and free up human
workers to focus on more complex and value-added tasks.

Blockchain
The use of blockchain technology, a significant technology trend, is expected
to continue to grow in 2023 and years after that, with potential applications in
areas such as supply chain management, finance, and other areas. It is
difficult to predict with certainty whether blockchain technology will “rule” in
2023 or not, as the adoption and use of blockchain technology depend on a
variety of factors such as market demand, regulatory environment, and the
availability of supporting infrastructure.
But blockchain technology will likely continue to be an important and
influential technology in 2023. As you know, Blockchain is a distributed
ledger technology that allows for the secure and transparent recording of
transactions, and it has the potential to transform a wide range of industries
by improving transparency, security, and efficiency.
Quantum Computing
Quantum computing a notable technology trend, is an emerging technology
that uses quantum-mechanical phenomena to process data. It is different
from classical computing which uses bits; quantum computers use qubits. In
comparison to classical computers, they are much faster at performing some
tasks.
Quantum computers have the potential to revolutionize fields such as
materials science, drug discovery, and financial modeling. It is still in the
early stages of development and has several technical challenges to
overcome before it can be widely used.
Many companies like Splunk, Honeywell, Microsoft, AWS, Google, etc are
working on developing quantum computing technology.

Digital Twins
Digital twin technology, a prominent technology trend, creates virtual
models of physical systems or processes, and it is expected to continue to
grow in popularity in 2023. Digital twins are digital representations of physical
objects, systems, or processes that can be used for simulation, analysis, and
optimization. They are created by collecting data from sensors and other
sources and using it to create a virtual model of the object or system being
represented.
Cybersecurity
Cybersecurity a crucial technology trend, refers to the practices and
technologies used to protect computer systems, networks, and devices from
cyber threats such as hacking, malware, and data breaches. As the use of
technology continues to grow and evolve, so do cybersecurity threats. The
importance of cybersecurity is expected to continue to grow as more devices
and systems become connected.
Several trends are expected to shape the future of cybersecurity. One
trend is the increasing use of cloud computing, which is the delivery of
computing services over the internet. Another trend is the growth of the
Internet of Things (IoT), which refers to the increasing number of devices
that are connected to the internet, such as smart home appliances, medical
devices, and industrial equipment. A third trend is the increasing use of
artificial intelligence (AI) and machine learning in cybersecurity.

Impact of IT on Organization
and Society
Positive Impacts of Technology on Modern Businesses:

Improved EfficiencyOne of the most significant positive

impacts of technology on modern businesses is improved
efficiency. With the help of technology, businesses can
automate various processes, such as inventory
management, order processing, and customer service,
leading to improved efficiency and reduced costs. For
instance, enterprises can use automated software to
manage inventory, eliminating manual counting and
reducing errors.

Enhanced CommunicationTechnology has also made it

easier for businesses to communicate with customers,
employees, and partners. Businesses can now use email,
chat, video conferencing, and other digital platforms to
communicate with stakeholders. This has not only
improved communication but also reduced the cost of
communication, especially for businesses with a global
reach.

Global Reach

Technology has enabled businesses to expand their reach

globally, allowing them to access new markets and
customers. For instance, businesses can now use e-
commerce platforms to sell their products to customers in
different parts of the world. Technology has also made it
easier for companies to enter new markets by providing
information about local markets and customer preferences.

Improved Customer Experience

Technology has significantly improved the customer

experience, making it easier for businesses to attract and
retain customers. With the help of technology, businesses
can collect customer data, such as purchase history and
preferences, which they can use to personalize the
customer experience. For instance, businesses can use
data to recommend products and services to customers,
increasing the likelihood of a sale.

Improved Collaboration
Technology has also improved collaboration among
employees, making it easier for them to work together on
projects. With the help of collaboration software,
employees can work on projects in real-time, share files,
and communicate with each other. This has improved
productivity and reduced the time it takes to complete
projects.

Negative Impacts of Technology on Modern Businesses:

Security Risks

Technology has also brought about security risks that

businesses must address. With the use of digital platforms,
businesses can now store and share sensitive information
online, making them vulnerable to cyber-attacks. This can
lead to the loss of customer data, financial losses, and
damage to the business’s reputation.

