What is the artificial intelligence industry? Potential and job opportunities in the Vietnamese market.

The artificial intelligence industry in Vietnam has made significant progress and is a top priority technology not only in Vietnam but also in the world. The investment of large enterprises has shown the development potential of this industry in the future. Let 1C Vietnam learn about the development potential, job opportunities as well as the main specialties of the artificial intelligence (AI) industry in the article below.

1. What is artificial intelligence (AI) industry?

Artificial intelligence (AI) is a field in computer science that focuses on creating machines and systems capable of performing human-like tasks. AI is widely applied in many fields from industrial automation, transportation, healthcare, marketing, education, etc. \

Specialties in the artificial intelligence industry include:

• Computer Vision
• Fuzzy Logic System
• Expert systems
• Robotics
• Machine Learning
• Natural language processing (natural network/ deep learning)

2. Potential and job opportunities of the artificial intelligence industry in Vietnam

According to the report on the "Government's Artificial Intelligence Readiness Index 2023", Vietnam ranks 5th out of 10 ASEAN, up 1 level compared to 2022 and ranked 59th out of 193 global countries. Besides, the young and dynamic economy creates huge opportunities for the artificial intelligence industry. Currently, Vietnam owns 4 technology unicorns: Momo, Sky Mavis, VNG and VN Life.

Vietnam is currently one of 60 countries in the world that has launched a national strategy on artificial intelligence development. The Minister of Science and Technology said that after 2 years of implementing the "National Strategy on research, development and application of artificial intelligence until 2030", Vietnam has achieved remarkable results, Many products have been applied in life.

With society's interest and government investment in AI, job opportunities in the artificial intelligence industry in Vietnam will continue to increase in the future.

3. Main specialties of artificial intelligence industry

3.1. Computer vision

This is one of the most popular branches of artificial intelligence today, with the aim of developing techniques that help computers see and understand digital images and videos. Applying machine learning models to images allows computers to identify objects, faces, people, and animals. Algorithmic models help computers learn about the context of visual data, and with enough data fed through the model, computers can teach themselves how to distinguish one image from another.

Computer vision applies in many industries, such as:

• Object tracking: track and identify objects
• Image classification: some images are correctly classified and predicted to belong to certain classes
• Facial recognition: face unlock on smartphones by mapping and matching facial features

3.2. Fuzzy Logic System

Fuzzy logic system is a technique that helps solve problems or statements that can be true or false. This method replicates human decisions by considering the possibilities available between the values ​​“yes” or “no”. In other words, this system measures how true a hypothesis is.

You can use this system to reason about uncertain topics. It is a convenient and flexible way to deploy machine learning techniques and replicate human thinking in a reasonable way.

The open logic system includes 4 parts:

• Rule base: Has all the if-then rules and conditions
• Fuzzification module: Helps transform input
• Inference engine: determines the degree of agreement between the rules and the fuzzy input
• The Defuzzification module converts fuzzy sets into crisp values.

For example, Nissan companies use a fuzzy logic system to control stopping in dangerous situations, depending on the acceleration, speed, and wheel friction of each car.

3.3. Expert systems

An expert system is a program that specializes in performing a single task. The system is primarily designed to solve complex problems using human-like decision-making capabilities.

They use a set of rules, called inference rules, whose knowledge base is determined by the data that has been provided. Using if-then logic concepts, they can solve complex problems and help with information management, virus detection, loan analysis.

The first expert systems were developed in the 1970s and contributed greatly to the success of artificial intelligence. An example of an expert system is CaDeT, a diagnostic support system that can help medical professionals detect cancer in its early stages.

3.4. Robotics

Robots are programmed machines that can automatically perform a series of complex actions. They are controlled by external devices or their control system can be embedded internally.

Robots help humans perform tedious and repetitive tasks. In particular, AI-powered robots can help companies like NASA explore space. Humanoid robots are the latest developments and the more famous examples of robot evolution.

Sophia, a robot developed by Hanson Robotics, operates through a combination of artificial intelligence and neural networks. She recognizes human faces and understands emotions and gestures – and can even interact with people. Common examples of robots in everyday life applications include industries such as manufacturing, healthcare, retail, etc.

3.5. Machine Learning

Machine learning is the ability to learn automatically from data and algorithms, and is one of the most demanding branches of artificial intelligence. Machine learning improves performance by using past experiences to make decisions without being specifically programmed. This process involves collecting historical data, such as instruction and direct experience, so that logical models can be built for future inferences. Output accuracy depends on data size - larger amounts of data build a better model, thereby increasing model accuracy. Machine learning algorithms are classified into three types:

• Supervised learning. Machines are trained with labeled data to predict outcomes.
• Unsupervised learning. Machines are trained with unlabeled data, with the model extracting information from the input to identify features and patterns so it can produce results.
• Reinforcement learning. Machines learn through trial and error, using feedback to shape actions

3.6. Natural language processing (natural network/ deep learning)

Neural networks are also known as artificial neural networks (ANN) or neural networks (SNN). At the heart of deep learning algorithms, neural networks are inspired by the human brain and they replicate biological neurons to transmit signals to each other. ANN has layers of nodes, including an input layer, one or more hidden layers, and an output layer. Each node, also known as an artificial neuron, connects to other neurons and has associated thresholds and weights. When the output of an individual node exceeds a specified threshold value, that node is triggered to send data to the next network layer. Neural networks use training data to both learn and improve accuracy.

In general, the artificial intelligence industry in Vietnam is still very new and has a lot of potential for development. Understanding the development potential and majors will help you find the right path for development. own. Follow 1C Vietnam now to receive the latest news about the artificial intelligence industry in Vietnam and around the world.