Artificial intelligence

About Artificial Intelligence

Given the continuous development of science, technology, and innovations, countries around the world are striving to implement digital systems across industries, widely using artificial intelligence technologies to simplify labor, save time, and improve the efficiency of various sectors.
Artificial intelligence is one of the most powerful processes of the 21st century, and its implementation will have a positive impact on the acceleration of production processes, as well as the distribution of goods, work, and services. These technologies are penetrating all spheres of the global socio-economic system and form the foundation of development.
The introduction of artificial intelligence plays a significant role in all spheres of human activity and, through the promotion of the philosophy of "disruptive" development, can become one of the driving forces of the economy, significantly boosting productivity and labor efficiency.

Legal regulations governing the industry

Strategy for the development of artificial intelligence in the Republic of Tajikistan for the period up to 2040

Reference: http://www.portali-huquqi.tj/publicadliya/view_qonunhoview.php?showdetail=&asosi_id=26592

Artificial Intelligence Alphabet

The Artificial Intelligence Alphabet serves as a foundation for understanding key concepts, methods, and technologies in the field of artificial intelligence. This alphabet is aimed at clarifying the main terms and concepts used in AI.

A brief description of some key concepts and terms:

A – Algorithms
Algorithms are a set of clear steps used to solve tasks or perform operations. In artificial intelligence, algorithms are used for learning and data processing.

B – Bots
Bots are automated programs that perform specific tasks. For example, chatbots are used for communication with users.

C – Convolutional Neural Networks (CNN)
CNNs are neural networks designed to process images and spatial data. They are widely used for image and video recognition.

D – Big Data
Large volumes of data characterized by volume, variety, and speed of increase. Big data is crucial for training and analyzing artificial intelligence.

E – Emotion AI
Technologies that detect human emotions through facial recognition, voice, and text analysis.

F – Federated Learning
A method that allows training AI models using decentralized data that remains on devices and is not transferred to a central server.

G – Generative Adversarial Networks (GAN)
GANs consist of two neural networks: a generator and a discriminator, which compete against each other. They are used to create new data.

H – Hidden Layers
Used in neural networks. Hidden layers are located between the input and output layers and process data.

I – Supervised Learning
A method where AI is trained using labeled training data with known labels or outcomes.

J – Joint Statistical Language Modeling
A method for analyzing and predicting text using linguistic data.

K – Reinforcement Learning
A method where AI learns to interact with the environment through rewards and punishments.

L – Machine Learning
Methods that allow algorithms and models to learn from data and make decisions.

M – Joint Statistical Models
Used for analyzing multiple datasets simultaneously.

N – Neural Networks
Mathematical models inspired by the human brain that are used for pattern recognition, text processing, and prediction.

O – Optimization
The process of finding the best parameter values for AI models to achieve optimal results.

P – Natural Language Processing (NLP)
Methods and algorithms for recognizing, analyzing, and generating natural language.

Q – Quantum Computing
Computer technologies that use the laws of quantum mechanics applied for AI analysis.

R – Recurrent Neural Networks (RNN)
Neural networks with recurrent connections, used for processing sequential data such as text and time series.

S – Unsupervised Learning
A method where AI learns from unlabeled data, with no prior known outcomes.

T – Image Analysis
Technologies for recognizing objects and patterns in images and videos.

U – Understanding Meaning
Analysis and interpretation of data, text, and images using AI.

V – Video Analysis
Technologies for analyzing content and movement in video material.

W – Weights
Numerical values that define the connections between neurons in neural networks.

X – Cross-Domain AI Applications
The use of AI in various fields, including healthcare, finance, commerce, and manufacturing.

Y – Data Fusion
Methods for combining data from different sources for deeper analysis.

Z – Artificial Intelligence (AI)
Systems and programs capable of thinking, learning, and making decisions.

This alphabet helps to better understand the key AI concepts and their applications in various systems and programs.

Suggestions on the Issue of Artificial Intelligence

Department for Innovation Development and Support of Commercialization of Scientific and Technical Results
Phone: (992 37) 233-30-37
(992 37) 233-30-38
(992 37) 233-30-39

List of higher education institutions and AI training centers