Cost

Implementing technology in businesses can be costly,

especially for small businesses. The cost of purchasing and
maintaining technology can be a significant challenge for
businesses that are just starting.

Over-reliance on Technology
Businesses that rely too much on technology risk being
disrupted if there is a failure in the technology. For
instance, if a business’s website goes down, it may not be
able to conduct transactions, leading to revenue loss.

Wrap Up

Technology has undoubtedly had a major impact on

modern businesses, both positive and negative. The
positive effects include improved efficiency, enhanced
communication, global reach, customer experience, and
collaboration. However, companies must also be aware of
the negative impacts, including job displacement,
increased competition, security risks, cost, and over-
reliance on technology.

Businesses need to navigate this dynamic landscape

carefully by understanding the various impacts of
technology and taking appropriate measures to mitigate
the negative effects. In doing so, businesses can harness
the benefits of technology to grow and succeed in the
modern world.
What is an expert system?
An expert system is a computer program that uses artificial intelligence (AI)
technologies to simulate the judgment and behavior of a human or an organization
that has expertise and experience in a particular field.

Expert systems are usually intended to complement, not replace, human experts.

The concept of expert systems was developed in the 1970s by computer scientist
Edward Feigenbaum, a computer science professor at Stanford University and
founder of Stanford's Knowledge Systems Laboratory. The world was moving
from data processing to "knowledge processing," Feigenbaum said in a 1988
manuscript. That meant computers had the potential to do more than basic
calculations and were capable of solving complex problems thanks to new
processor technology and computer architectures, he explained.

How does an expert system work?

Modern expert knowledge systems use machine learning and artificial
intelligence to simulate the behavior or judgment of domain experts. These
systems can improve their performance over time as they gain more experience,
just as humans do.

Expert systems accumulate experience and facts in a knowledge base and integrate
them with an inference or rules engine -- a set of rules for applying the knowledge
base to situations provided to the program.

What are the components of an expert system?

There are three main components of an expert system:

 The knowledge base. This is where the information the expert system
draws upon is stored. Human experts provide facts about the expert
system's particular domain or subject area are provided that are
organized in the knowledge base. The knowledge base often contains a
knowledge acquisition module that enables the system to gather
knowledge from external sources and store it in the knowledge base.

 The inference engine. This part of the system pulls relevant

information from the knowledge base to solve a user's problem. It is
a rules-based system that maps known information from the knowledge
base to a set of rules and makes decisions based on those inputs.
Inference engines often include an explanation module that shows users
how the system came to its conclusion.

 The user interface. This is the part of the expert system that end users
interact with to get an answer to their question or problem

Knowledge Management System

A knowledge management system (KMS) is a tool used by companies to help
organize documentation, frequently asked questions, and other information into
easily accessible formats for both internal and external customers.
Using knowledge management software can help keep documentation up to date,
assist customers in finding their own answers, and manage knowledge access and
permissions across user groups. It’s a tool that’s valuable to both small businesses
that are just starting out and global enterprises that need to distribute knowledge to a
wide variety of audiences.

Benefits of Knowledge Management System

1. Organizes and makes information accessible from a single source of truth

2. Keeps information up to date

3. Makes self-service functionalities more effective and deflects support tickets

4. Allows agents to share and reuse knowledge and learnings

5. Empowers customers to help themselves and improves customer satisfaction

6. Provides more detailed help to customers

Decision Support System

Broadly speaking, a decision support system (DSS) is an analytics software

program used to gather and analyze data to inform decision making. There
are many different types of decision support systems, from modern
business intelligence which uses AI and machine learning to suggest
insights and analyses for humans to perform, to model-based DSS systems
which use predefined criteria to perform automated calculations and deliver
best-case decisions. For all types, DSS is used in timely problem solving to
improve efficiency and streamline operations, planning and company
management.

