SCIENCE AND INNOVATION IN THE
EDUCATION SYSTEM
International scientific-online conference
15
ARTIFICIAL INTELLIGENCE-BASED MODELING: AUTOMATION,
INTELLIGENT SYSTEMS, APPLICATIONS, AND RESEARCH.
Saidov Umedjon Yusuf o’g’li
Bukhara State University teacher.
E-mail:saidovumid7744@gmail.com
https://doi.org/10.5281/zenodo.11504790
Artificial intelligence has completely changed the way we live with
innovative technologies. Artificial intelligence has entered human life very
quickly and has made incredible changes, taking its toll on every area of society.
The term artificial intelligence was first introduced at a conference in 1956[1].
The discussion at the conference led to the natural language generation of
interdisciplinary information technology. The emergence of the internet
contributed to the rapid development of technology. Artificial intelligence
technology has been an independent technology for thirty years, but now this
technology has become widespread in all spheres of life. Artificial intelligence is
known by the acronym AI and is the process of recreating human intelligence in
machines.
Many new and emerging technologies are integrated into artificial intelligence.
Startups of giant organizations are participating in major races to increase
productivity and artificial intelligence for the intellectual analysis of data.
According to Gartner's forecasts, AI personal computer deliveries in 2024
account for 22% of total personal computer deliveries, and by the end of 2026,
100% of corporate personal computer purchases will be AI computers[2]. AI
personal computers include a neural processor (NPU), which allows AI personal
computers to run longer, quieter, and colder, perform AI tasks continuously in
the background, and provide new opportunities for using AI in daily
activities[2].
Let's discuss the nine most recent technologies of artificial intelligence in this
article. Latest artificial intelligence technologies
The first place on the list of technologies of artificial intelligence, that are
considered relevant in 2024, is occupied by the generation of natural language:
Natural language generation. Machines process and communicate differently
from the human brain. Natural language generation is a modern technology that
converts structured data into a native language. The machines are programmed
with algorithms to convert the data to the format the user needs. Natural
language is a subset of artificial intelligence that helps content developers
automate content and deliver it in the desired format. Content developers can
SCIENCE AND INNOVATION IN THE
EDUCATION SYSTEM
International scientific-online conference
16
use automated content to advertise on various social media platforms and other
media platforms to reach the target audience. Human interference is
significantly reduced as the data is converted to the desired formats. Data can be
displayed in the form of diagrams, graphs, etc. In second place is the technology
of speech recognition.
Speech recognition. Speech recognition is another important set of artificial
intelligence that transforms human speech into a useful and understandable
format by computers. Speech recognition is a bridge between human and
computer interaction. The technology recognizes and alters human speech in
several languages. Alice in Yandex is a classic example of speech recognition. The
third place went to Virtual agent technology, which is now important:
Virtual agent. Virtual agents have become valuable tools for training designers. A
Virtual Agent is a computer application that interacts with people. Web
applications and mobile applications provide chatbots to customers as service
agents to collaborate with them and answer their questions. For example,
Google Assistant and Chatgpt help organize meetings, while Alexia from Amazon
makes it convenient for purchases to be made. The Virtual assistant also works
like a language assistant that selects tips on your choice and desire. IBM Watson
understands typical customer service requests requested in several ways[3].
Virtual agents also serve as applications. At the same time, decision management
technology, which is currently in need, especially in large enterprises and
organizations, is located in the fourth place on the list:
Decision management. Modern organizations are implementing decision
management systems to transform and interpret data into predictive models.
Enterprise-level applications implement decision management systems with the
aim of obtaining up-to-date information in the analysis of business data to assist
in organizational decision-making. Decision management helps you make quick
decisions, avoid risks, and automate the process. The decision management
system is widely used in the financial sector, health, trade, insurance, e-
commerce, and other industries.
And the fifth step of the list is occupied by deep learning technology:
Deep learning. Another area of artificial intelligence that works based on
artificial neural networks is deep learning. This technique teaches you to learn
computers and machines just like people do. The term "Deep" was coined
because it has hidden layers in neural networks. Deep learning is effective in
large data for teaching the model and graphic processing block. Algorithms work
in a hierarchy of predictive analysis automation. In-depth study is being used
SCIENCE AND INNOVATION IN THE
EDUCATION SYSTEM
International scientific-online conference
17
with success in many fields, such as aerospace and military, to detect objects
from satellites, help improve workers ' safety by detecting dangerous
phenomena when approaching a working machine, help identify cancer cells,
and assist in other matters.
Another of the significant technologies of this year was machine learning, which
took the sixth position on the list.
Machine learning. Machine learning is an artificial intelligence unit that allows a
machine to extract meaning from a dataset without being programmed. Machine
learning techniques help businesses make informed decisions with data analysis
performed using algorithms and statistical models[4]. Businesses are investing
heavily in machine learning to benefit from its use in various industries. It needs
machine learning methods to analyze patient data to predict and effectively treat
diseases such as health and medicine. The banking and financial sector needs
machine learning to identify and offer investment opportunities to customers
and analyze customer data to prevent risk and fraud. Retailers use machine
learning to predict changes in customer preferences, and consumer behavior by
analyzing customer data. Another style of artificial intelligence technologies,
such as process robotization automation, is in seventh place:
Automation of processes by robotization. Process robotics automation is an
artificial intelligence application that configures a robot (software application)
to interpret, communicate, and analyze data. This discipline of artificial
intelligence helps automate repetitive and rule-based partial or complete
manual operations.
Hardware tools optimized for artificial intelligence. Artificial intelligence
software is in high demand in the business world. With the increased attention
to software, the need for hardware that supports software also arises. The
traditional chip does not support artificial intelligence models. A new generation
of artificial intelligence chips is being developed for neural networks, deep
learning, and computer vision. AI hardware includes processors to control
extensible workloads, custom-purpose embedded silicon for neural networks,
neuromorphic chips, and more[5]. Large organizations such as Nvidia,
Qualcomm, and AMD are creating chips that can handle complex artificial
intelligence accounts. Health and the automotive industry can be areas that
benefit from these chips.
Conclusion. In conclusion, artificial intelligence will reflect computational
models of intelligence. Intelligence can be defined as structures, models, and
operational functions that can be programmed to solve problems, draw
SCIENCE AND INNOVATION IN THE
EDUCATION SYSTEM
International scientific-online conference
18
conclusions, process language, etc. The benefits of using artificial intelligence
have already been obtained in many areas. Organizations that apply artificial
intelligence must perform tests before the release to eliminate errors and errors.
The design and models should be solid. After the release of artificial systems,
enterprises must constantly monitor different scenarios. Organizations must
create and support standards and hire professionals from different disciplines to
make better decisions. The objective and future goals of artificial intelligence are
to eliminate mistakes and prejudices by automating all complex human
activities.
References:
1.
Nilsson, N., The Quest for Artificial Intelligence, Cambridge University
Press, 2010, p. 53
2.
"Gartner, Inc. 2023 Annual Report (Form 10-K)". U.S. Securities and
Exchange Commission. February 16, 2024.
3.
"DeepQA Project: FAQ". IBM. Archived from the original on June 29, 2011.
Retrieved February 11, 2011.
4.
"What is Machine Learning?". IBM. Archived from the original on 2023-12-
27. Retrieved 2023-06-27.
5.
Ham, Donhee; Park, Hongkun; Hwang, Sungwoo; Kim, Kinam (2021).
"Neuromorphic electronics based on copying and pasting the brain". Nature
Electronics. 4 (9): 635–644.