Traditional vs Modern DSS

Traditional DSS: Historically, DSS and BI tools relied on
preconfigured, historical data with no ability to drive real-time
decisions and action. With this approach, decisions are made
based on the past.
Modern DSS: New tools and processes allow for “active
intelligence”, a state of continuous intelligence with an end-to-
end analytics data pipeline delivering real-time, up-to-date
information designed to trigger immediate insights and actions.
Three key elements that characterize a decision support system framework
are model management, organizational data (your knowledge base) and
user interface. Let’s briefly explore each.

Key Elements of Decision Support Systems are as follows

Model Management: To make effective decisions, especially those

made on an ongoing basis, it’s crucial for companies to develop key
performance indicators (KPI’s) from which to evaluate performance
against goals, and measure improvements over time. These KPI’s then
form the decision criteria for the information models used to guide decision
making. Having models provides the backbone of consistency every
business needs to sustain success. Models can be leveraged by formally
coded rules in DSS or prescriptive analytics software or by analysis
using a BI platform.

Organizational Data or Knowledge Base: Before any DSS can

be used, raw data must be transformed into clean, accurate, and up-to-date
information. The graphic below illustrates how different types of data are
combined, cleaned and transformed into standardized formats. The data is
then stored in a repository such as a data lake or data warehouse using a
governed data catalog.

User Interface: You’ve stared at enough dense tables of numbers to

appreciate why it’s so necessary to have a more digestible and user-
friendly way to consume data. A user interface, complete with digital
dashboards, tables, graphs, widgets or other tools to present information,
enables users to better interact with, view, and use the data at their
disposal.

Executive Information Systems

An executive information system (EIS) is a decision support system (DSS) used to

assist senior executives in the decision-making process. It does this by providing
easy access to important data needed to achieve strategic goals in an
organization. An EIS normally features graphical displays on an easy-to-use
interface.

Executive information systems can be used in many different types of

organizations to monitor enterprise performance as well as to identify
opportunities and problems.

The typical EIS has four components: hardware, software, user interface and
telecommunication

Hardware

An EIS’s hardware should include input devices that executives can use to
enter, check, and update data; a central processing unit (CPU) that controls
the entire system; data storage for saving and archiving useful business
information; and output devices (e.g., monitors, printers, etc.) that show
visual representations of the data executives need to keep or read.

Software

An EIS’s software should be able to integrate all available data into

cohesive results. It should be capable of handling text and graphics;
connected to a database that contains all relevant internal and external
data; and have a model base that performs routine and special statistical,
financial, and other quantitative analyses.

User interface (UI)

This component should be capable of producing scheduled reports, FAQs,

and other information. It would be best if it’s menu-driven, too, allowing
executives to pick from predetermined choices for their needs. And since
not all executives are tech-savvy, it’s ideal for the UI to accept inputs and
produce outputs using programming (i.e., for the tech-savvy) and natural
language (i.e., for the not tech-savvy).
Telecommunications capability

Since most executives often travel, an EIS should have

telecommunications capability. That way, it remains accessible regardless
of location.

What Are the Benefits of Using an Executive Information System?

Using an EIS provides the following benefits:

 Easy for any executive to use

 Provides the ability to analyze trends
 Augments an executive’s leadership capabilities
 Enhances personal thinking and decision-making
 Makes strategic control flexible
 Enhances an organization’s market competitiveness
 Creates better reports
 Improves consensus building and communication
 Enables office automation
 Reduces time required to find information
 Enables company performance predictions
 Allows detailed examinations of critical success factors

What Are the Disadvantages of Using an Executive Information System?

Despite providing several advantages, EIS usage has cons, too, such as:

 Limited functionality
 Hard to quantify the benefits
 Possible information overload on an executive’s part
 System may become slow over time
 May lead to system insecurities
 May be too expensive for small companies
centralized and distributed processing in mis

Basis of Centralized
S.NO. Comparison database Distributed database

It is a database that
It is a database that consists of multiple
is stored, located as databases which are
1. Definition well as maintained connected with each other
at a single location and are spread across
only. different physical
locations.

2. Access time The data access The data access time in

time in the case of the case of multiple users
multiple users is is less in a distributed
more in a centralized database.
 Basis of Centralized
S.NO. Comparison database Distributed database

database.

The management,
The management,
modification, and
modification, and backup
backup of this
Management of this database are very
3. database are easier
of data difficult as it is spread
as the entire data is
across different physical
present at the same
locations.
location.

This database Since it is spread across

provides a uniform different locations thus it is
4. View
and complete view difficult to provide a
to the user. uniform view to the user.

This database has

This database may have
more data
Data some data replications
5. consistency in
Consistency thus data consistency is
comparison to
less.
distributed database.

The users cannot In a distributed database,

access the database if one database fails users
6. Failure
in case of database have access to other
failure occurs. databases.

A centralized
This database is very
7. Cost database is less
expensive.
costly.

Ease of
It is difficult to maintain
maintenance
because of the distribution
because the whole
of data and information at
of the data and
varied places. So, there is
8. Maintenance information is
a need to check for data
available at a single
redundancy issues and
location and thus,
how to maintain data
easy to reach and
consistency.
access.
 Basis of Centralized
S.NO. Comparison database Distributed database

A centralized
A distributed database is
database is less
more efficient than a
efficient as data
centralized database
finding becomes
because of the splitting up
9. Efficient quite complex
of data at several places
because of the
which makes data finding
storing of data and
simple and less time-
information at a
consuming.
particular place.

The response speed

The response speed is
Response is more in
10. less in comparison to a
Speed comparison to a
centralized database.
distributed database.

 High performance
because of the division
 Integrity of data of workload.
 Security  High availability
 Easy access to because of the
11. Advantages
all information readiness of available
 Data is easily nodes to do work.
portable  Independent nodes
and better control over
resources

 Data searching
 It is quite large and
takes time
complex so difficult to
 In case of failure
use and maintain.
of a centralized
 Difficult to provide
server, the whole
security
database will be
12. Disadvantages  Issue of data integrity
lost.
 Increase in storage
 If multiple users
and infrastructure
try to access the
requirements
data at the same
 Handling failures is a
time then it may
quite difficult task
create issues.

13. Examples  A desktop or  Apache Ignite

server CPU  Apache Cassandra
 Basis of Centralized
S.NO. Comparison database Distributed database

 Apache HBase
 A mainframe  Amazon SimpleDB
computer.  Clusterpoint
 FoundationDB.

Multimedia Approach to Information Processing

The traditional approaches to instruction are inadequate for
providing learner centered and appropriate experiences to the
students. In this situation, modern approach like multimedia
approach can play a prominent role in providing effective
learning experiences to the students. For transacting curriculum
material in an effective way, a teacher can depend upon the
multimedia approach confidently.
There are many modes of instruction, which require
use of several media-audio, visual and audio-visual. The learning
experiences provided through such media can be designated as
mediated experiences. Use of single medium cannot fulfill all the
requirements of developmental education. Hence, the use of
various media has to be judiciously combined. Although one of
the media could be the ‘Master Medium’, other media also should
be used so that quality of presentation becomes maximally
effective, resulting in totality of development.
MULTIMEDIA APPROACH
Multimedia is the digital integration of text(written), Graphics
(the interface of the program), Animation, Audio (dialogues,
Stories, Sound effects), Still images (Pictures and Visual Stimuli),
Motion video etc. Through the integration of all these media, the
learning experiences become an interactive one mirroring every
day experiences. Multimedia materials, however, combine all of
these media providing teachers with a package offering flexibility
 and ease of use as well as more “realistic” contexts for language
practice. Learning experiences provided through such media can
be called as mediated experience. When we integrate more than
one medium in teaching it is known as media mix multimedia
approach and integrated media approach.
THE EDUCATIONAL VALUES OF THE
MULTIMEDIA APPROACH
1. Multimedia approach can convey vast information and can
provide many sources from which students can get access to the
information.
2. Through multimedia approach a large number of models of
learning can be practiced over a great range of content.
3. Multimedia approach provides the opportunity to gain mastery of
competencies and skills which are based on theoretical
knowledge.
4. Multimedia approach is not restricted to a single type of learning
style or instructional mode. It can provide the support of a wide
range of activities.